{
  "01-ai/yi-1.5-34b-chat.description": "01.AI’s latest open-source fine-tuned model with 34B parameters, supporting multiple dialogue scenarios, trained on high-quality data and aligned with human preferences.",
  "01-ai/yi-1.5-9b-chat.description": "01.AI’s latest open-source fine-tuned model with 9B parameters, supporting multiple dialogue scenarios, trained on high-quality data and aligned with human preferences.",
  "360/deepseek-r1.description": "360-deployed DeepSeek-R1 uses large-scale RL in post-training to greatly boost reasoning with minimal labels. It matches OpenAI o1 on math, code, and natural language reasoning tasks.",
  "360gpt-pro-trans.description": "A translation-specialized model, deeply fine-tuned for leading translation quality.",
  "360gpt-pro.description": "360GPT Pro is a key 360 AI model with efficient text processing for diverse NLP scenarios, supporting long-text understanding and multi-turn dialogue.",
  "360gpt-turbo-responsibility-8k.description": "360GPT Turbo Responsibility 8K emphasizes semantic safety and responsibility for content-sensitive applications, ensuring accurate and robust user experiences.",
  "360gpt-turbo.description": "360GPT Turbo delivers strong compute and chat capability with excellent semantic understanding and generation efficiency, ideal for enterprise and developers.",
  "360gpt2-o1.description": "360gpt2-o1 builds chain-of-thought via tree search with a reflection mechanism and RL training, enabling self-reflection and self-correction.",
  "360gpt2-pro.description": "360GPT2 Pro is an advanced NLP model from 360 with excellent text generation and understanding, especially for creative tasks, handling complex transformations and roleplay.",
  "360zhinao2-o1.5.description": "360 Zhinao most powerful reasoning model, featuring the strongest capabilities and supporting both tool calling and advanced reasoning.",
  "360zhinao2-o1.description": "360zhinao2-o1 builds chain-of-thought via tree search with a reflection mechanism and RL training, enabling self-reflection and self-correction.",
  "360zhinao3-o1.5.description": "360 Zhinao Next-Generation Reasoning Model.",
  "4.0Ultra.description": "Spark Ultra is the most powerful model in the Spark series, improving text understanding and summarization while upgrading web search. It is a comprehensive solution for boosting workplace productivity and accurate responses, positioning it as a leading intelligent product.",
  "AnimeSharp.description": "AnimeSharp (aka \"4x-AnimeSharp\") is an open-source super-resolution model based on ESRGAN by Kim2091, focused on upscaling and sharpening anime-style images. It was renamed from \"4x-TextSharpV1\" in February 2022, originally also for text images but heavily optimized for anime content.",
  "Baichuan-M2-Plus.description": "We introduce Baichuan-M2, a medically-enhanced reasoning model, designed for real-world medical reasoning tasks. We start from real-world medical questions and conduct reinforcement learning training based on a large-scale verifier system. While maintaining the model's general capabilities, the medical effectiveness of the Baichuan-M2 model has achieved a breakthrough improvement. Baichuan-M2 is the best open-source medical model in the world to date. It surpasses all open-source models, including gpt-oss-120b, as well as many cutting-edge closed-source models on the HealthBench Benchmark. It is the open-source model closest to GPT-5 in medical capabilities. Our practice demonstrates that a robust verifier is crucial for linking model capabilities to the real world and an end-to-end reinforcement learning approach fundamentally enhances the model's medical reasoning abilities. The release of Baichuan-M2 advances the cutting edge of technology in the field of medical artificial intelligence.",
  "Baichuan-M2.description": "We introduce Baichuan-M2, a medically-enhanced reasoning model, designed for real-world medical reasoning tasks. We start from real-world medical questions and conduct reinforcement learning training based on a large-scale verifier system. While maintaining the model's general capabilities, the medical effectiveness of the Baichuan-M2 model has achieved a breakthrough improvement. Baichuan-M2 is the best open-source medical model in the world to date. It surpasses all open-source models, including gpt-oss-120b, as well as many cutting-edge closed-source models on the HealthBench Benchmark. It is the open-source model closest to GPT-5 in medical capabilities. Our practice demonstrates that a robust verifier is crucial for linking model capabilities to the real world and an end-to-end reinforcement learning approach fundamentally enhances the model's medical reasoning abilities. The release of Baichuan-M2 advances the cutting edge of technology in the field of medical artificial intelligence.",
  "Baichuan-M3-Plus.description": "We introduce Baichuan-M3, a new-generation medical-enhanced large language model designed to support clinical-grade medical assistance. In contrast to prior approaches that primarily focus on static question answering or superficial role-playing, Baichuan-M3 is trained to explicitly model the clinical decision-making process, aiming to improve usability and reliability in real-world medical practice. Rather than merely producing plausible-sounding answers, fluent doctor-like questioning, or high-frequency but vague recommendations such as “you should seek medical attention as soon as possible,” Baichuan-M3 is explicitly trained to proactively acquire critical clinical information, construct coherent medical reasoning pathways, and systematically constrain hallucination-prone behaviors throughout the decision process. This design endows the model with intrinsic medical-enhanced capabilities aligned with real clinical workflows. Across evaluations of clinical inquiry, medical hallucination robustness, HealthBench, and HealthBench-Hard, Baichuan-M3 surpasses the latest flagship model released by OpenAI, GPT-5.2, establishing a new state of the art in medical-enhanced language models.",
  "Baichuan-M3.description": "We introduce Baichuan-M3, a new-generation medical-enhanced large language model designed to support clinical-grade medical assistance. In contrast to prior approaches that primarily focus on static question answering or superficial role-playing, Baichuan-M3 is trained to explicitly model the clinical decision-making process, aiming to improve usability and reliability in real-world medical practice. Rather than merely producing plausible-sounding answers, fluent doctor-like questioning, or high-frequency but vague recommendations such as “you should seek medical attention as soon as possible,” Baichuan-M3 is explicitly trained to proactively acquire critical clinical information, construct coherent medical reasoning pathways, and systematically constrain hallucination-prone behaviors throughout the decision process. This design endows the model with intrinsic medical-enhanced capabilities aligned with real clinical workflows. Across evaluations of clinical inquiry, medical hallucination robustness, HealthBench, and HealthBench-Hard, Baichuan-M3 surpasses the latest flagship model released by OpenAI, GPT-5.2, establishing a new state of the art in medical-enhanced language models.",
  "Baichuan2-Turbo.description": "Uses search augmentation to connect the model with domain and web knowledge. Supports PDF/Word uploads and URL inputs for timely, comprehensive retrieval and professional, accurate outputs.",
  "Baichuan3-Turbo-128k.description": "With a 128K ultra-long context window, it is optimized for high-frequency enterprise scenarios with major gains and strong value. Compared to Baichuan2, content creation improves by 20%, knowledge QA by 17%, and roleplay by 40%. Overall performance is better than GPT-3.5.",
  "Baichuan3-Turbo.description": "Optimized for high-frequency enterprise scenarios with major gains and strong value. Compared to Baichuan2, content creation improves by 20%, knowledge QA by 17%, and roleplay by 40%. Overall performance is better than GPT-3.5.",
  "Baichuan4-Air.description": "A top-performing model in China, surpassing major overseas models on Chinese tasks like knowledge, long-form text, and creative generation. It also features industry-leading multimodal capabilities with strong results on authoritative benchmarks.",
  "Baichuan4-Turbo.description": "A top-performing model in China, surpassing major overseas models on Chinese tasks like knowledge, long-form text, and creative generation. It also features industry-leading multimodal capabilities with strong results on authoritative benchmarks.",
  "Baichuan4.description": "Top domestic performance, surpassing leading overseas models on Chinese tasks like encyclopedic knowledge, long text, and creative generation. Also offers industry-leading multimodal capabilities and strong benchmark results.",
  "ByteDance-Seed/Seed-OSS-36B-Instruct.description": "Seed-OSS is a family of open-source LLMs from ByteDance Seed, designed for strong long-context handling, reasoning, agent, and general abilities. Seed-OSS-36B-Instruct is a 36B instruction-tuned model with native ultra-long context for processing large documents or codebases. It is optimized for reasoning, code generation, and agent tasks (tool use) while retaining strong general ability. A key feature is \"Thinking Budget,\" allowing flexible reasoning length to improve efficiency.",
  "DeepSeek-OCR.description": "DeepSeek-OCR is a vision-language model from DeepSeek AI focused on OCR and \"context optical compression.\" It explores compressing context from images, efficiently processes documents, and converts them to structured text (e.g., Markdown). It accurately recognizes text in images, suited for document digitization, text extraction, and structured processing.",
  "DeepSeek-R1-Distill-Llama-70B.description": "DeepSeek R1, the larger and smarter model in the DeepSeek suite, is distilled into the Llama 70B architecture. Benchmarks and human evals show it is smarter than the base Llama 70B, especially on math and fact-precision tasks.",
  "DeepSeek-R1-Distill-Qwen-1.5B.description": "A DeepSeek-R1 distilled model based on Qwen2.5-Math-1.5B. Reinforcement learning and cold-start data optimize reasoning performance, setting new multi-task benchmarks for open models.",
  "DeepSeek-R1-Distill-Qwen-14B.description": "A DeepSeek-R1 distilled model based on Qwen2.5-14B. Reinforcement learning and cold-start data optimize reasoning performance, setting new multi-task benchmarks for open models.",
  "DeepSeek-R1-Distill-Qwen-32B.description": "The DeepSeek-R1 series improves reasoning performance with reinforcement learning and cold-start data, setting new multi-task benchmarks for open models and surpassing OpenAI o1-mini.",
  "DeepSeek-R1-Distill-Qwen-7B.description": "A DeepSeek-R1 distilled model based on Qwen2.5-Math-7B. Reinforcement learning and cold-start data optimize reasoning performance, setting new multi-task benchmarks for open models.",
  "DeepSeek-R1.description": "State-of-the-art efficient LLM, strong at reasoning, math, and coding.",
  "DeepSeek-V3-1.description": "DeepSeek V3.1 is a next-gen reasoning model with improved complex reasoning and chain-of-thought, suited for deep analysis tasks.",
  "DeepSeek-V3-Fast.description": "Provider: sophnet. DeepSeek V3 Fast is the high-TPS version of DeepSeek V3 0324, full-precision (non-quantized) with stronger code and math and faster responses.",
  "DeepSeek-V3.1-Think.description": "DeepSeek-V3.1 thinking mode: a new hybrid reasoning model with thinking and non-thinking modes, more efficient than DeepSeek-R1-0528. Post-training optimizations significantly improve agent tool use and agent task performance.",
  "DeepSeek-V3.2.description": "deepseek-v3.2 introduces sparse attention mechanism, aiming to improve training and inference efficiency when processing long texts, priced lower than deepseek-v3.1.",
  "DeepSeek-V3.description": "ByteDance Volcengine’s open deployment is currently the most stable; recommended. It has been auto-upgraded to the latest release (250324).",
  "Doubao-lite-128k.description": "Doubao-lite offers ultra-fast responses and better value, with flexible options across scenarios. Supports 128K context for inference and fine-tuning.",
  "Doubao-lite-32k.description": "Doubao-lite offers ultra-fast responses and better value, with flexible options across scenarios. Supports 32K context for inference and fine-tuning.",
  "Doubao-lite-4k.description": "Doubao-lite offers ultra-fast responses and better value, with flexible options across scenarios. Supports 4K context for inference and fine-tuning.",
  "Doubao-pro-128k.description": "Best-performing flagship model for complex tasks, strong in reference QA, summarization, creation, classification, and roleplay. Supports 128K context for inference and fine-tuning.",
  "Doubao-pro-32k.description": "Best-performing flagship model for complex tasks, strong in reference QA, summarization, creation, classification, and roleplay. Supports 32K context for inference and fine-tuning.",
  "Doubao-pro-4k.description": "Best-performing flagship model for complex tasks, strong in reference QA, summarization, creation, classification, and roleplay. Supports 4K context for inference and fine-tuning.",
  "DreamO.description": "DreamO is an open-source image customization model jointly developed by ByteDance and Peking University, using a unified architecture to support multi-task image generation. It employs efficient compositional modeling to generate highly consistent, customized images based on user-specified identity, subject, style, background, and other conditions.",
  "ERNIE-3.5-128K.description": "Baidu’s flagship large-scale LLM trained on massive Chinese/English corpora with strong general ability for chat, creation, and plugin use; supports automatic Baidu Search plugin integration for fresh answers.",
  "ERNIE-3.5-8K-Preview.description": "Baidu’s flagship large-scale LLM trained on massive Chinese/English corpora with strong general ability for chat, creation, and plugin use; supports automatic Baidu Search plugin integration for fresh answers.",
  "ERNIE-3.5-8K.description": "Baidu’s flagship large-scale LLM trained on massive Chinese/English corpora with strong general ability for chat, creation, and plugin use; supports automatic Baidu Search plugin integration for fresh answers.",
  "ERNIE-4.0-8K-Latest.description": "Baidu’s flagship ultra-large LLM with comprehensive upgrades over ERNIE 3.5, suitable for complex tasks across domains; supports Baidu Search plugin integration for fresh answers.",
  "ERNIE-4.0-8K-Preview.description": "Baidu’s flagship ultra-large LLM with comprehensive upgrades over ERNIE 3.5, suitable for complex tasks across domains; supports Baidu Search plugin integration for fresh answers.",
  "ERNIE-4.0-Turbo-8K-Latest.description": "Baidu’s flagship ultra-large LLM with strong overall performance for complex tasks, with Baidu Search plugin integration for fresh answers. It outperforms ERNIE 4.0.",
  "ERNIE-4.0-Turbo-8K-Preview.description": "Baidu’s flagship ultra-large LLM with strong overall performance for complex tasks, with Baidu Search plugin integration for fresh answers. It outperforms ERNIE 4.0.",
  "ERNIE-Character-8K.description": "Baidu’s vertical-domain LLM for game NPCs, customer service, and roleplay, with clearer persona consistency, stronger instruction following, and better reasoning.",
  "ERNIE-Lite-Pro-128K.description": "Baidu’s lightweight LLM balancing quality and inference performance, better than ERNIE Lite and suitable for low-compute accelerators.",
  "ERNIE-Speed-128K.description": "Baidu’s latest high-performance LLM (2024) with strong general ability, suitable as a base for fine-tuning to handle specific scenarios, with excellent reasoning performance.",
  "ERNIE-Speed-Pro-128K.description": "Baidu’s latest high-performance LLM (2024) with strong general ability, better than ERNIE Speed, suitable as a base for fine-tuning with excellent reasoning performance.",
  "FLUX-1.1-pro.description": "FLUX.1.1 Pro",
  "FLUX.1-Kontext-dev.description": "FLUX.1-Kontext-dev is a multimodal image generation and editing model from Black Forest Labs based on a Rectified Flow Transformer architecture with 12B parameters. It focuses on generating, reconstructing, enhancing, or editing images under given context conditions. It combines the controllable generation strengths of diffusion models with Transformer context modeling, supporting high-quality outputs for tasks like inpainting, outpainting, and visual scene reconstruction.",
  "FLUX.1-Kontext-pro.description": "FLUX.1 Kontext [pro]",
  "FLUX.1-dev.description": "FLUX.1-dev is an open-source multimodal language model (MLLM) from Black Forest Labs, optimized for image-text tasks and combining image/text understanding and generation. Built on advanced LLMs (such as Mistral-7B), it uses a carefully designed vision encoder and multi-stage instruction tuning to enable multimodal coordination and complex task reasoning.",
  "GLM-4.5-Air.description": "GLM-4.5-Air: Lightweight version for fast responses.",
  "GLM-4.5.description": "GLM-4.5: High-performance model for reasoning, coding, and agent tasks.",
  "GLM-4.6.description": "GLM-4.6: Previous generation model.",
  "GLM-4.7.description": "GLM-4.7 is Zhipu's latest flagship model, enhanced for Agentic Coding scenarios with improved coding capabilities, long-term task planning, and tool collaboration.",
  "GLM-5-Turbo.description": "GLM-5-Turbo is a foundation model deeply optimized for agentic scenarios. It has been specifically optimized for core requirements of agent tasks from the training phase, enhancing key capabilities such as tool invocation, command following, and long-chain execution. It is ideal for building high-performance agent assistants.",
  "GLM-5.1.description": "GLM-5.1 is Zhipu's latest flagship model, an enhanced iteration of GLM-5 with improved agentic engineering capabilities for complex systems engineering and long-horizon tasks.",
  "GLM-5.description": "GLM-5 is Zhipu’s next-generation flagship foundation model, purpose-built for Agentic Engineering. It delivers reliable productivity in complex systems engineering and long-horizon agentic tasks. In coding and agent capabilities, GLM-5 achieves state-of-the-art performance among open-source models. In real-world programming scenarios, its user experience approaches that of Claude Opus 4.5. It excels at complex systems engineering and long-horizon agent tasks, making it an ideal foundation model for general-purpose agent assistants.",
  "Gryphe/MythoMax-L2-13b.description": "MythoMax-L2 (13B) is an innovative model for diverse domains and complex tasks.",
  "HelloMeme.description": "HelloMeme is an AI tool that generates memes, GIFs, or short videos from the images or motions you provide. It requires no drawing or coding skills—just a reference image—to produce fun, attractive, and stylistically consistent content.",
  "HiDream-E1-Full.description": "HiDream-E1-Full is an open-source multimodal image editing model from HiDream.ai, based on an advanced Diffusion Transformer architecture and strong language understanding (built-in LLaMA 3.1-8B-Instruct). It supports natural-language-driven image generation, style transfer, local edits, and repainting, with excellent image-text understanding and execution.",
  "HiDream-I1-Full.description": "HiDream-I1 is a new open-source base image generation model released by HiDream. With 17B parameters (Flux has 12B), it can deliver industry-leading image quality in seconds.",
  "HunyuanDiT-v1.2-Diffusers-Distilled.description": "hunyuandit-v1.2-distilled is a lightweight text-to-image model optimized via distillation to generate high-quality images quickly, especially suited for low-resource environments and real-time generation.",
  "I2V-01-Director.description": "A director-level video generation model has been officially released, offering improved adherence to camera movement instructions and cinematic shot storytelling language.",
  "I2V-01-live.description": "Enhanced character performance: more stable, smoother, and more vivid.",
  "I2V-01.description": "The foundational image-to-video model of the 01 series.",
  "InstantCharacter.description": "InstantCharacter is a tuning-free personalized character generation model released by Tencent AI in 2025, aiming for high-fidelity, cross-scenario consistent character generation. It can model a character from a single reference image and flexibly transfer it across styles, actions, and backgrounds.",
  "InternVL2-8B.description": "InternVL2-8B is a powerful vision-language model supporting multimodal image-text processing, accurately recognizing image content and generating relevant descriptions or answers.",
  "InternVL2.5-26B.description": "InternVL2.5-26B is a powerful vision-language model supporting multimodal image-text processing, accurately recognizing image content and generating relevant descriptions or answers.",
  "KAT-Coder-Air-V1.description": "A lightweight version within the KAT-Coder series. Specifically designed for Agentic Coding, it comprehensively covers programming tasks and scenarios. Leveraging large-scale agent-based reinforcement learning, it enables emergent intelligent behaviors and significantly outperforms comparable models in coding performance.",
  "KAT-Coder-Exp-72B-1010.description": "KAT-Coder-Exp-72B is the RL innovation experimental version in the KAT-Coder series, achieving a remarkable performance of 74.6% on the SWE-Bench verified benchmark, setting a new record for open-source models. It focuses on Agentic Coding and currently only supports the SWE-Agent scaffold, but can also be used for simple conversations.",
  "KAT-Coder-Pro-V1.description": "Designed for Agentic Coding, it comprehensively covers programming tasks and scenarios, achieving intelligent behavior emergence through large-scale reinforcement learning, significantly outperforming similar models in code writing performance.",
  "KAT-Coder-Pro-V2.description": "The latest high-performance model from the Kuaishou Kwaipilot team, designed for complex enterprise projects and SaaS integration. It excels in code-related scenarios and is compatible with various types of agent frameworks (Claude Code, OpenCode, KiloCode), natively supports OpenClaw, and is optimized specifically for front-end page aesthetics.",
  "Kimi-K2.5.description": "Kimi K2.5 is the most capable Kimi model, delivering open-source SOTA in agent tasks, coding, and vision understanding. It supports multimodal inputs and both thinking and non-thinking modes.",
  "Kolors.description": "Kolors is a text-to-image model developed by the Kuaishou Kolors team. Trained with billions of parameters, it has notable advantages in visual quality, Chinese semantic understanding, and text rendering.",
  "Kwai-Kolors/Kolors.description": "Kolors is a large-scale latent-diffusion text-to-image model by the Kuaishou Kolors team. Trained on billions of text-image pairs, it excels in visual quality, complex semantic accuracy, and Chinese/English text rendering, with strong Chinese content understanding and generation.",
  "Ling-2.5-1T.description": "As the latest flagship real-time model in the Ling series, Ling-2.5-1T introduces comprehensive upgrades in model architecture, token efficiency, and preference alignment, aiming to elevate the quality of accessible AI to a new level.",
  "Ling-2.6-1T.description": "The latest flagship large language model, featuring support for a 1M-token context window and enabling an end-to-end workflow from logical reasoning to task execution.",
  "Ling-2.6-flash.description": "Ling-2.6-flash is the latest generation high cost-performance model in the Ling series. It adopts a Mixture-of-Experts (MoE) architecture, with a total parameter count of 100B and 6.1B activated parameters per token, achieving an optimal balance between inference performance and computational cost.",
  "Llama-3.2-11B-Vision-Instruct.description": "Strong image reasoning on high-resolution images, suited for visual understanding applications.",
  "Llama-3.2-90B-Vision-Instruct.description": "Advanced image reasoning for visual-understanding agent applications.",
  "LongCat-2.0-Preview.description": "The core features of LongCat-2.0-Preview are as follows: Designed for agent development scenarios, with native support for tool use, multi-step reasoning, and long-context tasks; Excels in code generation, automated workflows, and complex instruction execution; Deeply integrated with productivity tools such as Claude Code, OpenClaw, OpenCode, and Kilo Code.",
  "M2-her.description": "A text dialogue model designed for role-playing and multi-turn conversations, with character customization and emotional expression.",
  "Meta-Llama-3-3-70B-Instruct.description": "Llama 3.3 70B is a versatile Transformer model for chat and generation tasks.",
  "Meta-Llama-3.1-405B-Instruct.description": "Llama 3.1 instruction-tuned text model optimized for multilingual chat, performing strongly on common industry benchmarks among open and closed chat models.",
  "Meta-Llama-3.1-70B-Instruct.description": "Llama 3.1 instruction-tuned text model optimized for multilingual chat, performing strongly on common industry benchmarks among open and closed chat models.",
  "Meta-Llama-3.1-8B-Instruct.description": "Llama 3.1 instruction-tuned text model optimized for multilingual chat, performing strongly on common industry benchmarks among open and closed chat models.",
  "Meta-Llama-3.2-1B-Instruct.description": "Cutting-edge small language model with strong language understanding, excellent reasoning, and text generation.",
  "Meta-Llama-3.2-3B-Instruct.description": "Cutting-edge small language model with strong language understanding, excellent reasoning, and text generation.",
  "Meta-Llama-3.3-70B-Instruct.description": "Llama 3.3 is the most advanced multilingual open-source Llama model, delivering near-405B performance at very low cost. It is Transformer-based and improved with SFT and RLHF for usefulness and safety. The instruction-tuned version is optimized for multilingual chat and beats many open and closed chat models on industry benchmarks. Knowledge cutoff: Dec 2023.",
  "Meta-Llama-4-Maverick-17B-128E-Instruct-FP8.description": "Llama 4 Maverick is a large MoE model with efficient expert activation for strong reasoning performance.",
  "MiMo-V2-Pro.description": "MiMo-V2-Pro is specifically designed for high-intensity agent workflows in real-world scenarios. It features over 1 trillion total parameters (42B activated parameters), adopts an innovative hybrid attention architecture, and supports an ultra-long context length of up to 1 million tokens. Built on a powerful foundational model, we continuously scale computational resources across a broader range of agent scenarios, further expanding the action space of intelligence and achieving significant generalization—from coding to real-world task execution (“claw”).",
  "MiniMax-Hailuo-02.description": "The next-generation video generation model, MiniMax Hailuo 02, has been officially released, supporting 1080P resolution and 10-second video generation.",
  "MiniMax-Hailuo-2.3-Fast.description": "Brand-new video generation model with comprehensive upgrades in body motion, physical realism, and instruction following.",
  "MiniMax-Hailuo-2.3.description": "Brand-new video generation model with comprehensive upgrades in body motion, physical realism, and instruction following.",
  "MiniMax-M1.description": "A new in-house reasoning model with 80K chain-of-thought and 1M input, delivering performance comparable to top global models.",
  "MiniMax-M2-Stable.description": "Built for efficient coding and agent workflows, with higher concurrency for commercial use.",
  "MiniMax-M2.1-Lightning.description": "Powerful multilingual programming capabilities with faster and more efficient inference.",
  "MiniMax-M2.1-highspeed.description": "Powerful multilingual programming capabilities, comprehensively upgraded programming experience. Faster and more efficient.",
  "MiniMax-M2.1.description": "MiniMax-M2.1 is a flagship open-source large model from MiniMax, focusing on solving complex real-world tasks. Its core strengths are multi-language programming capabilities and the ability to solve complex tasks as an Agent.",
  "MiniMax-M2.5-highspeed.description": "MiniMax M2.5 Highspeed: Same performance as M2.5 with faster inference.",
  "MiniMax-M2.5.description": "MiniMax-M2.5 is a flagship open-source large model from MiniMax, focusing on solving complex real-world tasks. Its core strengths are multi-language programming capabilities and the ability to solve complex tasks as an Agent.",
  "MiniMax-M2.7-highspeed.description": "MiniMax M2.7 Highspeed: Same performance as M2.7 with significantly faster inference.",
  "MiniMax-M2.7.description": "First self-evolving model with top-tier coding and agentic performance (~60 tps).",
  "MiniMax-M2.description": "MiniMax M2: Previous generation model.",
  "MiniMax-M3.description": "Frontier multimodal coding and agentic model with a 1M context window, native image/video understanding, and controllable thinking.",
  "MiniMax-Text-01.description": "MiniMax-01 introduces large-scale linear attention beyond classic Transformers, with 456B parameters and 45.9B activated per pass. It achieves top-tier performance and supports up to 4M tokens of context (32× GPT-4o, 20× Claude-3.5-Sonnet).",
  "MiniMaxAI/MiniMax-M2.5.description": "MiniMax-M2.5 is the latest large language model developed by MiniMax, trained through large-scale reinforcement learning across hundreds of thousands of complex, real-world environments. Featuring an MoE architecture with 229 billion parameters, it achieves industry-leading performance in tasks such as programming, agent tool-calling, search, and office scenarios.",
  "Moonshot-Kimi-K2-Instruct.description": "1T total parameters with 32B active. Among non-thinking models, it is top-tier in frontier knowledge, math, and coding, and stronger at general agent tasks. Optimized for agent workloads, it can take actions, not just answer questions. Best for improvisational, general chat, and agent experiences as a reflex-level model without long thinking.",
  "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO.description": "Nous Hermes 2 - Mixtral 8x7B-DPO (46.7B) is a high-precision instruction model for complex computation.",
  "OmniConsistency.description": "OmniConsistency improves style consistency and generalization in image-to-image tasks by introducing large-scale Diffusion Transformers (DiTs) and paired stylized data, avoiding style degradation.",
  "PaddlePaddle/PaddleOCR-VL-1.5.description": "PaddleOCR-VL-1.5 is an upgraded version of the PaddleOCR-VL series, achieving 94.5% accuracy on the OmniDocBench v1.5 document parsing benchmark, surpassing leading general large models and specialized document parsing models. It innovatively supports irregular bounding box localization for document elements, handling scanned, tilted, and screen-captured images effectively.",
  "Phi-3-medium-128k-instruct.description": "The same Phi-3-medium model with a larger context window for RAG or few-shot prompts.",
  "Phi-3-medium-4k-instruct.description": "A 14B-parameter model with higher quality than Phi-3-mini, focused on high-quality, reasoning-intensive data.",
  "Phi-3-mini-128k-instruct.description": "The same Phi-3-mini model with a larger context window for RAG or few-shot prompts.",
  "Phi-3-mini-4k-instruct.description": "The smallest Phi-3 family member, optimized for quality and low latency.",
  "Phi-3-small-128k-instruct.description": "The same Phi-3-small model with a larger context window for RAG or few-shot prompts.",
  "Phi-3-small-8k-instruct.description": "A 7B-parameter model with higher quality than Phi-3-mini, focused on high-quality, reasoning-intensive data.",
  "Phi-3.5-mini-instruct.description": "An updated version of the Phi-3-mini model.",
  "Phi-3.5-vision-instrust.description": "An updated version of the Phi-3-vision model.",
  "Pro/MiniMaxAI/MiniMax-M2.5.description": "MiniMax-M2.5 is the latest large language model developed by MiniMax, trained through large-scale reinforcement learning across hundreds of thousands of complex, real-world environments. Featuring an MoE architecture with 229 billion parameters, it achieves industry-leading performance in tasks such as programming, agent tool-calling, search, and office scenarios.",
  "Pro/Qwen/Qwen2.5-7B-Instruct.description": "Qwen2.5-7B-Instruct is part of Alibaba Cloud’s latest LLM series. The 7B model brings notable gains in coding and math, supports 29+ languages, and improves instruction following, structured data understanding, and structured output (especially JSON).",
  "Pro/deepseek-ai/DeepSeek-R1.description": "DeepSeek-R1 is an RL-driven reasoning model that reduces repetition and improves readability. It uses cold-start data before RL to further boost reasoning, matches OpenAI-o1 on math, code, and reasoning tasks, and improves overall results through careful training.",
  "Pro/deepseek-ai/DeepSeek-V3.1-Terminus.description": "DeepSeek-V3.1-Terminus is an updated V3.1 model positioned as a hybrid agent LLM. It fixes user-reported issues and improves stability, language consistency, and reduces mixed Chinese/English and abnormal characters. It integrates Thinking and Non-thinking modes with chat templates for flexible switching. It also improves Code Agent and Search Agent performance for more reliable tool use and multi-step tasks.",
  "Pro/deepseek-ai/DeepSeek-V3.2.description": "DeepSeek-V3.2 is a model that combines high computational efficiency with excellent reasoning and Agent performance. Its approach is built on three key technological breakthroughs: DeepSeek Sparse Attention (DSA), an efficient attention mechanism that significantly reduces computational complexity while maintaining model performance, and is specifically optimized for long-context scenarios; a scalable reinforcement learning framework through which model performance can rival GPT-5, with its high-compute version matching Gemini-3.0-Pro in reasoning capabilities; and a large-scale Agent task synthesis pipeline aimed at integrating reasoning capabilities into tool use scenarios, thereby improving instruction following and generalization in complex interactive environments. The model achieved gold medal performance in the 2025 International Mathematical Olympiad (IMO) and International Olympiad in Informatics (IOI).",
  "Pro/deepseek-ai/DeepSeek-V3.description": "DeepSeek-V3 is a 671B-parameter MoE model using MLA and DeepSeekMoE with loss-free load balancing for efficient inference and training. Pretrained on 14.8T high-quality tokens and further tuned with SFT and RL, it outperforms other open models and approaches leading closed models.",
  "Pro/moonshotai/Kimi-K2.5.description": "Kimi K2.5 is an open-source native multimodal agent model, built on Kimi-K2-Base, trained on approximately 1.5 trillion mixed vision and text tokens. The model adopts an MoE architecture with 1T total parameters and 32B active parameters, supporting a 256K context window, seamlessly integrating vision and language understanding capabilities.",
  "Pro/moonshotai/Kimi-K2.6.description": "Kimi K2.6 is an open-source native multimodal agent model from Moonshot AI, achieving open-source state-of-the-art performance on multiple mainstream benchmarks including HLE (with tools), SWE-Bench Pro, and BrowseComp. The model adopts a MoE architecture with 1T total parameters and 32B active parameters, supports a 256K token context window, and integrates native multimodal capabilities.",
  "Pro/zai-org/GLM-4.7.description": "GLM-4.7 is Zhipu's new generation flagship model with 355B total parameters and 32B active parameters, fully upgraded in general dialogue, reasoning, and agent capabilities. GLM-4.7 enhances Interleaved Thinking and introduces Preserved Thinking and Turn-level Thinking.",
  "Pro/zai-org/GLM-5.1.description": "GLM-5.1 is a next-generation flagship model designed for agent engineering, using a Mixture of Experts (MoE) architecture with 754B parameters. It significantly enhances programming capabilities, achieving leading results on SWE-Bench Pro, and substantially outperforms its predecessor on benchmarks like NL2Repo and Terminal-Bench 2.0. Designed for long-duration agent tasks, it handles ambiguous questions with better judgment, decomposes complex tasks, executes experiments, analyzes results, and continuously optimizes through hundreds of iterations and thousands of tool calls.",
  "Pro/zai-org/glm-5.1.description": "GLM-5.1 is Zhipu’s next-generation flagship agent model for intelligent engineering. It uses a 754B Mixture-of-Experts architecture with native tool calling, prefix completion, FIM support, and a 200K context window for long-horizon workflows.",
  "Pro/zai-org/glm-5.description": "GLM-5 is Zhipu's next-generation large language model, focusing on complex system engineering and long-duration Agent tasks. The model parameters have been expanded to 744B (40B active) and integrate DeepSeek Sparse Attention.",
  "QwQ-32B-Preview.description": "Qwen QwQ is an experimental research model focused on improving reasoning.",
  "Qwen/QwQ-32B-Preview.description": "Qwen QwQ is an experimental research model focused on improved AI reasoning.",
  "Qwen/Qwen-Image-Edit-2509.description": "Qwen-Image-Edit-2509 is the latest editing version of Qwen-Image from the Qwen team. Built on the 20B Qwen-Image model, it extends strong text rendering into image editing for precise text edits. It uses a dual-control architecture, sending inputs to Qwen2.5-VL for semantic control and a VAE encoder for appearance control, enabling both semantic- and appearance-level editing. It supports local edits (add/remove/modify) and higher-level semantic edits like IP creation and style transfer while preserving semantics. It achieves SOTA results on multiple benchmarks.",
  "Qwen/Qwen-Image.description": "Qwen-Image is a 20B-parameter image generation foundation model from the Qwen team. It makes major gains in complex text rendering and precise image editing, especially for high-fidelity Chinese/English text. It supports multi-line and paragraph layouts while keeping typography coherent. Beyond text rendering, it supports a wide range of styles from photorealistic to anime, and advanced editing like style transfer, object add/remove, detail enhancement, text editing, and pose control, aiming to be a comprehensive visual creation foundation.",
  "Qwen/Qwen2-72B-Instruct.description": "Qwen 2 Instruct (72B) delivers precise instruction following for enterprise workloads.",
  "Qwen/Qwen2-7B-Instruct.description": "Qwen2-7B-Instruct is a 7B instruction-tuned model in the Qwen2 series using Transformer, SwiGLU, QKV bias, and grouped-query attention. It handles large inputs and performs strongly across understanding, generation, multilingual, coding, math, and reasoning benchmarks, outperforming most open models and surpassing Qwen1.5-7B-Chat in multiple evaluations.",
  "Qwen/Qwen2.5-14B-Instruct.description": "Qwen2.5-14B-Instruct is part of Alibaba Cloud’s latest LLM series. The 14B model brings notable gains in coding and math, supports 29+ languages, and improves instruction following, structured data understanding, and structured output (especially JSON).",
  "Qwen/Qwen2.5-32B-Instruct.description": "Qwen2.5-32B-Instruct is part of Alibaba Cloud’s latest LLM series. The 32B model brings notable gains in coding and math, supports 29+ languages, and improves instruction following, structured data understanding, and structured output (especially JSON).",
  "Qwen/Qwen2.5-72B-Instruct-128K.description": "Qwen2.5-72B-Instruct is part of Alibaba Cloud’s latest LLM series. The 72B model improves coding and math, supports up to 128K input and over 8K output, offers 29+ languages, and improves instruction following and structured output (especially JSON).",
  "Qwen/Qwen2.5-72B-Instruct-Turbo.description": "Qwen2.5 is a new LLM family optimized for instruction-style tasks.",
  "Qwen/Qwen2.5-72B-Instruct.description": "Qwen2.5-72B-Instruct is part of Alibaba Cloud’s latest LLM series. The 72B model brings notable gains in coding and math, supports 29+ languages, and improves instruction following, structured data understanding, and structured output (especially JSON).",
  "Qwen/Qwen2.5-7B-Instruct-Turbo.description": "Qwen2.5 is a new LLM family optimized for instruction-style tasks.",
  "Qwen/Qwen2.5-7B-Instruct.description": "Qwen2.5-7B-Instruct is part of Alibaba Cloud’s latest LLM series. The 7B model brings notable gains in coding and math, supports 29+ languages, and improves instruction following, structured data understanding, and structured output (especially JSON).",
  "Qwen/Qwen2.5-Coder-32B-Instruct.description": "Qwen2.5 Coder 32B Instruct is the latest Alibaba Cloud code-focused LLM. Built on Qwen2.5 and trained on 5.5T tokens, it significantly improves code generation, reasoning, and repair while retaining math and general strengths, providing a strong base for coding agents.",
  "Qwen/Qwen3-14B.description": "Qwen3 is a next-gen Tongyi Qwen model with major gains in reasoning, general ability, agent capability, and multilingual performance, and supports switching thinking modes.",
  "Qwen/Qwen3-235B-A22B.description": "Qwen3 235B A22B is the Qwen3 ultra-scale model delivering top-tier AI capability.",
  "Qwen/Qwen3-30B-A3B-Instruct-2507.description": "Qwen3-30B-A3B-Instruct-2507 is the updated non-thinking version of Qwen3-30B-A3B. It is an MoE model with 30.5B total and 3.3B active parameters. It significantly improves instruction following, logical reasoning, text understanding, math, science, coding, and tool use, expands multilingual long-tail knowledge, and better aligns with user preferences on subjective open tasks. It supports 256K context. This model is non-thinking only and will not output `נקוד` tags.",
  "Qwen/Qwen3-32B.description": "Qwen3 is a next-gen Tongyi Qwen model with major gains in reasoning, general ability, agent capability, and multilingual performance, and supports switching thinking modes.",
  "Qwen/Qwen3-8B.description": "Qwen3 is a next-gen Tongyi Qwen model with major gains in reasoning, general ability, agent capability, and multilingual performance, and supports switching thinking modes.",
  "Qwen/Qwen3-Coder-30B-A3B-Instruct.description": "Qwen3-Coder-30B-A3B-Instruct is a Qwen3 code model from the Qwen team. It is streamlined for high performance and efficiency while boosting code capabilities. It shows strong advantages on agentic coding, automated browser operations, and tool use among open models. It natively supports 256K context and can extend to 1M tokens for codebase-level understanding. It powers agentic coding on platforms like Qwen Code and CLINE with a dedicated function-calling format.",
  "Qwen/Qwen3-Omni-30B-A3B-Captioner.description": "Qwen3-Omni-30B-A3B-Captioner is a Qwen3-series VLM built for high-quality, detailed, accurate image captions. It uses a 30B-parameter MoE architecture to deeply understand images and produce fluent descriptions, excelling at detail capture, scene understanding, object recognition, and relational reasoning.",
  "Qwen/Qwen3-Omni-30B-A3B-Instruct.description": "Qwen3-Omni-30B-A3B-Instruct is a Qwen3-series MoE model with 30B total and 3B active parameters, delivering strong performance at lower inference cost. Trained on high-quality multi-source multilingual data, it supports full-modal inputs (text, images, audio, video) and cross-modal understanding and generation.",
  "Qwen/Qwen3-Omni-30B-A3B-Thinking.description": "Qwen3-Omni-30B-A3B-Thinking is the core \"Thinker\" component of Qwen3-Omni. It processes multimodal inputs (text, audio, images, video) and performs complex chain-of-thought reasoning, unifying inputs into a shared representation for deep cross-modal understanding. It is an MoE model with 30B total and 3B active parameters, balancing strong reasoning and compute efficiency.",
  "Qwen/Qwen3-VL-30B-A3B-Instruct.description": "Qwen3-VL-30B-A3B-Instruct is the instruction-tuned Qwen3-VL model with strong vision-language understanding and generation. It natively supports 256K context for multimodal chat and image-conditioned generation.",
  "Qwen/Qwen3-VL-30B-A3B-Thinking.description": "Qwen3-VL-30B-A3B-Thinking is the reasoning-enhanced version of Qwen3-VL, optimized for multimodal reasoning, image-to-code, and complex visual understanding. It supports 256K context with stronger chain-of-thought ability.",
  "Qwen/Qwen3-VL-32B-Instruct.description": "Qwen3-VL-32B-Instruct is a vision-language model from the Qwen team with leading SOTA results on multiple VL benchmarks. It supports megapixel-resolution images and offers strong visual understanding, multilingual OCR, fine-grained visual grounding, and visual dialogue. It handles complex multimodal tasks and supports tool calling and prefix completion.",
  "Qwen/Qwen3-VL-32B-Thinking.description": "Qwen3-VL-32B-Thinking is optimized for complex visual reasoning. It includes a built-in thinking mode that generates intermediate reasoning steps before answers, boosting multi-step logic, planning, and complex reasoning. It supports megapixel images, strong visual understanding, multilingual OCR, fine-grained grounding, visual dialogue, tool calling, and prefix completion.",
  "Qwen/Qwen3-VL-8B-Instruct.description": "Qwen3-VL-8B-Instruct is a Qwen3 vision-language model built on Qwen3-8B-Instruct and trained on large image-text data. It excels at general visual understanding, vision-centric dialogue, and multilingual text recognition in images, suitable for visual QA, captioning, multimodal instruction following, and tool use.",
  "Qwen/Qwen3-VL-8B-Thinking.description": "Qwen3-VL-8B-Thinking is the visual thinking version of Qwen3, optimized for complex multi-step reasoning. It generates a thinking chain before answers to improve accuracy, ideal for deep visual QA and detailed image analysis.",
  "Qwen/Qwen3.5-122B-A10B.description": "Qwen3.5-122B-A10B is a native multimodal large language model from the Qwen team with 122B total parameters and only 10B active parameters. It adopts an efficient hybrid architecture combining Gated Delta Networks and Sparse Mixture-of-Experts (MoE), natively supporting 256K context length with extensibility to approximately 1M tokens.",
  "Qwen/Qwen3.5-27B.description": "Qwen3.5-27B is a native multimodal large language model from the Qwen team with 27B parameters. It adopts an efficient hybrid architecture combining Gated Delta Networks and Gated Attention, natively supporting 256K context length with extensibility to approximately 1M tokens.",
  "Qwen/Qwen3.5-35B-A3B.description": "Qwen3.5-35B-A3B is a native multimodal large language model from the Qwen team with 35B total parameters and only 3B active parameters. It adopts an efficient hybrid architecture combining Gated Delta Networks and Sparse Mixture-of-Experts (MoE), natively supporting 256K context length with extensibility to approximately 1M tokens.",
  "Qwen/Qwen3.5-397B-A17B.description": "Qwen3.5-397B-A17B is the latest vision-language model in the Qwen3.5 series, using a Mixture-of-Experts (MoE) architecture with 397B total parameters and 17B active parameters. It natively supports 256K context length with extensibility to approximately 1M tokens, supports 201 languages, and provides unified vision-language understanding, tool calling, and reasoning capabilities.",
  "Qwen/Qwen3.5-4B.description": "Qwen3.5-4B is a native multimodal large language model from the Qwen team with 4B parameters, the most lightweight Dense model in the Qwen3.5 series. It adopts an efficient hybrid architecture combining Gated Delta Networks and Gated Attention, natively supporting 256K context length with extensibility to approximately 1M tokens.",
  "Qwen/Qwen3.5-9B.description": "Qwen3.5-9B is a native multimodal large language model from the Qwen team with 9B parameters. As a lightweight Dense model in the Qwen3.5 series, it adopts an efficient hybrid architecture combining Gated Delta Networks and Gated Attention, natively supporting 256K context length with extensibility to approximately 1M tokens.",
  "Qwen/Qwen3.6-27B.description": "Qwen3.6-27B is the first open-source medium-sized dense model in the Qwen3.6 series, with key enhancements for code generation, Agent workflows, and real-world development scenarios. Compared to Qwen3.5-27B, this model shows significant improvements in front-end development, repository-level reasoning, tool calling, and complex problem-solving, with newly added historical reasoning capability optimizations.",
  "Qwen/Qwen3.6-35B-A3B.description": "Qwen3.6-35B-A3B is a large language model from the Qwen team in the Qwen3.6 series, using a Mixture-of-Experts (MoE) architecture with 35B total parameters and 3B active parameters. It balances efficient inference with excellent performance and supports both thinking and non-thinking modes, allowing flexible switching between fast response and deep reasoning.",
  "Qwen2-72B-Instruct.description": "Qwen2 is the latest Qwen series, supporting a 128k context window. Compared with today’s best open models, Qwen2-72B significantly surpasses leading models in natural language understanding, knowledge, code, math, and multilingual capabilities.",
  "Qwen2-7B-Instruct.description": "Qwen2 is the latest Qwen series, surpassing the best open models of similar size and even larger models. Qwen2 7B shows significant advantages on multiple benchmarks, especially in code and Chinese understanding.",
  "Qwen2-VL-72B.description": "Qwen2-VL-72B is a powerful vision-language model supporting multimodal image-text processing, accurately recognizing image content and generating relevant descriptions or answers.",
  "Qwen2.5-14B-Instruct.description": "Qwen2.5-14B-Instruct is a 14B-parameter LLM with strong performance, optimized for Chinese and multilingual scenarios, supporting intelligent Q&A and content generation.",
  "Qwen2.5-32B-Instruct.description": "Qwen2.5-32B-Instruct is a 32B-parameter LLM with balanced performance, optimized for Chinese and multilingual scenarios, supporting intelligent Q&A and content generation.",
  "Qwen2.5-72B-Instruct.description": "LLM for Chinese and English, tuned for language, coding, math, and reasoning.",
  "Qwen2.5-7B-Instruct.description": "Qwen2.5-7B-Instruct is a 7B-parameter LLM that supports function calling and seamless external system integration, greatly improving flexibility and extensibility. It is optimized for Chinese and multilingual scenarios, supporting intelligent Q&A and content generation.",
  "Qwen2.5-Coder-14B-Instruct.description": "Qwen2.5-Coder-14B-Instruct is a large-scale pre-trained coding instruction model with strong code understanding and generation. It efficiently handles a wide range of programming tasks, ideal for smart coding, automated script generation, and programming Q&A.",
  "Qwen2.5-Coder-32B-Instruct.description": "Advanced LLM for code generation, reasoning, and bug fixing across major programming languages.",
  "Qwen3-235B-A22B-Instruct-2507-FP8.description": "Qwen3 235B A22B Instruct 2507 is optimized for advanced reasoning and instruction-following, using MoE to keep reasoning efficient at scale.",
  "Qwen3.5-Plus.description": "Qwen3.5 Plus supports text, image, and video input. Its performance on pure text tasks is comparable to Qwen3 Max, with better performance and lower cost. Its multimodal capabilities are significantly improved compared to the Qwen3 VL series.",
  "Ring-2.5-1T.description": "Compared to the previously released Ring-1T, Ring-2.5-1T achieves significant improvements across three key dimensions: generation efficiency, reasoning depth, and long-horizon task execution capability: Generation Efficiency**: By leveraging a high proportion of linear attention mechanisms, Ring-2.5-1T reduces memory access overhead by more than 10×. When processing sequences exceeding 32K tokens, it delivers over 3× higher generation throughput, making it particularly well-suited for deep reasoning and long-horizon task execution. Deep Reasoning**: Building on RLVR, a dense reward mechanism is introduced to provide feedback on the rigor of the reasoning process. This enables Ring-2.5-1T to achieve gold-medal-level performance in both IMO 2025 and CMO 2025 (self-evaluated). Long-Horizon Task Execution**: Through large-scale fully asynchronous agent-based reinforcement learning training, the model significantly enhances its ability to autonomously execute complex tasks over extended periods. This allows Ring-2.5-1T to seamlessly integrate with agent programming frameworks such as Claude Code and OpenClaw personal AI assistants.",
  "Ring-2.6-1T.description": "Ring-2.6-1T is a trillion-parameter-scale reasoning model that activates approximately 63B parameters per inference. Designed for Agent workflows, it focuses on agent capabilities, tool use, and long-horizon task execution, achieving leading performance on benchmarks such as PinchBench, ClawEval, TAU2-Bench, and GAIA2-search. The model is optimized across execution quality, latency, and cost, making it well suited for advanced coding agents, complex reasoning pipelines, and large-scale autonomous systems.",
  "S2V-01.description": "The foundational reference-to-video model of the 01 series.",
  "Skylark2-lite-8k.description": "Skylark 2nd-gen model. Skylark2-lite has fast responses for real-time, cost-sensitive scenarios with lower accuracy needs, with an 8K context window.",
  "Skylark2-pro-32k.description": "Skylark 2nd-gen model. Skylark2-pro offers higher accuracy for complex text generation such as professional copywriting, novel writing, and high-quality translation, with a 32K context window.",
  "Skylark2-pro-4k.description": "Skylark 2nd-gen model. Skylark2-pro offers higher accuracy for complex text generation such as professional copywriting, novel writing, and high-quality translation, with a 4K context window.",
  "Skylark2-pro-character-4k.description": "Skylark 2nd-gen model. Skylark2-pro-character excels at roleplay and chat, matching prompts with distinct persona styles and natural dialogue for chatbots, virtual assistants, and customer service, with fast responses.",
  "Skylark2-pro-turbo-8k.description": "Skylark 2nd-gen model. Skylark2-pro-turbo-8k offers faster inference at lower cost with an 8K context window.",
  "T2V-01-Director.description": "A director-level video generation model has been officially released, offering improved adherence to camera movement instructions and cinematic shot storytelling language.",
  "T2V-01.description": "The foundational text-to-video model of the 01 series.",
  "THUDM/GLM-4-32B-0414.description": "GLM-4-32B-0414 is a next-gen open GLM model with 32B parameters, comparable to OpenAI GPT and DeepSeek V3/R1 series in performance.",
  "THUDM/GLM-4-9B-0414.description": "GLM-4-9B-0414 is a 9B GLM model that inherits GLM-4-32B techniques while offering a lighter deployment. It performs well in code generation, web design, SVG generation, and search-based writing.",
  "THUDM/GLM-Z1-9B-0414.description": "GLM-Z1-9B-0414 is a small 9B-parameter GLM model that retains open-source strengths while delivering impressive capability. It performs strongly on math reasoning and general tasks, leading its size class among open models.",
  "Wan-AI/Wan2.2-I2V-A14B.description": "Wan2.2-I2V-A14B is one of the first open-source image-to-video (I2V) generation models released by Wan-AI, an AI initiative under Alibaba, to adopt a Mixture of Experts (MoE) architecture. The model focuses on generating smooth and natural dynamic video sequences by combining static images with text prompts. Its core innovation lies in the MoE architecture: a high-noise expert is responsible for handling the coarse structure in the early stages of video generation, while a low-noise expert refines fine-grained details in the later stages. This design improves overall model performance without increasing inference cost. Compared to previous versions, Wan2.2 is trained on a significantly larger dataset, leading to notable improvements in understanding complex motion, aesthetic styles, and semantic content. It produces more stable videos and reduces unrealistic camera movements.",
  "Wan-AI/Wan2.2-T2V-A14B.description": "Wan2.2-T2V-A14B is the first open-source video generation model released by Alibaba to adopt a Mixture of Experts (MoE) architecture. The model is designed for text-to-video (T2V) generation tasks and is capable of producing videos up to 5 seconds in length at resolutions of 480P or 720P. By introducing the MoE architecture, the model significantly increases its overall capacity while keeping inference costs nearly unchanged. It includes a high-noise expert that handles the global structure in the early stages of generation, and a low-noise expert that refines fine details in the later stages of the video. In addition, Wan2.2 incorporates carefully curated aesthetic data, with detailed annotations across dimensions such as lighting, composition, and color. This enables more precise and controllable generation of cinematic-quality visuals. Compared to previous versions, the model is trained on a larger dataset, resulting in significantly improved generalization in motion, semantics, and aesthetics, and better handling of complex dynamic effects.",
  "Yi-34B-Chat.description": "Yi-1.5-34B retains the series’ strong general language abilities while using incremental training on 500B high-quality tokens to significantly improve math logic and coding.",
  "abab5.5-chat.description": "Built for productivity scenarios with complex task handling and efficient text generation for professional use.",
  "abab5.5s-chat.description": "Designed for Chinese persona chat, delivering high-quality Chinese dialogue for various applications.",
  "abab6.5g-chat.description": "Designed for multilingual persona chat, supporting high-quality dialogue generation in English and other languages.",
  "abab6.5s-chat.description": "Suitable for a wide range of NLP tasks, including text generation and dialogue systems.",
  "abab6.5t-chat.description": "Optimized for Chinese persona chat, providing fluent dialogue that fits Chinese expression habits.",
  "accounts/fireworks/models/deepseek-r1.description": "DeepSeek-R1 is a state-of-the-art LLM optimized with reinforcement learning and cold-start data, delivering excellent reasoning, math, and coding performance.",
  "accounts/fireworks/models/deepseek-v3.description": "A powerful Mixture-of-Experts (MoE) language model from DeepSeek with 671B total parameters and 37B active parameters per token.",
  "accounts/fireworks/models/llama-v3-70b-instruct.description": "Meta developed and released the Meta Llama 3 LLM series, which includes pre-trained and instruction-tuned text generation models at 8B and 70B. The Llama 3 instruction-tuned models are optimized for conversational use and outperform many existing open chat models on common industry benchmarks.",
  "accounts/fireworks/models/llama-v3-8b-instruct-hf.description": "The Meta Llama 3 instruction-tuned models are optimized for conversational use and outperform many existing open chat models on common industry benchmarks. Llama 3 8B Instruct (HF version) is the original FP16 version of Llama 3 8B Instruct, with results expected to match the official Hugging Face implementation.",
  "accounts/fireworks/models/llama-v3-8b-instruct.description": "Meta developed and released the Meta Llama 3 LLM series, a collection of pre-trained and instruction-tuned text generation models at 8B and 70B. The Llama 3 instruction-tuned models are optimized for conversational use and outperform many existing open chat models on common industry benchmarks.",
  "accounts/fireworks/models/llama-v3p1-405b-instruct.description": "Meta Llama 3.1 is a multilingual LLM family with pre-trained and instruction-tuned generation models at 8B, 70B, and 405B sizes. The instruction-tuned text models are optimized for multilingual dialogue and outperform many existing open and closed chat models on common industry benchmarks. 405B is the most capable model in the Llama 3.1 family, using FP8 inference that closely matches the reference implementation.",
  "accounts/fireworks/models/llama-v3p1-70b-instruct.description": "Meta Llama 3.1 is a multilingual LLM family with pre-trained and instruction-tuned generation models at 8B, 70B, and 405B sizes. The instruction-tuned text models are optimized for multilingual dialogue and outperform many existing open and closed chat models on common industry benchmarks.",
  "accounts/fireworks/models/llama-v3p1-8b-instruct.description": "Meta Llama 3.1 is a multilingual LLM family with pre-trained and instruction-tuned generation models at 8B, 70B, and 405B sizes. The instruction-tuned text models are optimized for multilingual dialogue and outperform many existing open and closed chat models on common industry benchmarks.",
  "accounts/fireworks/models/llama-v3p2-11b-vision-instruct.description": "An instruction-tuned vision reasoning model from Meta with 11B parameters, optimized for visual recognition, image reasoning, captioning, and image-related Q&A. It understands visual data such as charts and graphs and bridges vision and language by generating textual descriptions of image details.",
  "accounts/fireworks/models/llama-v3p2-3b-instruct.description": "Llama 3.2 3B Instruct is a lightweight multilingual model from Meta, designed for efficient runtime with significant latency and cost advantages over larger models. Typical use cases include query/prompt rewriting and writing assistance.",
  "accounts/fireworks/models/llama-v3p2-90b-vision-instruct.description": "An instruction-tuned vision reasoning model from Meta with 90B parameters, optimized for visual recognition, image reasoning, captioning, and image-related Q&A. It understands visual data such as charts and graphs and bridges vision and language by generating textual descriptions of image details. Note: this model is currently provided experimentally as a serverless model. For production use, note that Fireworks may retire the deployment on short notice.",
  "accounts/fireworks/models/llama-v3p3-70b-instruct.description": "Llama 3.3 70B Instruct is the December update to Llama 3.1 70B. It improves tool use, multilingual text support, math, and coding over the July 2024 release. It reaches industry-leading performance in reasoning, math, and instruction following, offering performance comparable to 3.1 405B with significant speed and cost advantages.",
  "accounts/fireworks/models/mistral-small-24b-instruct-2501.description": "A 24B-parameter model with state-of-the-art capability comparable to larger models.",
  "accounts/fireworks/models/mixtral-8x22b-instruct.description": "Mixtral MoE 8x22B Instruct v0.1 is the instruction-tuned version of Mixtral MoE 8x22B v0.1, with the chat completion API enabled.",
  "accounts/fireworks/models/mixtral-8x7b-instruct.description": "Mixtral MoE 8x7B Instruct is the instruction-tuned version of Mixtral MoE 8x7B, with the chat completion API enabled.",
  "accounts/fireworks/models/mythomax-l2-13b.description": "An improved variant of MythoMix, possibly its more refined form, merging MythoLogic-L2 and Huginn with a highly experimental tensor-type merge technique. Its unique nature makes it excellent for storytelling and roleplay.",
  "accounts/fireworks/models/phi-3-vision-128k-instruct.description": "Phi-3-Vision-128K-Instruct is a lightweight, state-of-the-art open multimodal model built from synthetic data and curated public web datasets, focusing on high-quality, reasoning-intensive text and vision data. It belongs to the Phi-3 family, with a multimodal version supporting a 128K context length (in tokens). The model undergoes rigorous enhancement, including supervised fine-tuning and direct preference optimization, to ensure accurate instruction following and strong safety measures.",
  "accounts/fireworks/models/qwen-qwq-32b-preview.description": "The Qwen QwQ model focuses on advancing AI reasoning, demonstrating that open models can rival closed frontier models in reasoning. QwQ-32B-Preview is an experimental release that matches o1 and surpasses GPT-4o and Claude 3.5 Sonnet on reasoning and analysis across GPQA, AIME, MATH-500, and LiveCodeBench. Note: this model is currently provided experimentally as a serverless model. For production use, note that Fireworks may retire the deployment on short notice.",
  "accounts/fireworks/models/qwen2-vl-72b-instruct.description": "The 72B Qwen-VL model is Alibaba’s latest iteration, reflecting nearly a year of innovation.",
  "accounts/fireworks/models/qwen2p5-72b-instruct.description": "Qwen2.5 is a decoder-only LLM series developed by the Qwen team and Alibaba Cloud, offering 0.5B, 1.5B, 3B, 7B, 14B, 32B, and 72B sizes, with both base and instruction-tuned variants.",
  "accounts/fireworks/models/qwen2p5-coder-32b-instruct.description": "Qwen2.5-Coder is the latest Qwen LLM designed for code (formerly CodeQwen). Note: this model is currently provided experimentally as a serverless model. For production use, note that Fireworks may retire the deployment on short notice.",
  "accounts/yi-01-ai/models/yi-large.description": "Yi-Large is a top-tier LLM that ranks just below GPT-4, Gemini 1.5 Pro, and Claude 3 Opus on the LMSYS leaderboard. It excels in multilingual capability, especially Spanish, Chinese, Japanese, German, and French. Yi-Large is also developer-friendly, using the same API schema as OpenAI for easy integration.",
  "ai21-jamba-1.5-large.description": "A 398B-parameter (94B active) multilingual model with a 256K context window, function calling, structured output, and grounded generation.",
  "ai21-jamba-1.5-mini.description": "A 52B-parameter (12B active) multilingual model with a 256K context window, function calling, structured output, and grounded generation.",
  "ai21-labs/AI21-Jamba-1.5-Large.description": "A 398B-parameter (94B active) multilingual model with a 256K context window, function calling, structured output, and grounded generation.",
  "ai21-labs/AI21-Jamba-1.5-Mini.description": "A 52B-parameter (12B active) multilingual model with a 256K context window, function calling, structured output, and grounded generation.",
  "alibaba/qwen-3-14b.description": "Qwen3 is the latest generation in the Qwen series, offering a comprehensive set of dense and MoE models. Built on extensive training, it brings breakthroughs in reasoning, instruction following, agent capabilities, and multilingual support.",
  "alibaba/qwen-3-235b.description": "Qwen3 is the latest generation in the Qwen series, offering a comprehensive set of dense and MoE models. Built on extensive training, it brings breakthroughs in reasoning, instruction following, agent capabilities, and multilingual support.",
  "alibaba/qwen-3-30b.description": "Qwen3 is the latest generation in the Qwen series, offering a comprehensive set of dense and MoE models. Built on extensive training, it brings breakthroughs in reasoning, instruction following, agent capabilities, and multilingual support.",
  "alibaba/qwen-3-32b.description": "Qwen3 is the latest generation in the Qwen series, offering a comprehensive set of dense and MoE models. Built on extensive training, it brings breakthroughs in reasoning, instruction following, agent capabilities, and multilingual support.",
  "alibaba/qwen3-coder.description": "Qwen3-Coder-480B-A35B-Instruct is Qwen’s most agentic code model, performing strongly on agentic coding, agentic browser use, and other core coding tasks, matching Claude Sonnet-level results.",
  "amazon/nova-lite.description": "A very low-cost multimodal model with extremely fast processing of image, video, and text inputs.",
  "amazon/nova-micro.description": "A text-only model offering ultra-low latency at very low cost.",
  "amazon/nova-pro.description": "A highly capable multimodal model with the best balance of accuracy, speed, and cost for a wide range of tasks.",
  "amazon/titan-embed-text-v2.description": "Amazon Titan Text Embeddings V2 is a lightweight, efficient multilingual embedding model supporting 1024, 512, and 256 dimensions.",
  "anthropic.claude-3-5-sonnet-20240620-v1:0.description": "Claude 3.5 Sonnet raises the industry standard, outperforming competitors and Claude 3 Opus across broad evaluations while keeping mid-tier speed and cost.",
  "anthropic.claude-3-5-sonnet-20241022-v2:0.description": "Claude 3.5 Sonnet raises the industry standard, outperforming competitors and Claude 3 Opus across broad evaluations while keeping mid-tier speed and cost.",
  "anthropic.claude-3-haiku-20240307-v1:0.description": "Claude 3 Haiku is Anthropic’s fastest, most compact model, delivering near-instant responses for simple queries. It enables seamless, human-like AI experiences and supports image input with a 200K context window.",
  "anthropic.claude-3-opus-20240229-v1:0.description": "Claude 3 Opus is Anthropic’s most powerful AI model with state-of-the-art performance on highly complex tasks. It handles open-ended prompts and novel scenarios with exceptional fluency and human-like understanding, and supports image input with a 200K context window.",
  "anthropic.claude-3-sonnet-20240229-v1:0.description": "Claude 3 Sonnet balances intelligence and speed for enterprise workloads, offering strong value at lower cost. It is designed as a reliable workhorse for scaled AI deployments and supports image input with a 200K context window.",
  "anthropic.claude-instant-v1.description": "A fast, economical, yet capable model for everyday chat, text analysis, summarization, and document Q&A.",
  "anthropic.claude-v2.description": "A highly capable model across tasks from complex dialogue and creative generation to detailed instruction following.",
  "anthropic.claude-v2:1.description": "An updated Claude 2 with double the context window and improved reliability, hallucination rate, and evidence-based accuracy for long documents and RAG.",
  "anthropic/claude-3-haiku.description": "Claude 3 Haiku is Anthropic’s fastest model, designed for enterprise workloads with longer prompts. It can quickly analyze large documents like quarterly reports, contracts, or legal cases at half the cost of peers.",
  "anthropic/claude-3-opus.description": "Claude 3 Opus is Anthropic’s most intelligent model with market-leading performance on highly complex tasks, handling open-ended prompts and novel scenarios with exceptional fluency and human-like understanding.",
  "anthropic/claude-3.5-haiku.description": "Claude 3.5 Haiku features enhanced speed, coding accuracy, and tool use, suitable for scenarios with demanding requirements for speed and tool interaction.",
  "anthropic/claude-3.5-sonnet.description": "Claude 3.5 Sonnet is the fast, efficient model in the Sonnet family, offering better coding and reasoning performance, with some versions gradually replaced by Sonnet 3.7 and later.",
  "anthropic/claude-3.7-sonnet.description": "Claude 3.7 Sonnet is an upgraded Sonnet model with stronger reasoning and coding, suitable for enterprise-grade complex tasks.",
  "anthropic/claude-haiku-4.5.description": "Claude Haiku 4.5 is Anthropic’s high-performance fast model, delivering very low latency while maintaining high accuracy.",
  "anthropic/claude-opus-4.1.description": "Opus 4.1 is Anthropic’s high-end model optimized for programming, complex reasoning, and long-running tasks.",
  "anthropic/claude-opus-4.5.description": "Claude Opus 4.5 is Anthropic’s flagship model, combining top-tier intelligence with scalable performance for complex, high-quality reasoning tasks.",
  "anthropic/claude-opus-4.description": "Opus 4 is Anthropic’s flagship model designed for complex tasks and enterprise applications.",
  "anthropic/claude-sonnet-4.5.description": "Claude Sonnet 4.5 is Anthropic’s latest hybrid reasoning model optimized for complex reasoning and coding.",
  "anthropic/claude-sonnet-4.description": "Claude Sonnet 4 is Anthropic’s hybrid reasoning model with mixed thinking and non-thinking capability.",
  "aya.description": "Aya 23 is Cohere’s multilingual model supporting 23 languages for diverse use cases.",
  "aya:35b.description": "Aya 23 is Cohere’s multilingual model supporting 23 languages for diverse use cases.",
  "azure-DeepSeek-R1-0528.description": "Deployed by Microsoft; DeepSeek R1 has been upgraded to DeepSeek-R1-0528. The update increases compute and post-training algorithm optimizations, significantly improving reasoning depth and inference. It performs strongly on math, coding, and general logic benchmarks, approaching leading models like O3 and Gemini 2.5 Pro.",
  "baichuan-m2-32b.description": "Baichuan M2 32B is a MoE model from Baichuan Intelligence with strong reasoning.",
  "baichuan/baichuan2-13b-chat.description": "Baichuan-13B is an open-source, commercially usable 13B-parameter LLM from Baichuan, achieving best-in-class results for its size on authoritative Chinese and English benchmarks.",
  "baidu/ernie-5.0-thinking-preview.description": "ERNIE 5.0 Thinking Preview is Baidu’s next-generation native multimodal ERNIE model, strong in multimodal understanding, instruction following, creation, factual Q&A, and tool calling.",
  "big-pickle.description": "Big Pickle by OpenCode — free open-weights model with strong coding capabilities.",
  "black-forest-labs/flux-1.1-pro.description": "FLUX 1.1 Pro is a faster, improved FLUX Pro with excellent image quality and prompt adherence.",
  "black-forest-labs/flux-dev.description": "FLUX Dev is the development version of FLUX for non-commercial use.",
  "black-forest-labs/flux-pro.description": "FLUX Pro is the professional FLUX model for high-quality image output.",
  "black-forest-labs/flux-schnell.description": "FLUX Schnell is a fast image generation model optimized for speed.",
  "c4ai-aya-expanse-32b.description": "Aya Expanse is a high-performance 32B multilingual model that uses instruction tuning, data arbitrage, preference training, and model merging to rival monolingual models. It supports 23 languages.",
  "c4ai-aya-expanse-8b.description": "Aya Expanse is a high-performance 8B multilingual model that uses instruction tuning, data arbitrage, preference training, and model merging to rival monolingual models. It supports 23 languages.",
  "c4ai-aya-vision-32b.description": "Aya Vision is a state-of-the-art multimodal model that performs strongly on key language, text, and vision benchmarks. It supports 23 languages. This 32B version focuses on top-tier multilingual performance.",
  "c4ai-aya-vision-8b.description": "Aya Vision is a state-of-the-art multimodal model that performs strongly on key language, text, and vision benchmarks. This 8B version focuses on low latency and strong performance.",
  "charglm-3.description": "CharGLM-3 is built for roleplay and emotional companionship, supporting ultra-long multi-turn memory and personalized dialogue.",
  "charglm-4.description": "CharGLM-4 is built for roleplay and emotional companionship, supporting ultra-long multi-turn memory and personalized dialogue.",
  "chat-latest.description": "Latest Instant model used in ChatGPT.",
  "chatgpt-4o-latest.description": "ChatGPT-4o is a dynamic model updated in real time. It combines strong language understanding and generation for large-scale use cases like customer support, education, and technical assistance.",
  "claude-2.0.description": "Claude 2 delivers key enterprise improvements, including a leading 200K-token context, reduced hallucinations, system prompts, and a new test feature: tool calling.",
  "claude-2.1.description": "Claude 2 delivers key enterprise improvements, including a leading 200K-token context, reduced hallucinations, system prompts, and a new test feature: tool calling.",
  "claude-3-5-haiku-20241022.description": "Claude 3.5 Haiku is Anthropic’s fastest next-gen model. Compared to Claude 3 Haiku, it improves across skills and surpasses the prior largest model Claude 3 Opus on many intelligence benchmarks.",
  "claude-3-5-haiku-latest.description": "Claude 3.5 Haiku delivers fast responses for lightweight tasks.",
  "claude-3-5-haiku.description": "Claude Haiku 3.5 by Anthropic — fast and cost-efficient model with vision support.",
  "claude-3-7-sonnet-20250219.description": "Claude 3.7 Sonnet is Anthropic’s most intelligent model and the first hybrid reasoning model on the market. It can produce near-instant responses or extended step-by-step reasoning that users can see. Sonnet is especially strong at coding, data science, vision, and agent tasks.",
  "claude-3-7-sonnet-latest.description": "Claude 3.7 Sonnet is Anthropic’s latest and most capable model for highly complex tasks, excelling in performance, intelligence, fluency, and understanding.",
  "claude-3-haiku-20240307.description": "Claude 3 Haiku is Anthropic’s fastest and most compact model, designed for near-instant responses with fast, accurate performance.",
  "claude-3-opus-20240229.description": "Claude 3 Opus is Anthropic’s most powerful model for highly complex tasks, excelling in performance, intelligence, fluency, and comprehension.",
  "claude-3-sonnet-20240229.description": "Claude 3 Sonnet balances intelligence and speed for enterprise workloads, delivering high utility at lower cost and reliable large-scale deployment.",
  "claude-fable-5.description": "Claude Fable 5 is Anthropic's most capable model — a new tier above Opus for the most demanding reasoning and long-horizon agentic work.",
  "claude-haiku-4-5-20251001.description": "Claude Haiku 4.5 is Anthropic’s fastest and smartest Haiku model, with lightning speed and extended reasoning.",
  "claude-haiku-4-5.description": "Claude Haiku 4.5 by Anthropic — next-gen Haiku with enhanced reasoning and vision.",
  "claude-haiku-4.5.description": "Claude Haiku 4.5 is Anthropic’s fastest and smartest Haiku model, with lightning speed and extended reasoning.",
  "claude-opus-4-1-20250805-thinking.description": "Claude Opus 4.1 Thinking is an advanced variant that can reveal its reasoning process.",
  "claude-opus-4-1-20250805.description": "Claude Opus 4.1 is Anthropic’s latest and most capable model for highly complex tasks, excelling in performance, intelligence, fluency, and understanding.",
  "claude-opus-4-1.description": "Claude Opus 4.1 by Anthropic — premium reasoning model with deep analysis capabilities.",
  "claude-opus-4-20250514.description": "Claude Opus 4 is Anthropic’s most powerful model for highly complex tasks, excelling in performance, intelligence, fluency, and comprehension.",
  "claude-opus-4-5-20251101.description": "Claude Opus 4.5 is Anthropic’s flagship model, combining outstanding intelligence with scalable performance, ideal for complex tasks requiring the highest-quality responses and reasoning.",
  "claude-opus-4-5.description": "Claude Opus 4.5 by Anthropic — flagship model with top-tier reasoning and coding.",
  "claude-opus-4-6.description": "Claude Opus 4.6 by Anthropic — 1M context window flagship with advanced reasoning.",
  "claude-opus-4-7.description": "Claude Opus 4.7 by Anthropic — latest Opus with state-of-the-art reasoning and coding.",
  "claude-opus-4-8.description": "Claude Opus 4.8 is Anthropic's most capable model, building on Opus 4.7 with improvements across reasoning, agentic coding, and tool use.",
  "claude-opus-4.5.description": "Claude Opus 4.5 is Anthropic’s flagship model, combining top-tier intelligence with scalable performance for complex, high-quality reasoning tasks.",
  "claude-opus-4.6-fast.description": "Claude Opus 4.6 is Anthropic’s most intelligent model for building agents and coding.",
  "claude-opus-4.6.description": "Claude Opus 4.6 is Anthropic’s most intelligent model for building agents and coding.",
  "claude-sonnet-4-20250514-thinking.description": "Claude Sonnet 4 Thinking can produce near-instant responses or extended step-by-step thinking with visible process.",
  "claude-sonnet-4-20250514.description": "Claude Sonnet 4 can produce near-instant responses or extended step-by-step thinking with visible process.",
  "claude-sonnet-4-5-20250929.description": "Claude Sonnet 4.5 is Anthropic’s most intelligent model to date.",
  "claude-sonnet-4-5.description": "Claude Sonnet 4.5 by Anthropic — improved Sonnet with enhanced coding performance.",
  "claude-sonnet-4-6.description": "Claude Sonnet 4.6 by Anthropic — latest Sonnet with superior coding and tool use.",
  "claude-sonnet-4.5.description": "Claude Sonnet 4.5 is Anthropic’s most intelligent model to date.",
  "claude-sonnet-4.6.description": "Claude Sonnet 4.6 is Anthropic’s best combination of speed and intelligence.",
  "claude-sonnet-4.description": "Claude Sonnet 4 by Anthropic — balanced model with strong coding and reasoning abilities.",
  "codegeex-4.description": "CodeGeeX-4 is a powerful AI coding assistant that supports multilingual Q&A and code completion to boost developer productivity.",
  "codegeex4-all-9b.description": "CodeGeeX4-ALL-9B is a multilingual code generation model supporting code completion and generation, code interpreter, web search, function calling, and repo-level code Q&A, covering a wide range of software development scenarios. It is a top-tier code model under 10B parameters.",
  "codegemma.description": "CodeGemma is a lightweight model for varied programming tasks, enabling fast iteration and integration.",
  "codegemma:2b.description": "CodeGemma is a lightweight model for varied programming tasks, enabling fast iteration and integration.",
  "codellama.description": "Code Llama is an LLM focused on code generation and discussion, with broad language support for developer workflows.",
  "codellama/CodeLlama-34b-Instruct-hf.description": "Code Llama is an LLM focused on code generation and discussion, with broad language support for developer workflows.",
  "codellama:13b.description": "Code Llama is an LLM focused on code generation and discussion, with broad language support for developer workflows.",
  "codellama:34b.description": "Code Llama is an LLM focused on code generation and discussion, with broad language support for developer workflows.",
  "codellama:70b.description": "Code Llama is an LLM focused on code generation and discussion, with broad language support for developer workflows.",
  "codeqwen.description": "CodeQwen1.5 is a large language model trained on extensive code data, built for complex programming tasks.",
  "codestral-latest.description": "Codestral is our most advanced coding model; v2 (Jan 2025) targets low-latency, high-frequency tasks like FIM, code correction, and test generation.",
  "codestral.description": "Codestral is Mistral AI’s first code model, delivering strong code generation support.",
  "cogito-2.1:671b.description": "Cogito v2.1 671B is a US open-source LLM free for commercial use, with performance rivaling top models, higher token reasoning efficiency, a 128k long context, and strong overall capability.",
  "cogvideox-2.description": "CogVideoX-2 is Zhipu’s new-generation video generation foundation model, with image-to-video capabilities improved by 38%. It delivers significant enhancements in large-scale motion handling, visual stability, instruction adherence, artistic style, and overall visual aesthetics.",
  "cogvideox-3.description": "CogVideoX-3 adds a start-and-end frame generation feature, significantly improving visual stability and clarity. It enables smooth and natural large-scale subject motion, offers better instruction adherence and more realistic physical simulation, and further enhances performance in high-definition realistic and 3D-style scenes.",
  "cogvideox-flash.description": "CogVideoX-Flash is a free video generation model released by Zhipu, capable of generating videos that follow user instructions while achieving higher aesthetic quality scores.",
  "cogview-3-flash.description": "CogView-3-Flash is a free image generation model launched by Zhipu. It generates images that align with user instructions while achieving higher aesthetic quality scores. CogView-3-Flash is primarily used in fields such as artistic creation, design reference, game development, and virtual reality, helping users rapidly convert text descriptions into images.",
  "cogview-4.description": "CogView-4 is Zhipu’s first open-source text-to-image model that can generate Chinese characters. It improves semantic understanding, image quality, and Chinese/English text rendering, supports arbitrary-length bilingual prompts, and can generate images at any resolution within specified ranges.",
  "cohere-command-r-plus.description": "Command R+ is an advanced RAG-optimized model built for enterprise workloads.",
  "cohere-command-r.description": "Command R is a scalable generative model designed for RAG and tool use, enabling production-grade AI.",
  "cohere/Cohere-command-r-plus.description": "Command R+ is an advanced RAG-optimized model built for enterprise workloads.",
  "cohere/Cohere-command-r.description": "Command R is a scalable generative model designed for RAG and tool use, enabling production-grade AI.",
  "cohere/command-a.description": "Command A is Cohere’s strongest model yet, excelling at tool use, agents, RAG, and multilingual use cases. It has a 256K context length, runs on just two GPUs, and delivers 150% higher throughput than Command R+ 08-2024.",
  "cohere/embed-v4.0.description": "A model that classifies or converts text, images, or mixed content into embeddings.",
  "comfyui/flux-dev.description": "FLUX.1 Dev is a high-quality text-to-image model (10–50 steps), ideal for premium creative and artistic output.",
  "comfyui/flux-kontext-dev.description": "FLUX.1 Kontext-dev is an image editing model that supports text-guided edits, including local edits and style transfer.",
  "comfyui/flux-krea-dev.description": "FLUX.1 Krea-dev is a safety-enhanced text-to-image model co-developed with Krea, with built-in safety filters.",
  "comfyui/flux-schnell.description": "FLUX.1 Schnell is an ultra-fast text-to-image model that generates high-quality images in 1-4 steps, ideal for real-time use and rapid prototyping.",
  "comfyui/stable-diffusion-15.description": "Stable Diffusion 1.5 is a classic 512x512 text-to-image model, ideal for rapid prototyping and creative experiments.",
  "comfyui/stable-diffusion-35-inclclip.description": "Stable Diffusion 3.5 with built-in CLIP/T5 encoders needs no external encoder files, suitable for models like sd3.5_medium_incl_clips with lower resource usage.",
  "comfyui/stable-diffusion-35.description": "Stable Diffusion 3.5 is a next-generation text-to-image model with Large and Medium variants. It requires external CLIP encoder files and delivers excellent image quality and prompt adherence.",
  "comfyui/stable-diffusion-custom-refiner.description": "Custom SDXL image-to-image model. Use custom_sd_lobe.safetensors as the model filename; if you have a VAE, use custom_sd_vae_lobe.safetensors. Place model files in the required Comfy folders.",
  "comfyui/stable-diffusion-custom.description": "Custom SD text-to-image model. Use custom_sd_lobe.safetensors as the model filename; if you have a VAE, use custom_sd_vae_lobe.safetensors. Place model files in the required Comfy folders.",
  "comfyui/stable-diffusion-refiner.description": "SDXL image-to-image model performs high-quality transformations from input images, supporting style transfer, restoration, and creative variations.",
  "comfyui/stable-diffusion-xl.description": "SDXL is a text-to-image model supporting 1024x1024 high-resolution generation with better image quality and detail.",
  "command-a-03-2025.description": "Command A is our most capable model to date, excelling at tool use, agents, RAG, and multilingual scenarios. It has a 256K context window, runs on just two GPUs, and delivers 150% higher throughput than Command R+ 08-2024.",
  "command-light-nightly.description": "To shorten the gap between major releases, we offer nightly Command builds. For the command-light series this is called command-light-nightly. It is the newest, most experimental (and potentially unstable) version, updated regularly without notice, so it is not recommended for production.",
  "command-light.description": "A smaller, faster Command variant that is nearly as capable but faster.",
  "command-nightly.description": "To shorten the gap between major releases, we offer nightly Command builds. For the Command series this is called command-nightly. It is the newest, most experimental (and potentially unstable) version, updated regularly without notice, so it is not recommended for production.",
  "command-r-03-2024.description": "command-r is an instruction-following chat model that performs language tasks with higher quality, improved reliability, and longer context than previous models. It supports complex workflows such as code generation, RAG, tool use, and agents.",
  "command-r-08-2024.description": "command-r-08-2024 is an updated Command R model released in August 2024.",
  "command-r-plus-04-2024.description": "command-r-plus is an alias of command-r-plus-04-2024, so using command-r-plus in the API points to that model.",
  "command-r-plus-08-2024.description": "Command R+ is an instruction-following chat model with higher quality, greater reliability, and a longer context window than previous models. It is best for complex RAG workflows and multi-step tool use.",
  "command-r-plus.description": "Command R+ is a high-performance LLM designed for real enterprise scenarios and complex apps.",
  "command-r.description": "Command R is an LLM optimized for chat and long-context tasks, ideal for dynamic interaction and knowledge management.",
  "command-r7b-12-2024.description": "command-r7b-12-2024 is a small, efficient update released in December 2024. It excels at RAG, tool use, and agent tasks that require complex, multi-step reasoning.",
  "command.description": "An instruction-following chat model that delivers higher quality and reliability on language tasks, with a longer context window than our base generative models.",
  "computer-use-preview.description": "computer-use-preview is a specialized model for the \"computer use tool,\" trained to understand and execute computer-related tasks.",
  "dall-e-3.description": "DALL·E 3",
  "databricks/dbrx-instruct.description": "DBRX Instruct offers highly reliable instruction handling across industries.",
  "deepseek-ai/DeepSeek-OCR.description": "DeepSeek-OCR is a vision-language model from DeepSeek AI focused on OCR and \"context optical compression.\" It explores compressing context from images, efficiently processes documents, and converts them to structured text (e.g., Markdown). It accurately recognizes text in images, suited for document digitization, text extraction, and structured processing.",
  "deepseek-ai/DeepSeek-R1-0528-Qwen3-8B.description": "DeepSeek-R1-0528-Qwen3-8B distills chain-of-thought from DeepSeek-R1-0528 into Qwen3 8B Base. It reaches SOTA among open models, beating Qwen3 8B by 10% on AIME 2024 and matching Qwen3-235B-thinking performance. It excels on math reasoning, programming, and general logic benchmarks. It shares the Qwen3-8B architecture but uses the DeepSeek-R1-0528 tokenizer.",
  "deepseek-ai/DeepSeek-R1-0528.description": "DeepSeek R1 leverages additional compute and post-training algorithmic optimizations to deepen reasoning. It performs strongly across benchmarks in math, programming, and general logic, approaching leaders like o3 and Gemini 2.5 Pro.",
  "deepseek-ai/DeepSeek-R1-Distill-Llama-70B.description": "DeepSeek-R1 distilled models use RL and cold-start data to improve reasoning and set new open-model multi-task benchmarks.",
  "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B.description": "DeepSeek-R1 distilled models use RL and cold-start data to improve reasoning and set new open-model multi-task benchmarks.",
  "deepseek-ai/DeepSeek-R1-Distill-Qwen-14B.description": "DeepSeek-R1 distilled models use RL and cold-start data to improve reasoning and set new open-model multi-task benchmarks.",
  "deepseek-ai/DeepSeek-R1.description": "DeepSeek-R1 improves reasoning with RL and cold-start data, setting new open-model multi-task benchmarks and surpassing OpenAI-o1-mini.",
  "deepseek-ai/DeepSeek-V3.1-Terminus.description": "DeepSeek-V3.1-Terminus is an updated V3.1 model positioned as a hybrid agent LLM. It fixes user-reported issues and improves stability, language consistency, and reduces mixed Chinese/English and abnormal characters. It integrates Thinking and Non-thinking modes with chat templates for flexible switching. It also improves Code Agent and Search Agent performance for more reliable tool use and multi-step tasks.",
  "deepseek-ai/DeepSeek-V3.1.description": "DeepSeek V3.1 uses a hybrid reasoning architecture and supports both thinking and non-thinking modes.",
  "deepseek-ai/DeepSeek-V3.2-Exp.description": "DeepSeek V3.2 Exp uses a hybrid reasoning architecture and supports both thinking and non-thinking modes.",
  "deepseek-ai/DeepSeek-V3.2.description": "DeepSeek-V3.2 is a model that combines high computational efficiency with excellent reasoning and Agent performance. Its approach is based on three major technological breakthroughs: DeepSeek Sparse Attention (DSA), an efficient attention mechanism that significantly reduces computational complexity while maintaining model performance, and is specifically optimized for long-context scenarios; a scalable reinforcement learning framework, through which the model's performance can rival GPT-5, and its high-compute version can rival Gemini-3.0-Pro in reasoning capabilities; and a large-scale Agent task synthesis pipeline, designed to integrate reasoning capabilities into tool-using scenarios, thereby improving instruction-following and generalization abilities in complex interactive environments. The model achieved gold medal results in the 2025 International Mathematical Olympiad (IMO) and International Informatics Olympiad (IOI).",
  "deepseek-ai/DeepSeek-V3.description": "DeepSeek-V3 is a 671B-parameter MoE model using MLA and DeepSeekMoE with loss-free load balancing for efficient training and inference. Pretrained on 14.8T high-quality tokens with SFT and RL, it outperforms other open models and approaches leading closed models.",
  "deepseek-ai/DeepSeek-V4-Flash.description": "DeepSeek-V4-Flash is a preview version of the MoE language model in the DeepSeek-V4 series. The total parameter size is 284B, the activation parameter size is 13B, and it supports 1M tokens ultra-long context.The model uses a hybrid attention architecture that combines CSA and HCA, and introduces mHC and Muon Optimizer to improve long-context reasoning efficiency, training stability, and overall performance.",
  "deepseek-ai/DeepSeek-V4-Pro.description": "DeepSeek-V4-Pro is the flagship MoE language model in the DeepSeek-V4 series, with 1.6T total parameters and 49B active parameters, natively supporting an ultra-long context of 1 million tokens. The model adopts an innovative hybrid attention architecture combining Compressed Sparse Attention (CSA) and Highly Compressed Attention (HCA), requiring only 27% of DeepSeek-V3.2 per-token inference FLOPs and 10% KV cache at 1M context. It also introduces Manifold-Constrained Hyper Connections (mHC) to enhance inter-layer signal propagation stability, and employs the Muon optimizer to accelerate convergence. DeepSeek-V4-Pro is pretrained on over 32T high-quality diverse tokens, with post-training using a two-stage paradigm of independent domain expert cultivation plus online policy distillation for unified integration. Its maximum reasoning intensity mode DeepSeek-V4-Pro-Max achieves top performance on coding benchmarks and significantly narrows the gap with leading closed-source models on reasoning and agentic tasks, making it one of the strongest open-source models today, supporting Non-think, Think High, and Think Max reasoning intensity modes.",
  "deepseek-ai/deepseek-llm-67b-chat.description": "DeepSeek LLM Chat (67B) is an innovative model offering deep language understanding and interaction.",
  "deepseek-chat.description": "A new open-source model combining general and code abilities. It preserves the chat model’s general dialogue and the coder model’s strong coding, with better preference alignment. DeepSeek-V2.5 also improves writing and instruction following.",
  "deepseek-coder-33B-instruct.description": "DeepSeek Coder 33B is a code language model trained on 2T tokens (87% code, 13% Chinese/English text). It introduces a 16K context window and fill-in-the-middle tasks, providing project-level code completion and snippet infilling.",
  "deepseek-coder-v2.description": "DeepSeek Coder V2 is an open-source MoE code model that performs strongly on coding tasks, comparable to GPT-4 Turbo.",
  "deepseek-coder-v2:236b.description": "DeepSeek Coder V2 is an open-source MoE code model that performs strongly on coding tasks, comparable to GPT-4 Turbo.",
  "deepseek-r1-0528.description": "685B full model released on 2025-05-28. DeepSeek-R1 uses large-scale RL in post-training, greatly improving reasoning with minimal labeled data, and performs strongly on math, coding, and natural language reasoning.",
  "deepseek-r1-250528.description": "DeepSeek R1 250528 is the full DeepSeek-R1 reasoning model for hard math and logic tasks.",
  "deepseek-r1-70b-fast-online.description": "DeepSeek R1 70B fast edition with real-time web search, delivering quicker responses while maintaining performance.",
  "deepseek-r1-70b-online.description": "DeepSeek R1 70B standard edition with real-time web search, suited for up-to-date chat and text tasks.",
  "deepseek-r1-distill-llama-70b.description": "DeepSeek R1 Distill Llama 70B combines R1 reasoning with the Llama ecosystem.",
  "deepseek-r1-distill-llama-8b.description": "DeepSeek-R1-Distill-Llama-8B is distilled from Llama-3.1-8B using DeepSeek R1 outputs.",
  "deepseek-r1-distill-llama.description": "deepseek-r1-distill-llama is distilled from DeepSeek-R1 on Llama.",
  "deepseek-r1-distill-qianfan-70b.description": "DeepSeek R1 Distill Qianfan 70B is an R1 distill based on Qianfan-70B with strong value.",
  "deepseek-r1-distill-qianfan-8b.description": "DeepSeek R1 Distill Qianfan 8B is an R1 distill based on Qianfan-8B for small and mid-sized apps.",
  "deepseek-r1-distill-qianfan-llama-70b.description": "DeepSeek R1 Distill Qianfan Llama 70B is an R1 distill based on Llama-70B.",
  "deepseek-r1-distill-qwen-1.5b.description": "DeepSeek R1 Distill Qwen 1.5B is an ultra-light distill model for very low-resource environments.",
  "deepseek-r1-distill-qwen-14b.description": "DeepSeek R1 Distill Qwen 14B is a mid-size distill model for multi-scenario deployment.",
  "deepseek-r1-distill-qwen-32b.description": "DeepSeek R1 Distill Qwen 32B is an R1 distill based on Qwen-32B, balancing performance and cost.",
  "deepseek-r1-distill-qwen-7b.description": "DeepSeek R1 Distill Qwen 7B is a lightweight distill model for edge and private enterprise environments.",
  "deepseek-r1-distill-qwen.description": "deepseek-r1-distill-qwen is distilled from DeepSeek-R1 on Qwen.",
  "deepseek-r1-fast-online.description": "DeepSeek R1 fast full version with real-time web search, combining 671B-scale capability and faster response.",
  "deepseek-r1-online.description": "DeepSeek R1 full version with 671B parameters and real-time web search, offering stronger understanding and generation.",
  "deepseek-r1.description": "DeepSeek-R1 uses cold-start data before RL and performs comparably to OpenAI-o1 on math, coding, and reasoning.",
  "deepseek-reasoner.description": "A DeepSeek reasoning model focused on complex logical reasoning tasks.",
  "deepseek-v2.description": "DeepSeek V2 is an efficient MoE model for cost-effective processing.",
  "deepseek-v2:236b.description": "DeepSeek V2 236B is DeepSeek’s code-focused model with strong code generation.",
  "deepseek-v3-0324.description": "DeepSeek-V3-0324 is a 671B-parameter MoE model with standout strengths in programming and technical capability, context understanding, and long-text handling.",
  "deepseek-v3.1-terminus.description": "DeepSeek-V3.1-Terminus is a terminal-optimized LLM from DeepSeek, tailored for terminal devices.",
  "deepseek-v3.1-think-250821.description": "DeepSeek V3.1 Think 250821 is the deep-thinking model corresponding to the Terminus version, built for high-performance reasoning.",
  "deepseek-v3.1.description": "DeepSeek V3.1 uses a hybrid reasoning architecture with both thinking and non-thinking modes.",
  "deepseek-v3.1:671b.description": "DeepSeek V3.1 is a next-generation reasoning model with improved complex reasoning and chain-of-thought, suited for tasks requiring deep analysis.",
  "deepseek-v3.2-exp.description": "deepseek-v3.2-exp introduces sparse attention to improve training and inference efficiency on long text, at a lower price than deepseek-v3.1.",
  "deepseek-v3.2-speciale.description": "On highly complex tasks, the Speciale model significantly outperforms the standard version, but it consumes considerably more tokens and incurs higher costs. Currently, DeepSeek-V3.2-Speciale is intended for research use only, does not support tool calls, and has not been specifically optimized for everyday conversation or writing tasks.",
  "deepseek-v3.2-think.description": "DeepSeek V3.2 Think is a full deep-thinking model with stronger long-chain reasoning.",
  "deepseek-v3.2-thinking.description": "DeepSeek-V3.2 Thinking is the thinking mode variant of DeepSeek-V3.2, focused on reasoning tasks.",
  "deepseek-v3.2.description": "DeepSeek-V3.2 is DeepSeek's latest coding model with strong reasoning capabilities.",
  "deepseek-v3.description": "DeepSeek-V3 is a powerful MoE model with 671B total parameters and 37B active per token.",
  "deepseek-v4-flash.description": "DeepSeek-V4-Flash is DeepSeek’s efficient 1M-context model on Volcano Ark, balancing speed and cost while keeping strong reasoning and agent capabilities.",
  "deepseek-v4-pro.description": "DeepSeek-V4-Pro is DeepSeek’s flagship MoE model on Volcano Ark, supporting both non-thinking and thinking modes for advanced reasoning, code generation, and complex agent workflows.",
  "deepseek-vl2-small.description": "DeepSeek VL2 Small is a lightweight multimodal version for resource-constrained and high-concurrency use.",
  "deepseek-vl2.description": "DeepSeek VL2 is a multimodal model for image-text understanding and fine-grained visual QA.",
  "deepseek/deepseek-chat-v3-0324.description": "DeepSeek V3 is a 685B-parameter MoE model and the latest iteration of DeepSeek’s flagship chat series.\n\nIt builds on [DeepSeek V3](/deepseek/deepseek-chat-v3) and performs strongly across tasks.",
  "deepseek/deepseek-chat-v3.1.description": "DeepSeek-V3.1 is DeepSeek’s long-context hybrid reasoning model, supporting mixed thinking/non-thinking modes and tool integration.",
  "deepseek/deepseek-chat.description": "DeepSeek-V3 is DeepSeek’s high-performance hybrid reasoning model for complex tasks and tool integration.",
  "deepseek/deepseek-math-v2.description": "DeepSeek Math V2 is a model that has made significant breakthroughs in mathematical reasoning capabilities. Its core innovation lies in the \"self-verification\" training mechanism, and it has achieved gold medal levels in several top mathematics competitions.",
  "deepseek/deepseek-r1-0528.description": "DeepSeek R1 0528 is an updated variant focused on open availability and deeper reasoning.",
  "deepseek/deepseek-r1-distill-llama-70b.description": "DeepSeek R1 Distill Llama 70B is a distilled LLM based on Llama 3.3 70B, fine-tuned using DeepSeek R1 outputs to achieve competitive performance with large frontier models.",
  "deepseek/deepseek-r1-distill-llama-8b.description": "DeepSeek R1 Distill Llama 8B is a distilled LLM based on Llama-3.1-8B-Instruct, trained using DeepSeek R1 outputs.",
  "deepseek/deepseek-r1-distill-qwen-14b.description": "DeepSeek R1 Distill Qwen 14B is a distilled LLM based on Qwen 2.5 14B, trained using DeepSeek R1 outputs. It surpasses OpenAI o1-mini on multiple benchmarks, achieving state-of-the-art results among dense models. Benchmark highlights:\nAIME 2024 pass@1: 69.7\nMATH-500 pass@1: 93.9\nCodeForces Rating: 1481\nFine-tuning on DeepSeek R1 outputs delivers competitive performance with larger frontier models.",
  "deepseek/deepseek-r1-distill-qwen-32b.description": "DeepSeek R1 Distill Qwen 32B is a distilled LLM based on Qwen 2.5 32B, trained using DeepSeek R1 outputs. It surpasses OpenAI o1-mini on multiple benchmarks, achieving state-of-the-art results among dense models. Benchmark highlights:\nAIME 2024 pass@1: 72.6\nMATH-500 pass@1: 94.3\nCodeForces Rating: 1691\nFine-tuning on DeepSeek R1 outputs delivers competitive performance with larger frontier models.",
  "deepseek/deepseek-r1.description": "DeepSeek R1 has been updated to DeepSeek-R1-0528. With more compute and post-training algorithmic optimizations, it significantly improves reasoning depth and capability. It performs strongly across math, programming, and general logic benchmarks, approaching leaders like o3 and Gemini 2.5 Pro.",
  "deepseek/deepseek-r1/community.description": "DeepSeek R1 is the latest open-source model released by the DeepSeek team, with very strong reasoning performance, especially in math, coding, and reasoning tasks, comparable to OpenAI o1.",
  "deepseek/deepseek-reasoner.description": "DeepSeek-V3 Thinking (reasoner) is DeepSeek’s experimental reasoning model, suitable for high-complexity reasoning tasks.",
  "deepseek/deepseek-v3.description": "A fast general-purpose LLM with enhanced reasoning.",
  "deepseek/deepseek-v3/community.description": "DeepSeek-V3 delivers a major breakthrough in reasoning speed over previous models. It ranks first among open-source models and rivals the most advanced closed models. DeepSeek-V3 adopts Multi-Head Latent Attention (MLA) and the DeepSeekMoE architecture, both fully validated in DeepSeek-V2. It also introduces a lossless auxiliary strategy for load balancing and a multi-token prediction training objective for stronger performance.",
  "deepseek_r1.description": "DeepSeek-R1 is a reinforcement-learning-driven reasoning model that addresses repetition and readability issues. Before RL, it uses cold-start data to further improve reasoning performance. It matches OpenAI-o1 on math, coding, and reasoning tasks, with carefully designed training improving overall results.",
  "deepseek_r1_distill_llama_70b.description": "DeepSeek-R1-Distill-Llama-70B is distilled from Llama-3.3-70B-Instruct. As part of the DeepSeek-R1 series, it is fine-tuned on DeepSeek-R1-generated samples and performs strongly in math, coding, and reasoning.",
  "deepseek_r1_distill_qwen_14b.description": "DeepSeek-R1-Distill-Qwen-14B is distilled from Qwen2.5-14B and fine-tuned on 800K curated samples generated by DeepSeek-R1, delivering strong reasoning.",
  "deepseek_r1_distill_qwen_32b.description": "DeepSeek-R1-Distill-Qwen-32B is distilled from Qwen2.5-32B and fine-tuned on 800K curated samples generated by DeepSeek-R1, excelling in math, coding, and reasoning.",
  "devstral-2512.description": "Devstral 2 is an enterprise-level text model that excels at using tools to explore codebases, edit multiple files, and power software engineering agents.",
  "devstral-2:123b.description": "Devstral 2 123B excels at using tools to explore codebases, edit multiple files, and support software engineering agents.",
  "doubao-1.5-lite-32k.description": "Doubao-1.5-lite is a new lightweight model with ultra-fast response, delivering top-tier quality and latency.",
  "doubao-1.5-pro-256k.description": "Doubao-1.5-pro-256k is a comprehensive upgrade to Doubao-1.5-Pro, improving overall performance by 10%. It supports a 256k context window and up to 12k output tokens, delivering higher performance, a larger window, and strong value for broader use cases.",
  "doubao-1.5-pro-32k.description": "Doubao-1.5-pro is a new-generation flagship model with across-the-board upgrades, excelling in knowledge, coding, and reasoning.",
  "doubao-1.5-vision-pro-32k.description": "Doubao-1.5-vision-pro is an upgraded multimodal model that supports images at any resolution and extreme aspect ratios, enhancing visual reasoning, document recognition, detail understanding, and instruction following.",
  "doubao-lite-32k.description": "Ultra-fast response with better value, offering more flexible choices across scenarios. Supports reasoning and fine-tuning with a 32k context window.",
  "doubao-pro-32k.description": "The best-performing flagship model for complex tasks, with strong results in reference QA, summarization, creation, text classification, and roleplay. Supports reasoning and fine-tuning with a 32k context window.",
  "doubao-seed-1.6-flash.description": "Doubao-Seed-1.6-flash is an ultra-fast multimodal deep-reasoning model with TPOT as low as 10ms. It supports both text and vision, surpasses the previous lite model in text understanding, and matches competing pro models in vision. It supports a 256k context window and up to 16k output tokens.",
  "doubao-seed-1.6-vision.description": "Doubao-Seed-1.6-vision is a visual deep-reasoning model that delivers stronger multimodal understanding and reasoning for education, image review, inspection/security, and AI search Q&A. It supports a 256k context window and up to 64k output tokens.",
  "doubao-seed-1.6.description": "Doubao-Seed-1.6 is a new multimodal deep-reasoning model with auto, thinking, and non-thinking modes. In non-thinking mode, it significantly outperforms Doubao-1.5-pro/250115. It supports a 256k context window and up to 16k output tokens.",
  "doubao-seed-1.8.description": "Doubao-Seed-1.8 has stronger multimodal understanding and Agent capabilities, supports text/image/video input and context caching, and can deliver excellent performance in complex tasks.",
  "doubao-seed-2.0-code.description": "Doubao-Seed-2.0-code is deeply optimized for agentic coding, supports multimodal inputs and a 256k context window, fitting coding, vision understanding, and agent workflows.",
  "doubao-seed-2.0-lite.description": "Doubao-Seed-2.0-lite is a new multimodal deep-reasoning model that delivers better value and a strong choice for common tasks, with a context window up to 256k.",
  "doubao-seed-2.0-mini.description": "Doubao-Seed-2.0-mini is a lightweight model with fast response and high performance, suitable for small tasks and high-concurrency scenarios.",
  "doubao-seed-2.0-pro.description": "Doubao-Seed-2.0-pro is ByteDance's flagship Agent general model, with all-around leaps in complex task planning and execution capabilities.",
  "doubao-seed-code.description": "Doubao-Seed-Code is deeply optimized for agentic coding, supports multimodal inputs (text/image/video) and a 256k context window, is compatible with the Anthropic API, and fits coding, vision understanding, and agent workflows.",
  "doubao-seedance-1-0-pro-250528.description": "Seedance 1.0 Pro is a video generation foundation model that supports multi-shot storytelling. It delivers strong performance across multiple dimensions. The model achieves breakthroughs in semantic understanding and instruction following, enabling it to generate 1080P high-definition videos with smooth motion, rich details, diverse styles, and cinematic-level visual aesthetics.",
  "doubao-seedance-1-0-pro-fast-251015.description": "Seedance 1.0 Pro Fast is a comprehensive model designed to minimize cost while maximizing performance, achieving an excellent balance between video generation quality, speed, and price. It inherits the core strengths of Seedance 1.0 Pro, while offering faster generation speeds and more competitive pricing, delivering creators a dual optimization of efficiency and cost.",
  "doubao-seedance-1-5-pro-251215.description": "Seedance 1.5 Pro by ByteDance supports text-to-video, image-to-video (first frame, first+last frame), and audio generation synchronized with visuals.",
  "doubao-seedance-2-0-260128.description": "Seedance 2.0 by ByteDance is the most powerful video generation model, supporting multimodal reference video generation, video editing, video extension, text-to-video, and image-to-video with synchronized audio.",
  "doubao-seedance-2-0-fast-260128.description": "Seedance 2.0 Fast by ByteDance offers the same capabilities as Seedance 2.0 with faster generation speeds at a more competitive price.",
  "doubao-seedream-4-0-250828.description": "Seedream 4.0 is an image generation model from ByteDance Seed, supporting text and image inputs with highly controllable, high-quality image generation. It generates images from text prompts.",
  "doubao-seedream-4-5-251128.description": "Seedream 4.5 is ByteDance’s latest multimodal image model, integrating text-to-image, image-to-image, and batch image generation capabilities, while incorporating commonsense and reasoning abilities. Compared to the previous 4.0 version, it delivers significantly improved generation quality, with better editing consistency and multi-image fusion. It offers more precise control over visual details, producing small text and small faces more naturally, and achieves more harmonious layout and color, enhancing overall aesthetics.",
  "doubao-seedream-5-0-260128.description": "Doubao-Seedream-5.0-lite is ByteDance’s latest image-generation model. For the first time, it integrates online retrieval capabilities, allowing it to incorporate real-time web information and enhance the timeliness of generated images. The model’s intelligence has also been upgraded, enabling precise interpretation of complex instructions and visual content. Additionally, it offers improved global knowledge coverage, reference consistency, and generation quality in professional scenarios, better meeting enterprise-level visual creation needs.",
  "dreamina-seedance-2-0-260128.description": "Seedance 2.0 by ByteDance is the most powerful video generation model, supporting multimodal reference video generation, video editing, video extension, text-to-video, and image-to-video with synchronized audio.",
  "dreamina-seedance-2-0-fast-260128.description": "Seedance 2.0 Fast by ByteDance offers the same capabilities as Seedance 2.0 with faster generation speeds at a more competitive price.",
  "emohaa.description": "Emohaa is a mental health model with professional counseling abilities to help users understand emotional issues.",
  "ernie-4.5-0.3b.description": "ERNIE 4.5 0.3B is an open-source lightweight model for local and customized deployment.",
  "ernie-4.5-8k-preview.description": "ERNIE 4.5 8K Preview is an 8K context preview model for evaluating ERNIE 4.5.",
  "ernie-4.5-turbo-128k.description": "ERNIE 4.5 Turbo 128K is a high-performance general model with search augmentation and tool calling for QA, coding, and agent scenarios.",
  "ernie-4.5-turbo-20260402.description": "ERNIE 4.5 Turbo 20260402 is a high-performance general model with search augmentation and tool calling for QA, coding, and agent scenarios.",
  "ernie-4.5-turbo-32k.description": "ERNIE 4.5 Turbo 32K is a mid-length context version for QA, knowledge base retrieval, and multi-turn dialogue.",
  "ernie-4.5-turbo-latest.description": "Latest ERNIE 4.5 Turbo with optimized overall performance, ideal as the primary production model.",
  "ernie-4.5-turbo-vl-32k.description": "ERNIE 4.5 Turbo VL 32K is a mid-long multimodal version for combined long-doc and image understanding.",
  "ernie-4.5-turbo-vl-latest.description": "ERNIE 4.5 Turbo VL Latest is the newest multimodal version with improved image-text understanding and reasoning.",
  "ernie-4.5-turbo-vl.description": "ERNIE 4.5 Turbo VL is a mature multimodal model for production image-text understanding and recognition.",
  "ernie-5.0-thinking-latest.description": "Wenxin 5.0 Thinking is a native full-modal flagship model with unified text, image, audio, and video modeling. It delivers broad capability upgrades for complex QA, creation, and agent scenarios.",
  "ernie-5.0-thinking-preview.description": "Wenxin 5.0 Thinking Preview is a native full-modal flagship model with unified text, image, audio, and video modeling. It delivers broad capability upgrades for complex QA, creation, and agent scenarios.",
  "ernie-5.0.description": "ERNIE 5.0, the new-generation model in the ERNIE series, is a natively multimodal large model. It adopts a unified multimodal modeling approach, jointly modeling text, images, audio, and video to deliver comprehensive multimodal capabilities. Its foundational abilities have been significantly upgraded, achieving strong performance on benchmark evaluations. It particularly excels in multimodal understanding, instruction following, creative writing, factual accuracy, agent planning, and tool utilization.",
  "ernie-5.1.description": "ERNIE 5.1 is the latest model in the ERNIE series, featuring comprehensive upgrades to its foundational capabilities. It demonstrates significant improvements in areas such as agents, knowledge processing, reasoning, and deep search. This release adopts a decoupled fully asynchronous reinforcement learning architecture, specifically designed to address key challenges in the evolution of large models toward autonomous agent decision-making, including training–inference numerical discrepancies, low utilization of heterogeneous computing resources, and global issues caused by long-tail effects. In addition, large-scale agent post-training techniques are employed to further enhance the model’s capabilities and generalization performance. Through a three-stage collaborative framework involving environment, expert, and fusion processes, the approach not only ensures training efficiency but also significantly improves the model’s stability and performance on complex tasks.",
  "ernie-char-fiction-8k-preview.description": "ERNIE Character Fiction 8K Preview is a character and plot creation model preview for feature evaluation and testing.",
  "ernie-char-fiction-8k.description": "ERNIE Character Fiction 8K is a persona model for novels and plot creation, suited for long-form story generation.",
  "ernie-image-turbo.description": "ERNIE-Image is an 8B-parameter text-to-image model developed by Baidu. It ranks among the top on multiple benchmarks, achieving a tied first place in SuperCLUE in China and leading in the open-source track.",
  "ernie-irag-edit.description": "ERNIE iRAG Edit is an image editing model supporting erasing, repainting, and variant generation.",
  "ernie-lite-pro-128k.description": "ERNIE Lite Pro 128K is a lightweight high-performance model for latency- and cost-sensitive scenarios.",
  "ernie-novel-8k.description": "ERNIE Novel 8K is built for long-form novels and IP plots with multi-character narratives.",
  "ernie-speed-pro-128k.description": "ERNIE Speed Pro 128K is a high-concurrency, high-value model for large-scale online services and enterprise apps.",
  "ernie-x1-turbo-32k-preview.description": "ERNIE X1 Turbo 32K Preview is a fast thinking model with 32K context for complex reasoning and multi-turn chat.",
  "ernie-x1-turbo-32k.description": "ERNIE X1 Turbo 32K is a fast thinking model with 32K context for complex reasoning and multi-turn chat.",
  "ernie-x1.1-preview.description": "ERNIE X1.1 Preview is a thinking-model preview for evaluation and testing.",
  "ernie-x1.1.description": "ERNIE X1.1 is a thinking-model preview for evaluation and testing.",
  "fal-ai/bytedance/seedream/v4.5.description": "Seedream 4.5, built by ByteDance Seed team, supports multi-image editing and composition. Features enhanced subject consistency, precise instruction following, spatial logic understanding, aesthetic expression, poster layout and logo design with high-precision text-image rendering.",
  "fal-ai/bytedance/seedream/v4.description": "Seedream 4.0 is an image generation model from ByteDance Seed, supporting text and image inputs with highly controllable, high-quality image generation. It generates images from text prompts.",
  "fal-ai/flux-kontext/dev.description": "FLUX.1 model focused on image editing, supporting text and image inputs.",
  "fal-ai/flux-pro/kontext.description": "FLUX.1 Kontext [pro] accepts text and reference images as input, enabling targeted local edits and complex global scene transformations.",
  "fal-ai/flux/krea.description": "Flux Krea [dev] is an image generation model with an aesthetic bias toward more realistic, natural images.",
  "fal-ai/flux/schnell.description": "FLUX.1 [schnell] is a 12B-parameter image generation model built for fast, high-quality output.",
  "fal-ai/hunyuan-image/v3.description": "A powerful native multimodal image generation model.",
  "fal-ai/imagen4/preview.description": "High-quality image generation model from Google.",
  "fal-ai/nano-banana.description": "Nano Banana is Google’s newest, fastest, and most efficient native multimodal model, enabling image generation and editing through conversation.",
  "fal-ai/qwen-image-edit.description": "A professional image editing model from the Qwen team that supports semantic and appearance edits, precisely edits Chinese and English text, and enables high-quality edits such as style transfer and object rotation.",
  "fal-ai/qwen-image.description": "A powerful image generation model from the Qwen team with impressive Chinese text rendering and diverse visual styles.",
  "flux-1-schnell.description": "A 12B-parameter text-to-image model from Black Forest Labs using latent adversarial diffusion distillation to generate high-quality images in 1-4 steps. It rivals closed alternatives and is released under Apache-2.0 for personal, research, and commercial use.",
  "flux-dev.description": "Open-source R&D image generation model, efficiently optimized for non-commercial innovation research.",
  "flux-kontext-max.description": "State-of-the-art contextual image generation and editing, combining text and images for precise, coherent results.",
  "flux-kontext-pro.description": "State-of-the-art contextual image generation and editing, combining text and images for precise, coherent results.",
  "flux-pro-1.1-ultra.description": "Ultra-high-resolution image generation with 4MP output, producing crisp images in 10 seconds.",
  "flux-pro-1.1.description": "Upgraded professional-grade image generation model with excellent image quality and precise prompt adherence.",
  "flux-pro.description": "Top-tier commercial image generation model with unmatched image quality and diverse outputs.",
  "flux.1-schnell.description": "FLUX.1-schnell is a high-performance image generation model for fast multi-style outputs.",
  "gemini-1.0-pro-001.description": "Gemini 1.0 Pro 001 (Tuning) provides stable, tunable performance for complex tasks.",
  "gemini-1.0-pro-002.description": "Gemini 1.0 Pro 002 (Tuning) provides strong multimodal support for complex tasks.",
  "gemini-1.0-pro-latest.description": "Gemini 1.0 Pro is Google’s high-performance AI model designed for broad task scaling.",
  "gemini-1.5-flash-001.description": "Gemini 1.5 Flash 001 is an efficient multimodal model for broad application scaling.",
  "gemini-1.5-flash-002.description": "Gemini 1.5 Flash 002 is an efficient multimodal model built for broad deployment.",
  "gemini-1.5-flash-8b-exp-0924.description": "Gemini 1.5 Flash 8B 0924 is the latest experimental model with notable gains across text and multimodal use cases.",
  "gemini-1.5-flash-8b.description": "Gemini 1.5 Flash 8B is an efficient multimodal model for broad application scaling.",
  "gemini-1.5-flash-exp-0827.description": "Gemini 1.5 Flash 0827 delivers optimized multimodal processing for complex tasks.",
  "gemini-1.5-flash-latest.description": "Gemini 1.5 Flash is Google’s latest multimodal AI model with fast processing, supporting text, image, and video inputs for efficient scaling across tasks.",
  "gemini-1.5-pro-001.description": "Gemini 1.5 Pro 001 is a scalable multimodal AI solution for complex tasks.",
  "gemini-1.5-pro-002.description": "Gemini 1.5 Pro 002 is the latest production-ready model with higher-quality output, especially for math, long context, and vision tasks.",
  "gemini-1.5-pro-exp-0801.description": "Gemini 1.5 Pro 0801 provides strong multimodal processing with greater flexibility for app development.",
  "gemini-1.5-pro-exp-0827.description": "Gemini 1.5 Pro 0827 applies latest optimizations for more efficient multimodal processing.",
  "gemini-1.5-pro-latest.description": "Gemini 1.5 Pro supports up to 2 million tokens, an ideal mid-sized multimodal model for complex tasks.",
  "gemini-2.0-flash-001.description": "Gemini 2.0 Flash delivers next-gen features including exceptional speed, native tool use, multimodal generation, and a 1M-token context window.",
  "gemini-2.0-flash-lite-001.description": "A Gemini 2.0 Flash variant optimized for cost efficiency and low latency.",
  "gemini-2.0-flash-lite.description": "A Gemini 2.0 Flash variant optimized for cost efficiency and low latency.",
  "gemini-2.0-flash.description": "Gemini 2.0 Flash delivers next-gen features including exceptional speed, native tool use, multimodal generation, and a 1M-token context window.",
  "gemini-2.5-flash-image.description": "Nano Banana is Google’s newest, fastest, and most efficient native multimodal model, enabling conversational image generation and editing.",
  "gemini-2.5-flash-image:image.description": "Nano Banana is Google’s newest, fastest, and most efficient native multimodal model, enabling conversational image generation and editing.",
  "gemini-2.5-flash-lite-preview-06-17.description": "Gemini 2.5 Flash-Lite Preview is Google’s smallest, best-value model, designed for large-scale use.",
  "gemini-2.5-flash-lite.description": "Gemini 2.5 Flash-Lite is Google’s smallest, best-value model, designed for large-scale use.",
  "gemini-2.5-flash-preview-04-17.description": "Gemini 2.5 Flash Preview is Google’s best-value model with full capabilities.",
  "gemini-2.5-flash.description": "Gemini 2.5 Flash is Google’s best-value model with full capabilities.",
  "gemini-2.5-pro-preview-03-25.description": "Gemini 2.5 Pro Preview is Google’s most advanced reasoning model, able to reason over code, math, and STEM problems and analyze large datasets, codebases, and documents with long context.",
  "gemini-2.5-pro-preview-05-06.description": "Gemini 2.5 Pro Preview is Google’s most advanced reasoning model, able to reason over code, math, and STEM problems and analyze large datasets, codebases, and documents with long context.",
  "gemini-2.5-pro.description": "Gemini 2.5 Pro is Google’s most advanced reasoning model, able to reason over code, math, and STEM problems and analyze large datasets, codebases, and documents with long context.",
  "gemini-3-flash-preview.description": "Gemini 3 Flash is the smartest model built for speed, combining cutting-edge intelligence with excellent search grounding.",
  "gemini-3-flash.description": "Gemini 3 Flash by Google — ultra-fast model with multimodal input support.",
  "gemini-3-pro-image-preview.description": "Gemini 3 Pro Image (Nano Banana Pro) is Google's image generation model that also supports multimodal dialogue.",
  "gemini-3-pro-image-preview:image.description": "Gemini 3 Pro Image (Nano Banana Pro) is Google’s image generation model and also supports multimodal chat.",
  "gemini-3-pro-preview.description": "Gemini 3 Pro is Google’s most powerful agent and vibe-coding model, delivering richer visuals and deeper interaction on top of state-of-the-art reasoning.",
  "gemini-3.1-flash-image-preview.description": "Gemini 3.1 Flash Image (Nano Banana 2) is Google's fastest native image generation model with thinking support, conversational image generation and editing.",
  "gemini-3.1-flash-image-preview:image.description": "Gemini 3.1 Flash Image (Nano Banana 2) is Google's fastest native image generation model with thinking support, conversational image generation and editing.",
  "gemini-3.1-flash-lite-preview.description": "Gemini 3.1 Flash-Lite Preview is Google's most cost-efficient multimodal model, optimized for high-volume agentic tasks, translation, and data processing.",
  "gemini-3.1-flash-lite.description": "Gemini 3.1 Flash-Lite is Google's most cost-efficient multimodal model, optimized for high-volume agentic tasks, translation, and data processing.",
  "gemini-3.1-pro-preview.description": "Gemini 3.1 Pro Preview improves on Gemini 3 Pro with enhanced reasoning capabilities and adds medium thinking level support.",
  "gemini-3.1-pro.description": "Gemini 3.1 Pro by Google — premium multimodal model with 1M context window.",
  "gemini-3.5-flash.description": "Gemini's most intelligent model built for speed, combining frontier intelligence with superior search and grounding.",
  "gemini-flash-latest.description": "Points to gemini-3-flash-preview",
  "gemini-flash-lite-latest.description": "Points to gemini-3.1-flash-lite",
  "gemini-pro-latest.description": "Points to gemini-3.1-pro-preview",
  "gemma-7b-it.description": "Gemma 7B is cost-effective for small to mid-scale tasks.",
  "gemma2-9b-it.description": "Gemma 2 9B is optimized for specific tasks and tool integration.",
  "gemma2.description": "Gemma 2 is Google’s efficient model, covering use cases from small apps to complex data processing.",
  "gemma2:27b.description": "Gemma 2 is Google’s efficient model, covering use cases from small apps to complex data processing.",
  "gemma2:2b.description": "Gemma 2 is Google’s efficient model, covering use cases from small apps to complex data processing.",
  "generalv3.5.description": "Spark Max is the most full-featured version, supporting web search and many built-in plugins. Its fully optimized core capabilities, system roles, and function calling deliver excellent performance across complex application scenarios.",
  "generalv3.description": "Spark Pro is a high-performance LLM optimized for professional domains, focusing on math, programming, healthcare, and education, with web search and built-in plugins such as weather and date. It delivers strong performance and efficiency in complex knowledge Q&A, language understanding, and advanced text creation, making it an ideal choice for professional use cases.",
  "glm-4-0520.description": "GLM-4-0520 is the latest model version, designed for highly complex and diverse tasks with excellent performance.",
  "glm-4-7.description": "GLM-4.7 is the latest flagship model from Zhipu AI. GLM-4.7 enhances coding capabilities, long-term task planning, and tool collaboration for Agentic Coding scenarios, achieving leading performance among open-source models in multiple public benchmarks. General capabilities are improved, with more concise and natural responses, and more immersive writing. In complex agent tasks, instruction following is stronger during tool calls, and the aesthetics of Artifacts and Agentic Coding frontend, as well as long-term task completion efficiency, are further enhanced. • Stronger programming capabilities: Significantly improved multi-language coding and terminal agent performance; GLM-4.7 can now implement \"think first, then act\" mechanisms in programming frameworks like Claude Code, Kilo Code, TRAE, Cline, and Roo Code, with more stable performance on complex tasks. • Frontend aesthetics improvement: GLM-4.7 shows significant progress in frontend generation quality, capable of generating websites, PPTs, and posters with better visual appeal. • Stronger tool calling capabilities: GLM-4.7 enhances tool calling abilities, scoring 67 in BrowseComp web task evaluation; achieving 84.7 in τ²-Bench interactive tool calling evaluation, surpassing Claude Sonnet 4.5 as the open-source SOTA. • Reasoning capability improvement: Significantly enhanced math and reasoning abilities, scoring 42.8% in the HLE (\"Humanity's Last Exam\") benchmark, a 41% improvement over GLM-4.6, surpassing GPT-5.1. • General capability enhancement: GLM-4.7 conversations are more concise, intelligent, and humane; writing and role-playing are more literary and immersive.",
  "glm-4-9b-chat.description": "GLM-4-9B-Chat performs strongly across semantics, math, reasoning, code, and knowledge. It also supports web browsing, code execution, custom tool calling, and long-text reasoning, with support for 26 languages including Japanese, Korean, and German.",
  "glm-4-air-250414.description": "GLM-4-Air is a high-value option with performance close to GLM-4, fast speed, and lower cost.",
  "glm-4-air.description": "GLM-4-Air is a high-value option with performance close to GLM-4, fast speed, and lower cost.",
  "glm-4-airx.description": "GLM-4-AirX is a more efficient GLM-4-Air variant with up to 2.6x faster reasoning.",
  "glm-4-alltools.description": "GLM-4-AllTools is a versatile agent model optimized for complex instruction planning and tool use such as web browsing, code explanation, and text generation, suitable for multi-task execution.",
  "glm-4-flash-250414.description": "GLM-4-Flash is ideal for simple tasks: fastest and free.",
  "glm-4-flash.description": "GLM-4-Flash is ideal for simple tasks: fastest and free.",
  "glm-4-flashx.description": "GLM-4-FlashX is an enhanced Flash version with ultra-fast reasoning.",
  "glm-4-long.description": "GLM-4-Long supports ultra-long inputs for memory-style tasks and large-scale document processing.",
  "glm-4-plus.description": "GLM-4-Plus is a high-intelligence flagship with strong long-text and complex-task handling and upgraded overall performance.",
  "glm-4.1v-thinking-flash.description": "GLM-4.1V-Thinking is the strongest known ~10B VLM, covering SOTA tasks like video understanding, image QA, subject solving, OCR, document and chart reading, GUI agents, frontend coding, and grounding. It even surpasses the 8x larger Qwen2.5-VL-72B on many tasks. With advanced RL, it uses chain-of-thought reasoning to improve accuracy and richness, outperforming traditional non-thinking models in both outcomes and explainability.",
  "glm-4.1v-thinking-flashx.description": "GLM-4.1V-Thinking is the strongest known ~10B VLM, covering SOTA tasks like video understanding, image QA, subject solving, OCR, document and chart reading, GUI agents, frontend coding, and grounding. It even surpasses the 8x larger Qwen2.5-VL-72B on many tasks. With advanced RL, it uses chain-of-thought reasoning to improve accuracy and richness, outperforming traditional non-thinking models in both outcomes and explainability.",
  "glm-4.5-air.description": "GLM-4.5 lightweight edition that balances performance and cost, with flexible hybrid thinking modes.",
  "glm-4.5-airx.description": "GLM-4.5-Air fast edition with quicker responses for high-scale, high-speed use.",
  "glm-4.5-x.description": "GLM-4.5 fast edition, delivering strong performance with generation speeds up to 100 tokens/sec.",
  "glm-4.5.description": "Zhipu flagship model with a switchable thinking mode, delivering open-source SOTA overall and up to 128K context.",
  "glm-4.5v.description": "Zhipu’s next-generation MoE vision reasoning model has 106B total parameters with 12B active, achieving SOTA among similarly sized open-source multimodal models across image, video, document understanding, and GUI tasks.",
  "glm-4.6.description": "Zhipu's latest flagship model GLM-4.6 (355B) fully surpasses its predecessors in advanced coding, long-text processing, reasoning, and agent capabilities. It particularly aligns with Claude Sonnet 4 in programming ability, becoming China's top Coding model.",
  "glm-4.6v-flash.description": "The GLM-4.6V series represents a major iteration of the GLM family in the multimodal direction, comprising GLM-4.6V (flagship), GLM-4.6V-FlashX (lightweight and high-speed), and GLM-4.6V-Flash (fully free). It extends the training-time context window to 128k tokens, achieves state-of-the-art visual understanding accuracy at comparable parameter scales, and, for the first time, natively integrates Function Call (tool invocation) capabilities into the visual model architecture. This unifies the pipeline from “visual perception” to “executable actions,” providing a consistent technical foundation for multimodal agents in real-world production scenarios.",
  "glm-4.6v-flashx.description": "The GLM-4.6V series represents a major iteration of the GLM family in the multimodal direction, comprising GLM-4.6V (flagship), GLM-4.6V-FlashX (lightweight and high-speed), and GLM-4.6V-Flash (fully free). It extends the training-time context window to 128k tokens, achieves state-of-the-art visual understanding accuracy at comparable parameter scales, and, for the first time, natively integrates Function Call (tool invocation) capabilities into the visual model architecture. This unifies the pipeline from “visual perception” to “executable actions,” providing a consistent technical foundation for multimodal agents in real-world production scenarios.",
  "glm-4.6v.description": "The GLM-4.6V series represents a major iteration of the GLM family in the multimodal direction, comprising GLM-4.6V (flagship), GLM-4.6V-FlashX (lightweight and high-speed), and GLM-4.6V-Flash (fully free). It extends the training-time context window to 128k tokens, achieves state-of-the-art visual understanding accuracy at comparable parameter scales, and, for the first time, natively integrates Function Call (tool invocation) capabilities into the visual model architecture. This unifies the pipeline from “visual perception” to “executable actions,” providing a consistent technical foundation for multimodal agents in real-world production scenarios.",
  "glm-4.7-flash.description": "GLM-4.7-Flash, as a 30B-level SOTA model, offers a new choice that balances performance and efficiency. It enhances coding capabilities, long-term task planning, and tool collaboration for Agentic Coding scenarios, achieving leading performance among open-source models of the same size in multiple current benchmark leaderboards. In executing complex intelligent agent tasks, it has stronger instruction compliance during tool calls, and further improves the aesthetics of front-end and the efficiency of long-term task completion for Artifacts and Agentic Coding.",
  "glm-4.7-flashx.description": "GLM-4.7-Flash, as a 30B-level SOTA model, offers a new choice that balances performance and efficiency. It enhances coding capabilities, long-term task planning, and tool collaboration for Agentic Coding scenarios, achieving leading performance among open-source models of the same size in multiple current benchmark leaderboards. In executing complex intelligent agent tasks, it has stronger instruction compliance during tool calls, and further improves the aesthetics of front-end and the efficiency of long-term task completion for Artifacts and Agentic Coding.",
  "glm-4.7.description": "GLM-4.7 is Zhipu's latest flagship model, enhanced for Agentic Coding scenarios with improved coding capabilities, long-term task planning, and tool collaboration. It achieves leading performance among open-source models on multiple public benchmarks. General capabilities are improved with more concise and natural responses and more immersive writing. For complex agent tasks, instruction following during tool calls is stronger, and the frontend aesthetics and long-term task completion efficiency of Artifacts and Agentic Coding are further enhanced.",
  "glm-4.description": "GLM-4 is the older flagship released in Jan 2024, now replaced by the stronger GLM-4-0520.",
  "glm-4v-flash.description": "GLM-4V-Flash focuses on efficient single-image understanding for fast analysis scenarios such as real-time or batch image processing.",
  "glm-4v-plus-0111.description": "GLM-4V-Plus understands video and multiple images, suitable for multimodal tasks.",
  "glm-4v-plus.description": "GLM-4V-Plus understands video and multiple images, suitable for multimodal tasks.",
  "glm-4v.description": "GLM-4V provides strong image understanding and reasoning across visual tasks.",
  "glm-5-turbo.description": "GLM-5-Turbo is a foundation model deeply optimized for agentic scenarios. It has been specifically optimized for core requirements of agent tasks from the training phase, enhancing key capabilities such as tool invocation, command following, and long-chain execution. It is ideal for building high-performance agent assistants.",
  "glm-5.1.description": "GLM-5.1 is Zhipu’s latest flagship model, aligned with Claude Opus 4.6 on overall and coding capabilities. It excels at long-horizon tasks, able to autonomously plan, execute, and iterate for up to 8 hours in a single task, making it an ideal foundation for Autonomous Agents and long-horizon Coding Agents.",
  "glm-5.description": "GLM-5 is Zhipu’s next-generation flagship foundation model, purpose-built for Agentic Engineering. It delivers reliable productivity in complex systems engineering and long-horizon agentic tasks. In coding and agent capabilities, GLM-5 achieves state-of-the-art performance among open-source models. In real-world programming scenarios, its user experience approaches that of Claude Opus 4.5. It excels at complex systems engineering and long-horizon agent tasks, making it an ideal foundation model for general-purpose agent assistants.",
  "glm-5v-turbo.description": "GLM-5V-Turbo is Zhipu’s multimodal Coding foundation model for visual programming tasks. It natively handles images, video, text, and files, and is optimized for long-horizon planning, complex coding, and agent execution in multimodal workflows.",
  "glm-image.description": "GLM-Image is Zhipu’s new flagship image generation model. The model was trained end-to-end on domestically produced chips and adopts an original hybrid architecture that combines autoregressive modeling with a diffusion decoder. This design enables strong global instruction understanding alongside fine-grained local detail rendering, overcoming long-standing challenges in generating knowledge-dense content such as posters, presentations, and educational diagrams. It represents an important exploration toward a new generation of “cognitive generative” technology paradigms, exemplified by Nano Banana Pro.",
  "glm-z1-air.description": "Reasoning model with strong reasoning for tasks that require deep inference.",
  "glm-z1-airx.description": "Ultra-fast reasoning with high reasoning quality.",
  "glm-z1-flash.description": "GLM-Z1 series provides strong complex reasoning, excelling in logic, math, and programming.",
  "glm-z1-flashx.description": "Fast and low-cost: Flash-enhanced with ultra-fast reasoning and higher concurrency.",
  "glm-zero-preview.description": "GLM-Zero-Preview delivers strong complex reasoning, excelling in logic, math, and programming.",
  "global.anthropic.claude-haiku-4-5-20251001-v1:0.description": "Claude Haiku 4.5 is Anthropic's fastest and most intelligent Haiku model, with lightning speed and extended thinking.",
  "global.anthropic.claude-opus-4-5-20251101-v1:0.description": "Claude Opus 4.5 is Anthropic's flagship model, combining exceptional intelligence and scalable performance for complex tasks requiring the highest-quality responses and reasoning.",
  "global.anthropic.claude-opus-4-6-v1.description": "Claude Opus 4.6 is Anthropic's most intelligent model for building agents and coding.",
  "global.anthropic.claude-opus-4-7.description": "Claude Opus 4.7 is Anthropic's most capable generally available model for complex reasoning and agentic coding.",
  "global.anthropic.claude-sonnet-4-5-20250929-v1:0.description": "Claude Sonnet 4.5 is Anthropic's most intelligent model to date.",
  "global.anthropic.claude-sonnet-4-6.description": "Claude Sonnet 4.6 is Anthropic’s best combination of speed and intelligence.",
  "google/gemini-2.0-flash-001.description": "Gemini 2.0 Flash delivers next-gen capabilities, including excellent speed, native tool use, multimodal generation, and a 1M-token context window.",
  "google/gemini-2.0-flash-lite-001.description": "Gemini 2.0 Flash Lite is a lightweight Gemini variant with thinking disabled by default to improve latency and cost, but it can be enabled via parameters.",
  "google/gemini-2.0-flash-lite.description": "Gemini 2.0 Flash Lite delivers next-gen features including exceptional speed, built-in tool use, multimodal generation, and a 1M-token context window.",
  "google/gemini-2.0-flash.description": "Gemini 2.0 Flash is Google’s high-performance reasoning model for extended multimodal tasks.",
  "google/gemini-2.5-flash-image.description": "Gemini 2.5 Flash Image (Nano Banana) is Google’s image generation model with multimodal conversation support.",
  "google/gemini-2.5-flash-lite.description": "Gemini 2.5 Flash Lite is the lightweight Gemini 2.5 variant optimized for latency and cost, suitable for high-throughput scenarios.",
  "google/gemini-2.5-flash.description": "Gemini 2.5 Flash is Google’s family spanning low latency to high-performance reasoning.",
  "google/gemini-2.5-pro-preview.description": "Gemini 2.5 Pro Preview is Google’s most advanced thinking model for reasoning over complex problems in code, math, and STEM, and for analyzing large datasets, codebases, and documents with long context.",
  "google/gemini-2.5-pro.description": "Gemini 2.5 Pro is Google’s flagship reasoning model with long context support for complex tasks.",
  "google/gemini-3-pro-image-preview.description": "Gemini 3 Pro Image (Nano Banana Pro) is Google’s image generation model with multimodal conversation support.",
  "google/gemini-3-pro-preview.description": "Gemini 3 Pro is the next-generation multimodal reasoning model in the Gemini family, understanding text, audio, images, and video, and handling complex tasks and large codebases.",
  "google/gemini-3.1-flash-image-preview.description": "Gemini 3.1 Flash Image Preview, a.k.a. \"Nano Banana 2,\" is Google’s latest state of the art image generation and editing model, delivering Pro-level visual quality at Flash speed. It combines advanced contextual understanding with fast, cost-efficient inference, making complex image generation and iterative edits significantly more accessible.",
  "google/gemini-embedding-001.description": "A state-of-the-art embedding model with strong performance in English, multilingual, and code tasks.",
  "google/gemma-2-27b-it.description": "Gemma 2 27B is a general-purpose LLM with strong performance across many scenarios.",
  "google/gemma-2-27b.description": "Gemma 2 is Google’s efficient model family for use cases from small apps to complex data processing.",
  "google/gemma-2-2b-it.description": "An advanced small language model designed for edge applications.",
  "google/gemma-2-9b-it.description": "Gemma 2 9B, developed by Google, offers efficient instruction following and solid overall capability.",
  "google/gemma-2-9b.description": "Gemma 2 is Google’s efficient model family for use cases from small apps to complex data processing.",
  "google/gemma-2b-it.description": "Gemma Instruct (2B) provides basic instruction handling for lightweight applications.",
  "google/gemma-3-12b-it.description": "Gemma 3 12B is a Google open-source language model setting a new bar for efficiency and performance.",
  "google/gemma-3-27b-it.description": "Gemma 3 27B is a Google open-source language model setting a new bar for efficiency and performance.",
  "google/text-embedding-005.description": "An English-focused text embedding model optimized for code and English language tasks.",
  "google/text-multilingual-embedding-002.description": "A multilingual text embedding model optimized for cross-lingual tasks across many languages.",
  "gpt-3.5-turbo-0125.description": "GPT 3.5 Turbo for text generation and understanding; currently points to gpt-3.5-turbo-0125.",
  "gpt-3.5-turbo-1106.description": "GPT 3.5 Turbo for text generation and understanding; currently points to gpt-3.5-turbo-0125.",
  "gpt-3.5-turbo-instruct.description": "GPT 3.5 Turbo for text generation and understanding tasks, optimized for instruction following.",
  "gpt-3.5-turbo.description": "GPT 3.5 Turbo for text generation and understanding; currently points to gpt-3.5-turbo-0125.",
  "gpt-35-turbo-16k.description": "GPT-3.5 Turbo 16k is a high-capacity text generation model for complex tasks.",
  "gpt-35-turbo.description": "GPT-3.5 Turbo is OpenAI’s efficient model for chat and text generation, supporting parallel function calling.",
  "gpt-4-0125-preview.description": "The latest GPT-4 Turbo model includes vision. Vision requests can use JSON mode and function calling. GPT-4 Turbo is an enhanced version that balances accuracy and efficiency for cost-effective multimodal tasks and real-time interactions.",
  "gpt-4-0613.description": "GPT-4 provides a larger context window to handle longer inputs, suitable for broad information synthesis and data analysis.",
  "gpt-4-1106-preview.description": "The latest GPT-4 Turbo model includes vision. Vision requests can use JSON mode and function calling. GPT-4 Turbo is an enhanced version that balances accuracy and efficiency for cost-effective multimodal tasks and real-time interactions.",
  "gpt-4-32k-0613.description": "GPT-4 provides a larger context window to handle longer inputs for scenarios needing broad information integration and data analysis.",
  "gpt-4-32k.description": "GPT-4 provides a larger context window to handle longer inputs for scenarios needing broad information integration and data analysis.",
  "gpt-4-turbo-2024-04-09.description": "The latest GPT-4 Turbo adds vision. Visual requests support JSON mode and function calling. It is a cost-effective multimodal model that balances accuracy and efficiency for real-time applications.",
  "gpt-4-turbo-preview.description": "The latest GPT-4 Turbo model includes vision. Vision requests can use JSON mode and function calling. GPT-4 Turbo is an enhanced version that balances accuracy and efficiency for cost-effective multimodal tasks and real-time interactions.",
  "gpt-4-turbo.description": "The latest GPT-4 Turbo adds vision. Visual requests support JSON mode and function calling. It is a cost-effective multimodal model that balances accuracy and efficiency for real-time applications.",
  "gpt-4-vision-preview.description": "GPT-4 Vision preview, designed for image analysis and processing tasks.",
  "gpt-4.1-mini.description": "GPT-4.1 mini balances intelligence, speed, and cost, making it attractive for many use cases.",
  "gpt-4.1-nano.description": "GPT-4.1 nano is the fastest and most cost-effective GPT-4.1 model.",
  "gpt-4.1.description": "GPT-4.1 is our flagship model for complex tasks and cross-domain problem solving.",
  "gpt-4.5-preview.description": "GPT-4.5-preview is the latest general-purpose model with deep world knowledge and better intent understanding, strong at creative tasks and agent planning. Its knowledge cutoff is October 2023.",
  "gpt-4.description": "GPT-4 provides a larger context window to handle longer inputs, suitable for broad information synthesis and data analysis.",
  "gpt-4o-2024-05-13.description": "ChatGPT-4o is a dynamic model updated in real time, combining strong understanding and generation for large-scale use cases like customer support, education, and technical support.",
  "gpt-4o-2024-08-06.description": "ChatGPT-4o is a dynamic model updated in real time. It combines strong language understanding and generation for large-scale use cases like customer support, education, and technical assistance.",
  "gpt-4o-2024-11-20.description": "ChatGPT-4o is a dynamic model updated in real time, combining strong understanding and generation for large-scale use cases like customer support, education, and technical support.",
  "gpt-4o-mini-realtime-preview.description": "GPT-4o-mini realtime variant with audio and text real-time I/O.",
  "gpt-4o-mini-search-preview.description": "GPT-4o mini Search Preview is trained to understand and execute web search queries via the Chat Completions API. Web search is billed per tool call in addition to token costs.",
  "gpt-4o-mini-transcribe.description": "GPT-4o Mini Transcribe is a speech-to-text model that transcribes audio with GPT-4o, improving word error rate, language ID, and accuracy over the original Whisper model.",
  "gpt-4o-mini-tts.description": "GPT-4o mini TTS is a text-to-speech model built on GPT-4o mini, converting text into natural-sounding speech with a max input of 2000 tokens.",
  "gpt-4o-mini.description": "GPT-4o mini is OpenAI’s latest model after GPT-4 Omni, supporting text+image input with text output. It is their most advanced small model, far cheaper than recent frontier models and over 60% cheaper than GPT-3.5 Turbo, while maintaining top-tier intelligence (82% MMLU).",
  "gpt-4o-realtime-preview-2024-10-01.description": "GPT-4o realtime variant with audio and text real-time I/O.",
  "gpt-4o-realtime-preview-2025-06-03.description": "GPT-4o realtime variant with audio and text real-time I/O.",
  "gpt-4o-realtime-preview.description": "GPT-4o realtime variant with audio and text real-time I/O.",
  "gpt-4o-search-preview.description": "GPT-4o Search Preview is trained to understand and execute web search queries via the Chat Completions API. Web search is billed per tool call in addition to token costs.",
  "gpt-4o-transcribe.description": "GPT-4o Transcribe is a speech-to-text model that transcribes audio with GPT-4o, improving word error rate, language ID, and accuracy over the original Whisper model.",
  "gpt-4o.description": "ChatGPT-4o is a dynamic model updated in real time, combining strong understanding and generation for large-scale use cases like customer support, education, and technical support.",
  "gpt-5-chat-latest.description": "The GPT-5 model used in ChatGPT, combining strong understanding and generation for conversational applications.",
  "gpt-5-chat.description": "GPT-5 Chat is a preview model optimized for conversational scenarios. It supports text and image input, outputs text only, and fits chatbots and conversational AI applications.",
  "gpt-5-codex.description": "GPT-5 Codex by OpenAI — coding-specialized variant with tool use support.",
  "gpt-5-mini.description": "A faster, more cost-efficient GPT-5 variant for well-defined tasks, delivering quicker responses while maintaining quality.",
  "gpt-5-nano.description": "GPT-5 Nano by OpenAI — lightweight and cost-efficient model.",
  "gpt-5-pro.description": "GPT-5 pro uses more compute to think deeper and consistently deliver better answers.",
  "gpt-5.1-chat-latest.description": "GPT-5.1 Chat: the ChatGPT variant of GPT-5.1, built for chat scenarios.",
  "gpt-5.1-codex-max.description": "GPT-5.1 Codex Max by OpenAI — maximum capability Codex variant.",
  "gpt-5.1-codex-mini.description": "GPT-5.1 Codex Mini by OpenAI — compact coding model with strong capabilities.",
  "gpt-5.1-codex.description": "GPT-5.1 Codex by OpenAI — coding-focused variant with enhanced tool use.",
  "gpt-5.1.description": "GPT-5.1 by OpenAI — improved GPT-5 with better reasoning accuracy.",
  "gpt-5.2-chat-latest.description": "GPT-5.2 Chat is the ChatGPT variant (chat-latest) for the latest conversation improvements.",
  "gpt-5.2-codex.description": "GPT-5.2 Codex by OpenAI — coding-specialized with improved tool call accuracy.",
  "gpt-5.2-pro.description": "GPT-5.2 pro: a smarter, more precise GPT-5.2 variant (Responses API only), suited for hard problems and longer multi-turn reasoning.",
  "gpt-5.2.description": "GPT-5.2 by OpenAI — upgraded reasoning and multimodal processing.",
  "gpt-5.3-chat-latest.description": "GPT-5.3 Chat is the latest ChatGPT model used in ChatGPT with improved conversation experiences.",
  "gpt-5.3-codex-spark.description": "GPT-5.3 Codex Spark by OpenAI — compact coding model optimized for speed.",
  "gpt-5.3-codex.description": "GPT-5.3 Codex by OpenAI — latest Codex with enhanced code understanding.",
  "gpt-5.4-mini.description": "GPT-5.4 Mini by OpenAI — efficient model balancing cost and performance.",
  "gpt-5.4-nano.description": "GPT-5.4 Nano by OpenAI — ultra-lightweight model for high-throughput tasks.",
  "gpt-5.4-pro.description": "GPT-5.4 Pro by OpenAI — most capable model with maximum context and reasoning.",
  "gpt-5.4.description": "GPT-5.4 by OpenAI — next-gen model with 1M+ context window and multimodal input.",
  "gpt-5.5-pro.description": "GPT-5.5 pro uses more compute to think harder and provide consistently better answers.",
  "gpt-5.5.description": "GPT-5.5 is our newest frontier model for the most complex professional work.",
  "gpt-5.description": "GPT-5 by OpenAI — flagship model with advanced reasoning and multimodal input.",
  "gpt-audio.description": "GPT Audio is a general chat model for audio input/output, supported in the Chat Completions API.",
  "gpt-image-1-mini.description": "A lower-cost GPT Image 1 variant with native text and image input and image output.",
  "gpt-image-1.5.description": "An enhanced GPT Image 1 model with 4× faster generation, more precise editing, and improved text rendering.",
  "gpt-image-1.description": "ChatGPT native multimodal image generation model.",
  "gpt-image-2.description": "OpenAI's next-generation multimodal image model with native reasoning, up to 4K resolution, near-perfect text rendering, and high-fidelity multilingual support.",
  "gpt-oss-120b.description": "Access requires an application. GPT-OSS-120B is an open-source large language model from OpenAI with strong text generation capability.",
  "gpt-oss-20b.description": "Access requires an application. GPT-OSS-20B is an open-source mid-size language model from OpenAI with efficient text generation.",
  "gpt-oss:120b.description": "GPT-OSS 120B is OpenAI’s large open-source LLM using MXFP4 quantization and positioned as a flagship model. It requires multi-GPU or high-end workstation environments and delivers excellent performance in complex reasoning, code generation, and multilingual processing, with advanced function calling and tool integration.",
  "gpt-oss:20b.description": "GPT-OSS 20B is an open-source LLM from OpenAI using MXFP4 quantization, suitable for high-end consumer GPUs or Apple Silicon Macs. It performs well in dialogue generation, coding, and reasoning tasks, supporting function calling and tool use.",
  "gpt-realtime.description": "A general real-time model supporting real-time text and audio I/O, plus image input.",
  "grok-3-mini.description": "xAI’s Grok 3 Mini with strong reasoning and fast responses.",
  "grok-3.description": "xAI’s Grok 3 with strong reasoning capability.",
  "grok-4-0709.description": "xAI’s Grok 4 with strong reasoning capability.",
  "grok-4-20-non-reasoning.description": "A non-reasoning variant for simple use cases",
  "grok-4-20-reasoning.description": "Intelligent, blazing-fast model that reasons before responding",
  "grok-4.20-0309-non-reasoning.description": "A non-reasoning variant for simple use cases",
  "grok-4.20-0309-reasoning.description": "Intelligent, blazing-fast model that reasons before responding",
  "grok-4.20-beta-0309-non-reasoning.description": "A non-reasoning variant for simple use cases",
  "grok-4.20-beta-0309-reasoning.description": "Intelligent, blazing-fast model that reasons before responding",
  "grok-4.20-multi-agent-0309.description": "A team of 4 or 16 agents, Excels at research use cases, Does not currently support client-side tools. Only supports xAI server side tools (eg X Search, Web Search tools) and remote MCP tools.",
  "grok-4.3.description": "The most truth-seeking large language model in the world",
  "grok-imagine-image-quality.description": "Generate images from text prompts, edit existing images with natural language, or iteratively refine images through multi-turn conversations.",
  "grok-imagine-image.description": "Generate images from text prompts, edit existing images with natural language, or iteratively refine images through multi-turn conversations.",
  "grok-imagine-video.description": "State-of-the-art video generation across quality, cost, and latency.",
  "groq/compound-mini.description": "Compound-mini is a composite AI system powered by publicly available models supported on GroqCloud, intelligently and selectively using tools to answer user queries.",
  "groq/compound.description": "Compound is a composite AI system powered by multiple publicly available models supported on GroqCloud, intelligently and selectively using tools to answer user queries.",
  "gryphe/mythomax-l2-13b.description": "MythoMax L2 13B is a creative, intelligent language model merged from multiple top models.",
  "happyhorse-1.0-i2v.description": "HappyHorse-1.0-I2V supports text-to-video generation, delivering highly faithful dynamic visuals. It can accurately understand textual semantics and produce high-quality videos that are smooth, natural, and rich in detail.",
  "happyhorse-1.0-r2v.description": "HappyHorse-1.0-R2V supports reference-based video generation, offering more stable subject and scene consistency. It supports up to 9 reference images, accurately preserves creative intent, and delivers enhanced expressive capability.",
  "happyhorse-1.0-t2v.description": "HappyHorse-1.0-T2V supports text-to-video generation, delivering highly faithful dynamic visuals. It can accurately understand textual semantics and produce high-quality videos that are smooth, natural, and rich in detail.",
  "hunyuan-2.0-instruct-20251111.description": "The model foundation has been comprehensively upgraded, with more robust core capabilities. It achieves top-tier performance in knowledge, mathematics, writing, and reasoning. It also demonstrates excellent performance in instruction following, multi-turn interactions, and long-context comprehension.",
  "hunyuan-2.0-thinking-20251109.description": "Specialized in creative content, multi-turn interactions, and practical instruction-following scenarios. Significantly enhanced capabilities in mathematics, coding, and agent-based tasks.",
  "hunyuan-code.description": "Hunyuan’s latest code model trained on 200B high-quality code data plus six months of SFT data, with 8K context. It ranks near the top in automated code benchmarks and in expert human evaluations across five languages.",
  "hunyuan-functioncall.description": "Hunyuan’s latest MoE FunctionCall model trained on high-quality tool-call data, with a 32K context window and leading benchmarks across dimensions.",
  "hunyuan-lite.description": "Upgraded to an MoE architecture with a 256K context window, leading many open-source models across NLP, code, math, and domain benchmarks.",
  "hunyuan-pro.description": "Trillion-parameter MOE-32K long-context model leading benchmarks, strong at complex instructions and reasoning, advanced math, function calling, and optimized for multilingual translation, finance, law, and medical domains.",
  "hunyuan-role-latest.description": "For role-playing scenarios, it delivers highly consistent character alignment and exceptionally natural, human-like conversational style. It offers engaging narrative development and progression, along with emotional companionship and fulfillment.",
  "hunyuan-role.description": "Hunyuan’s latest roleplay model, officially fine-tuned with roleplay data, delivering stronger base performance in roleplay scenarios.",
  "hunyuan-standard-256K.description": "Uses improved routing to mitigate load balancing and expert collapse. Long-text \"needle in a haystack\" reaches 99.9%. MOE-256K pushes further in length and quality, greatly expanding input length.",
  "hunyuan-standard.description": "Uses improved routing to mitigate load balancing and expert collapse. Long-text \"needle in a haystack\" reaches 99.9%. MOE-32K offers better value while balancing quality and price for long-text inputs.",
  "hunyuan-turbo.description": "Preview of Hunyuan’s next-gen LLM with a new MoE architecture, delivering faster reasoning and stronger results than hunyuan-pro.",
  "hunyuan-vision.description": "Hunyuan latest multimodal model supporting image + text inputs to generate text.",
  "hy-image-lite.description": "It adopts an ultra-high compression codec to enable fast image generation while maintaining high-quality output. It supports use cases such as e-commerce product image enhancement, design asset generation for creative tools, and iterative game scene development.",
  "hy-image-v3.0.description": "Based on the Hunyuan large model, it is capable of reasoning about image layout, composition, and brushwork, using world knowledge to infer commonsense visual scenes. It can also interpret complex semantics at the scale of thousands of characters, generate long-form textual content, complex comics, memes, and produce vivid and engaging educational illustrations.",
  "hy-video-1.5.description": "It supports multimodal inputs including text and images to generate high-quality videos, enabling scene transitions and multi-character interactions. It streamlines production workflows and reduces costs, making it suitable for enterprise advertising, marketing, and individual creative applications.",
  "hy3-preview.description": "Hunyuan Hy3 Preview is designed for agent workloads, adopting a Mixture-of-Experts (MoE) architecture with 295B total parameters and 21B activated parameters. It offers three modes within a single model—**no_think** (ultra-fast response), **think_low** (quick reasoning), and **think_high** (deep reasoning)—to accommodate varying latency and depth requirements, from high-frequency interactions to complex engineering tasks. It achieves near state-of-the-art performance on coding benchmarks such as SWE-bench Verified, and supports a 256K context window for cross-file code refactoring and long-document analysis. This model is well-suited for developers who require reliable task completion while remaining sensitive to inference cost.",
  "image-01-live.description": "An image generation model with fine detail, supporting text-to-image and controllable style presets.",
  "image-01.description": "A new image generation model with fine detail, supporting text-to-image and image-to-image.",
  "imagen-4.0-fast-generate-001.description": "Imagen 4th generation text-to-image model series Fast version",
  "imagen-4.0-generate-001.description": "Imagen 4th generation text-to-image model series",
  "imagen-4.0-ultra-generate-001.description": "Imagen 4th generation text-to-image model series Ultra version",
  "inception/mercury-coder-small.description": "Mercury Coder Small is ideal for code generation, debugging, and refactoring with minimal latency.",
  "inclusionAI/Ling-flash-2.0.description": "Ling-flash-2.0 is the third Ling 2.0 architecture model from Ant Group’s Bailing team. It is an MoE model with 100B total parameters but only 6.1B active per token (4.8B non-embedding). Despite its lightweight configuration, it matches or exceeds 40B dense models and even larger MoE models on multiple benchmarks, exploring high efficiency through architecture and training strategy.",
  "inclusionAI/Ling-mini-2.0.description": "Ling-mini-2.0 is a small, high-performance MoE LLM with 16B total parameters and only 1.4B active per token (789M non-embedding), delivering very fast generation. With efficient MoE design and large high-quality training data, it achieves top-tier performance comparable to dense models under 10B and larger MoE models.",
  "inclusionai/ling-1t.description": "Ling-1T is inclusionAI’s 1T MoE model, optimized for high-intensity reasoning tasks and large-context workloads.",
  "inclusionai/ling-flash-2.0.description": "Ling-flash-2.0 is inclusionAI’s MoE model optimized for efficiency and reasoning performance, suitable for mid-to-large tasks.",
  "inclusionai/ling-mini-2.0.description": "Ling-mini-2.0 is inclusionAI’s lightweight MoE model, significantly reducing cost while retaining reasoning capability.",
  "inclusionai/ming-flash-omini-preview.description": "Ming-flash-omni Preview is inclusionAI’s multimodal model, supporting speech, image, and video inputs, with improved image rendering and speech recognition.",
  "inclusionai/ring-1t.description": "Ring-1T is inclusionAI’s trillion-parameter MoE reasoning model, suited for large-scale reasoning and research tasks.",
  "inclusionai/ring-flash-2.0.description": "Ring-flash-2.0 is a Ring model variant from inclusionAI for high-throughput scenarios, emphasizing speed and cost efficiency.",
  "inclusionai/ring-mini-2.0.description": "Ring-mini-2.0 is inclusionAI's high-throughput lightweight MoE model, built for concurrency.",
  "intern-latest.description": "By default, it points to our latest released Intern series model, currently set to intern-s2-preview.",
  "intern-s1-mini.description": "A lightweight multimodal large model with strong scientific reasoning capabilities.",
  "intern-s1-pro.description": "We have launched our most advanced open-source multimodal reasoning model, currently the top-performing open-source multimodal large language model in terms of overall performance.",
  "intern-s1.description": "The open-source multimodal reasoning model not only demonstrates strong general-purpose capabilities but also achieves state-of-the-art performance across a wide range of scientific tasks.",
  "intern-s2-preview.description": "Our newly released 35B-A3B scientific multimodal reasoning model supports a 256K context window. Through task scaling and architectural optimization, it is specifically designed to enhance scientific discovery and general-purpose agent capabilities.",
  "internvl2.5-38b-mpo.description": "InternVL2.5 38B MPO is a multimodal pretrained model for complex image-text reasoning.",
  "internvl3-14b.description": "InternVL3 14B is a mid-size multimodal model balancing performance and cost.",
  "internvl3-1b.description": "InternVL3 1B is a lightweight multimodal model for resource-constrained deployment.",
  "internvl3-38b.description": "InternVL3 38B is a large open-source multimodal model for high-accuracy image-text understanding.",
  "internvl3.5-241b-a28b.description": "Our newly released multimodal large model features enhanced image-and-text understanding and long-sequence image comprehension capabilities, achieving performance comparable to leading closed-source models.",
  "internvl3.5-latest.description": "By default, it points to the latest model in the InternVL3.5 series, currently set to internvl3.5-241b-a28b.",
  "irag-1.0.description": "ERNIE iRAG is an image retrieval-augmented generation model for image search, image-text retrieval, and content generation.",
  "jamba-large.description": "Our most powerful, advanced model, designed for complex enterprise tasks with outstanding performance.",
  "jamba-mini.description": "The most efficient model in its class, balancing speed and quality with a smaller footprint.",
  "jina-deepsearch-v1.description": "DeepSearch combines web search, reading, and reasoning for thorough investigations. Think of it as an agent that takes your research task, performs broad searches with multiple iterations, and only then produces an answer. The process involves continuous research, reasoning, and multi-angle problem solving, fundamentally different from standard LLMs that answer from pretraining data or traditional RAG systems that rely on one-shot surface search.",
  "kimi-k2-instruct.description": "Kimi K2 Instruct is Kimi’s official reasoning model with long context for code, QA, and more.",
  "kimi-k2-thinking.description": "kimi-k2-thinking is a Moonshot AI thinking model with general agentic and reasoning abilities. It excels at deep reasoning and can solve hard problems via multi-step tool use.",
  "kimi-k2.5.description": "Kimi K2.5 is Kimi's most versatile model to date, featuring a native multimodal architecture that supports both vision and text inputs, 'thinking' and 'non-thinking' modes, and both conversational and agent tasks.",
  "kimi-k2.6.description": "Kimi-K2.6 is a large language model launched by Moonshot AI, with excellent coding and tool calling capabilities. Service deployment is only supported in mainland China.",
  "kimi-k2:1t.description": "Kimi K2 is a large MoE LLM from Moonshot AI with 1T total parameters and 32B active per forward pass. It is optimized for agent capabilities including advanced tool use, reasoning, and code synthesis.",
  "kling/kling-v3-image-generation.description": "Supports up to 10 reference images, allowing you to lock subjects, elements, and color tones to ensure consistent style. Combines style transfer, portrait/character referencing, multi-image fusion, and localized inpainting for flexible control. Delivers realistic portrait details, with overall visuals that are delicate and richly layered, featuring cinematic color and atmosphere.",
  "kling/kling-v3-omni-image-generation.description": "Unlock cinematic storytelling visuals with new series image generation and direct 2K/4K output. Deeply analyzes audiovisual elements in prompts to precisely execute creative instructions. Supports flexible multi-reference inputs and comprehensive quality upgrades, ideal for storyboards, narrative concept art, and scene design.",
  "kling/kling-v3-omni-video-generation.description": "New “All-in-One Reference” feature supports 3–8 second videos or multiple images to anchor character elements. Can match original audio and lip movements for authentic character representation. Enhances video consistency and dynamic expression. Supports audiovisual synchronization and intelligent storyboarding.",
  "kling/kling-v3-video-generation.description": "Intelligent storyboarding understands scene transitions within scripts, automatically arranging camera positions and shot types. A native multimodal framework ensures audiovisual consistency. Removes duration constraints, enabling more flexible multi-shot storytelling.",
  "kuaishou/kat-coder-pro-v1.description": "KAT-Coder-Pro-V1 (limited-time free) focuses on code understanding and automation for efficient coding agents.",
  "labs-devstral-small-2512.description": "Devstral Small 2 excels at using tools to explore code bases, edit multiple files, and power software engineering agents.",
  "labs-leanstral-2603.description": "Mistral's first open-source code agent designed for Lean 4, built for formal proof engineering in realistic repositories. 119B parameters with 6.5B active.",
  "lite.description": "Spark Lite is a lightweight LLM with ultra-low latency and efficient processing. It is fully free and supports real-time web search. Its fast responses perform well on low-compute devices and for model fine-tuning, delivering strong cost efficiency and an intelligent experience, especially for knowledge Q&A, content generation, and search scenarios.",
  "llama-3.1-70b-versatile.description": "Llama 3.1 70B delivers stronger AI reasoning for complex applications, supporting heavy compute with high efficiency and accuracy.",
  "llama-3.1-8b-instant.description": "Llama 3.1 8B is a high-efficiency model with fast text generation, ideal for large-scale, cost-effective applications.",
  "llama-3.1-instruct.description": "Llama 3.1 instruction-tuned model is optimized for chat and beats many open chat models on common industry benchmarks.",
  "llama-3.2-11b-vision-instruct.description": "Strong image reasoning on high-resolution images, suited for visual understanding apps.",
  "llama-3.2-11b-vision-preview.description": "Llama 3.2 is designed for tasks combining vision and text, excelling at image captioning and visual QA to bridge language generation and visual reasoning.",
  "llama-3.2-90b-vision-instruct.description": "Advanced image reasoning for visual-understanding agent applications.",
  "llama-3.2-90b-vision-preview.description": "Llama 3.2 is designed for tasks combining vision and text, excelling at image captioning and visual QA to bridge language generation and visual reasoning.",
  "llama-3.2-vision-instruct.description": "Llama 3.2-Vision instruction-tuned model is optimized for visual recognition, image reasoning, captioning, and general image Q&A.",
  "llama-3.3-70b-versatile.description": "Meta Llama 3.3 is a multilingual LLM with 70B parameters (text in/text out), offering pre-trained and instruction-tuned variants. The instruction-tuned text-only model is optimized for multilingual dialogue use cases and outperforms many available open and closed chat models on common industry benchmarks.",
  "llama-3.3-instruct.description": "Llama 3.3 instruction-tuned model is optimized for chat and beats many open chat models on common industry benchmarks.",
  "llama3-70b-8192.description": "Meta Llama 3 70B offers exceptional complexity handling for demanding projects.",
  "llama3-8b-8192.description": "Meta Llama 3 8B delivers strong reasoning performance for diverse scenarios.",
  "llama3-groq-70b-8192-tool-use-preview.description": "Llama 3 Groq 70B Tool Use provides strong tool-calling for efficient handling of complex tasks.",
  "llama3-groq-8b-8192-tool-use-preview.description": "Llama 3 Groq 8B Tool Use is optimized for efficient tool use with fast parallel compute.",
  "llama3.1.description": "Llama 3.1 is Meta’s leading model, scaling up to 405B parameters for complex dialogue, multilingual translation, and data analysis.",
  "llama3.1:405b.description": "Llama 3.1 is Meta’s leading model, scaling up to 405B parameters for complex dialogue, multilingual translation, and data analysis.",
  "llama3.1:70b.description": "Llama 3.1 is Meta’s leading model, scaling up to 405B parameters for complex dialogue, multilingual translation, and data analysis.",
  "llava-v1.5-7b-4096-preview.description": "LLaVA 1.5 7B fuses visual processing to generate complex outputs from visual inputs.",
  "llava.description": "LLaVA is a multimodal model combining a vision encoder and Vicuna for strong vision-language understanding.",
  "llava:13b.description": "LLaVA is a multimodal model combining a vision encoder and Vicuna for strong vision-language understanding.",
  "llava:34b.description": "LLaVA is a multimodal model combining a vision encoder and Vicuna for strong vision-language understanding.",
  "magistral-medium-2509.description": "Magistral Medium 1.2 is a frontier reasoning model from Mistral AI (Sep 2025) with vision support.",
  "magistral-small-2509.description": "Magistral Small 1.2 is an open-source small reasoning model from Mistral AI (Sep 2025) with vision support.",
  "mathstral.description": "MathΣtral is built for scientific research and mathematical reasoning, with strong computation and explanation.",
  "max-32k.description": "Spark Max 32K offers large-context processing with stronger context understanding and logical reasoning, supporting 32K-token inputs for long document reading and private knowledge Q&A.",
  "megrez-3b-instruct.description": "Megrez 3B Instruct is a small, efficient model from Wuwen Xinqiong.",
  "meituan/longcat-flash-chat.description": "An open-source non-thinking base model from Meituan optimized for dialogue and agent tasks, strong in tool use and complex multi-turn interactions.",
  "meta-llama-3-70b-instruct.description": "A powerful 70B-parameter model that excels at reasoning, coding, and broad language tasks.",
  "meta-llama-3-8b-instruct.description": "A versatile 8B-parameter model optimized for chat and text generation.",
  "meta-llama-3.1-405b-instruct.description": "Llama 3.1 instruction-tuned text model optimized for multilingual chat, performing strongly on common industry benchmarks among open and closed chat models.",
  "meta-llama-3.1-70b-instruct.description": "Llama 3.1 instruction-tuned text model optimized for multilingual chat, performing strongly on common industry benchmarks among open and closed chat models.",
  "meta-llama-3.1-8b-instruct.description": "Llama 3.1 instruction-tuned text model optimized for multilingual chat, performing strongly on common industry benchmarks among open and closed chat models.",
  "meta-llama/Llama-2-13b-chat-hf.description": "LLaMA-2 Chat (13B) provides strong language handling and a solid chat experience.",
  "meta-llama/Llama-2-70b-hf.description": "LLaMA-2 provides strong language handling and a solid interaction experience.",
  "meta-llama/Llama-3-70b-chat-hf.description": "Llama 3 70B Instruct Reference is a powerful chat model for complex dialogues.",
  "meta-llama/Llama-3-8b-chat-hf.description": "Llama 3 8B Instruct Reference offers multilingual support and broad domain knowledge.",
  "meta-llama/Llama-3.2-11B-Vision-Instruct-Turbo.description": "LLaMA 3.2 is designed for tasks combining vision and text. It excels at image captioning and visual QA, bridging language generation and visual reasoning.",
  "meta-llama/Llama-3.2-3B-Instruct-Turbo.description": "LLaMA 3.2 is designed for tasks combining vision and text. It excels at image captioning and visual QA, bridging language generation and visual reasoning.",
  "meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo.description": "LLaMA 3.2 is designed for tasks combining vision and text. It excels at image captioning and visual QA, bridging language generation and visual reasoning.",
  "meta-llama/Llama-3.3-70B-Instruct-Turbo.description": "Meta Llama 3.3 multilingual LLM is a 70B (text-in/text-out) pretrained and instruction-tuned model. The instruction-tuned text-only version is optimized for multilingual chat and outperforms many open and closed chat models on common industry benchmarks.",
  "meta-llama/Llama-Vision-Free.description": "LLaMA 3.2 is designed for tasks combining vision and text. It excels at image captioning and visual QA, bridging language generation and visual reasoning.",
  "meta-llama/Meta-Llama-3-70B-Instruct-Lite.description": "Llama 3 70B Instruct Lite is built for high performance with lower latency.",
  "meta-llama/Meta-Llama-3-70B-Instruct-Turbo.description": "Llama 3 70B Instruct Turbo delivers strong understanding and generation for the most demanding workloads.",
  "meta-llama/Meta-Llama-3-8B-Instruct-Lite.description": "Llama 3 8B Instruct Lite balances performance for resource-constrained environments.",
  "meta-llama/Meta-Llama-3-8B-Instruct-Turbo.description": "Llama 3 8B Instruct Turbo is a high-performance LLM for a wide range of use cases.",
  "meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo.description": "The 405B Llama 3.1 Turbo model provides massive context capacity for big data processing and excels in ultra-scale AI applications.",
  "meta-llama/Meta-Llama-3.1-405B-Instruct.description": "Llama 3.1 is Meta’s leading model family, scaling up to 405B parameters for complex dialogue, multilingual translation, and data analysis.",
  "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo.description": "Llama 3.1 70B is finely tuned for high-load applications; FP8 quantization delivers efficient compute and accuracy for complex scenarios.",
  "meta-llama/Meta-Llama-3.1-70B.description": "Llama 3.1 is Meta’s leading model family, scaling up to 405B parameters for complex dialogue, multilingual translation, and data analysis.",
  "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo.description": "Llama 3.1 8B uses FP8 quantization, supports up to 131,072 context tokens, and ranks among top open models for complex tasks across many benchmarks.",
  "meta-llama/llama-3-70b-instruct.description": "Llama 3 70B Instruct is optimized for high-quality dialogue and performs strongly in human evaluations.",
  "meta-llama/llama-3-8b-instruct.description": "Llama 3 8B Instruct is optimized for high-quality dialogue, outperforming many closed models.",
  "meta-llama/llama-3.1-70b-instruct.description": "Meta’s latest Llama 3.1 series, the 70B instruction-tuned variant optimized for high-quality dialogue. In industry evaluations, it shows strong performance against leading closed models. (Available only to enterprise-verified entities.)",
  "meta-llama/llama-3.1-8b-instruct.description": "Meta’s latest Llama 3.1 series, the 8B instruction-tuned variant is especially fast and efficient. In industry evaluations, it delivers strong performance, surpassing many leading closed models. (Available only to enterprise-verified entities.)",
  "meta-llama/llama-3.2-11b-vision-instruct.description": "LLaMA 3.2 is designed for tasks combining vision and text. It excels at image captioning and visual QA, bridging language generation and visual reasoning.",
  "meta-llama/llama-3.2-3b-instruct.description": "meta-llama/llama-3.2-3b-instruct",
  "meta-llama/llama-3.3-70b-instruct.description": "Llama 3.3 is the most advanced multilingual open-source Llama model, delivering near-405B performance at very low cost. It is Transformer-based and improved with SFT and RLHF for usefulness and safety. The instruction-tuned version is optimized for multilingual chat and beats many open and closed chat models on industry benchmarks. Knowledge cutoff: Dec 2023.",
  "meta-llama/llama-3.3-70b-instruct:free.description": "Llama 3.3 is the most advanced multilingual open-source Llama model, delivering near-405B performance at very low cost. It is Transformer-based and improved with SFT and RLHF for usefulness and safety. The instruction-tuned version is optimized for multilingual chat and beats many open and closed chat models on industry benchmarks. Knowledge cutoff: Dec 2023.",
  "meta.llama3-1-405b-instruct-v1:0.description": "Meta Llama 3.1 405B Instruct is the largest and most powerful Llama 3.1 Instruct model, a highly advanced model for dialogue reasoning and synthetic data generation, and a strong base for domain-specific continued pretraining or fine-tuning. The Llama 3.1 multilingual LLMs are a set of pre-trained and instruction-tuned generation models in 8B, 70B, and 405B sizes (text in/text out). The instruction-tuned text models are optimized for multilingual dialogue and outperform many available open chat models on common industry benchmarks. Llama 3.1 is designed for commercial and research use across languages. Instruction-tuned models are suited for assistant-style chat, while pretrained models fit broader natural language generation tasks. Llama 3.1 outputs can also be used to improve other models, including synthetic data generation and refinement. Llama 3.1 is an autoregressive Transformer model with an optimized architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF) to align with human preferences for helpfulness and safety.",
  "meta.llama3-1-70b-instruct-v1:0.description": "An updated Meta Llama 3.1 70B Instruct with an extended 128K context window, multilingual support, and improved reasoning. The Llama 3.1 multilingual LLMs are a set of pre-trained and instruction-tuned generation models in 8B, 70B, and 405B sizes (text in/text out). The instruction-tuned text models are optimized for multilingual dialogue and outperform many available open chat models on common industry benchmarks. Llama 3.1 is designed for commercial and research use across languages. Instruction-tuned models are suited for assistant-style chat, while pretrained models fit broader natural language generation tasks. Llama 3.1 outputs can also be used to improve other models, including synthetic data generation and refinement. Llama 3.1 is an autoregressive Transformer model with an optimized architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF) to align with human preferences for helpfulness and safety.",
  "meta.llama3-1-8b-instruct-v1:0.description": "An updated Meta Llama 3.1 8B Instruct with a 128K context window, multilingual support, and improved reasoning. The Llama 3.1 family includes 8B, 70B, and 405B instruction-tuned text models optimized for multilingual chat and strong benchmark performance. It is designed for commercial and research use across languages; instruction-tuned models suit assistant-style chat, while pretrained models fit broader generation tasks. Llama 3.1 outputs can also be used to improve other models (e.g., synthetic data and refinement). It is an autoregressive Transformer model, with SFT and RLHF to align for helpfulness and safety.",
  "meta.llama3-70b-instruct-v1:0.description": "Meta Llama 3 is an open LLM for developers, researchers, and enterprises, designed to help them build, experiment, and responsibly scale generative AI ideas. As part of the foundation for global community innovation, it is well suited for content creation, conversational AI, language understanding, R&D, and enterprise applications.",
  "meta.llama3-8b-instruct-v1:0.description": "Meta Llama 3 is an open LLM for developers, researchers, and enterprises, designed to help them build, experiment, and responsibly scale generative AI ideas. As part of the foundation for global community innovation, it is well suited to limited compute and resources, edge devices, and faster training times.",
  "meta/Llama-3.2-11B-Vision-Instruct.description": "Strong image reasoning on high-resolution images, suited for visual understanding apps.",
  "meta/Llama-3.2-90B-Vision-Instruct.description": "Advanced image reasoning for visual-understanding agent applications.",
  "meta/Llama-3.3-70B-Instruct.description": "Llama 3.3 is the most advanced multilingual open-source Llama model, delivering near-405B performance at very low cost. It is Transformer-based and improved with SFT and RLHF for usefulness and safety. The instruction-tuned version is optimized for multilingual chat and beats many open and closed chat models on industry benchmarks. Knowledge cutoff: Dec 2023.",
  "meta/Meta-Llama-3-70B-Instruct.description": "A powerful 70B-parameter model that excels at reasoning, coding, and broad language tasks.",
  "meta/Meta-Llama-3-8B-Instruct.description": "A versatile 8B-parameter model optimized for chat and text generation.",
  "meta/Meta-Llama-3.1-405B-Instruct.description": "Llama 3.1 instruction-tuned text model optimized for multilingual chat, performing strongly on common industry benchmarks among open and closed chat models.",
  "meta/Meta-Llama-3.1-70B-Instruct.description": "Llama 3.1 instruction-tuned text model optimized for multilingual chat, performing strongly on common industry benchmarks among open and closed chat models.",
  "meta/Meta-Llama-3.1-8B-Instruct.description": "Llama 3.1 instruction-tuned text model optimized for multilingual chat, performing strongly on common industry benchmarks among open and closed chat models.",
  "meta/llama-3.1-70b-instruct.description": "Built for complex dialogue with excellent context understanding, reasoning, and text generation.",
  "meta/llama-3.1-70b.description": "An updated Meta Llama 3 70B Instruct with 128K context, multilingual support, and improved reasoning.",
  "meta/llama-3.1-8b-instruct.description": "A cutting-edge model with strong language understanding, reasoning, and text generation.",
  "meta/llama-3.1-8b.description": "Llama 3.1 8B supports a 128K context window, ideal for real-time chat and data analysis, and offers significant cost savings versus larger models. Served by Groq on LPU hardware for fast, efficient inference.",
  "meta/llama-3.2-11b-vision-instruct.description": "A frontier vision-language model that excels at high-quality reasoning from images.",
  "meta/llama-3.2-11b.description": "An instruction-tuned image reasoning model (text+image input, text output) optimized for visual recognition, image reasoning, captioning, and general image QA.",
  "meta/llama-3.2-1b.description": "Text-only model for on-device use cases like multilingual local retrieval, summarization, and rewriting.",
  "meta/llama-3.2-3b.description": "Text-only model fine-tuned for on-device use cases like multilingual local retrieval, summarization, and rewriting.",
  "meta/llama-3.2-90b-vision-instruct.description": "A frontier vision-language model that excels at high-quality reasoning from images.",
  "meta/llama-3.2-90b.description": "An instruction-tuned image reasoning model (text+image input, text output) optimized for visual recognition, image reasoning, captioning, and general image QA.",
  "meta/llama-3.3-70b-instruct.description": "An advanced LLM strong at reasoning, math, common sense, and function calling.",
  "meta/llama-3.3-70b.description": "A perfect balance of performance and efficiency. Built for high-performance conversational AI in content creation, enterprise apps, and research, with strong language understanding for summarization, classification, sentiment, and code generation.",
  "meta/llama-4-maverick.description": "The Llama 4 family is a native multimodal AI model set supporting text and multimodal experiences, using MoE for leading text and image understanding. Llama 4 Maverick is a 17B model with 128 experts, served by DeepInfra.",
  "meta/llama-4-scout.description": "The Llama 4 family is a native multimodal AI model set supporting text and multimodal experiences, using MoE for leading text and image understanding. Llama 4 Scout is a 17B model with 16 experts, served by DeepInfra.",
  "microsoft/Phi-3-medium-128k-instruct.description": "The same Phi-3-medium model with a larger context window for RAG or few-shot prompts.",
  "microsoft/Phi-3-medium-4k-instruct.description": "A 14B-parameter model with higher quality than Phi-3-mini, focused on high-quality, reasoning-intensive data.",
  "microsoft/Phi-3-mini-128k-instruct.description": "The same Phi-3-mini model with a larger context window for RAG or few-shot prompts.",
  "microsoft/Phi-3-mini-4k-instruct.description": "The smallest Phi-3 family member, optimized for quality and low latency.",
  "microsoft/Phi-3-small-128k-instruct.description": "The same Phi-3-small model with a larger context window for RAG or few-shot prompts.",
  "microsoft/Phi-3-small-8k-instruct.description": "A 7B-parameter model with higher quality than Phi-3-mini, focused on high-quality, reasoning-intensive data.",
  "microsoft/Phi-3.5-mini-instruct.description": "An updated version of the Phi-3-mini model.",
  "microsoft/Phi-3.5-vision-instruct.description": "An updated version of the Phi-3-vision model.",
  "microsoft/WizardLM-2-8x22B.description": "WizardLM 2 is a language model from Microsoft AI that excels at complex dialogue, multilingual tasks, reasoning, and assistants.",
  "microsoft/wizardlm-2-8x22b.description": "WizardLM-2 8x22B is Microsoft AI’s most advanced Wizard model with highly competitive performance.",
  "mimo-v2-flash.description": "MiMo-V2-Flash is now officially open source! This is a MoE (Mixture-of-Experts) model purpose-built for extreme inference efficiency, with 309B total parameters (15B activated). Through innovations in a hybrid attention architecture and multi-layer MTP inference acceleration, it ranks among the global Top 2 open-source models across multiple agent benchmarking suites. Its coding capabilities surpass all open-source models and rival leading closed-source models such as Claude 4.5 Sonnet, while incurring only 2.5% of the inference cost and delivering 2× faster generation speed—pushing large-model inference efficiency to the limit.",
  "mimo-v2-pro.description": "MiMo-V2-Pro is Xiaomi’s flagship base model for complex reasoning, long-document processing, and agent workflows. It uses a trillion-parameter MoE architecture with 32B active parameters, supports a 256K context window, and is optimized for Claude-compatible APIs, coding, and multi-step planning.",
  "mimo-v2.5-pro.description": "MiMo-V2.5-Pro is Xiaomi's most capable flagship model to date, delivering significant improvements in general agentic capabilities, complex software engineering, and long-horizon tasks. It retains the 1T total / 42B active hybrid-attention architecture with a 1M context window, and can sustain complex long-horizon tasks spanning more than a thousand tool calls. Performance on demanding agentic benchmarks (ClawEval, GDPVal, SWE-bench Pro) is comparable to Claude Opus 4.6.",
  "mimo-v2.5.description": "MiMo-V2.5 is a native omni-modal Agent foundation model that understands images, video, audio, and text in a unified architecture, with a 1M context window. It delivers Pro-level agentic performance at roughly half the inference cost of MiMo-V2.5-Pro, with improved multimodal perception over MiMo-V2-Omni. Its built-in agentic capabilities (browsing, understanding, reasoning, execution) and faster inference make it well-suited to latency-sensitive and multi-step agent frameworks such as OpenClaw.",
  "minicpm-v.description": "MiniCPM-V is OpenBMB’s next-generation multimodal model with excellent OCR and multimodal understanding for wide-ranging use cases.",
  "minimax-m2.1.description": "MiniMax-M2.1 is the latest version of the MiniMax series, optimized for multilingual programming and real-world complex tasks. As an AI-native model, MiniMax-M2.1 achieves significant improvements in model performance, agent framework support, and multi-scenario adaptation, aiming to help enterprises and individuals find AI-native work and lifestyle more quickly.",
  "minimax-m2.5-free.description": "MiniMax M2.5 Free — free tier coding model with full reasoning capabilities.",
  "minimax-m2.5.description": "MiniMax M2.5 — efficient coding model with strong reasoning abilities.",
  "minimax-m2.7.description": "MiniMax M2.7 — latest MiniMax coding model with improved reasoning and tool use.",
  "minimax-m2.description": "MiniMax M2 is an efficient large language model built specifically for coding and agent workflows.",
  "minimax-m3.description": "MiniMax M3 — latest MiniMax model with vision support, strong reasoning, and improved tool use.",
  "minimax/minimax-m2.1.description": "MiniMax-M2.1 is a lightweight, cutting-edge large language model optimized for coding, proxy workflows, and modern application development, providing cleaner, more concise output and faster perceptual response times.",
  "minimax/minimax-m2.description": "MiniMax-M2 is a high-value model that excels at coding and agent tasks for many engineering scenarios.",
  "ministral-3:14b.description": "Ministral 3 14B is the largest model in the Ministral 3 series, delivering state-of-the-art performance comparable to the larger Mistral Small 3.2 24B counterpart. Optimized for local deployment, it delivers high performance on various hardware including local setups.",
  "ministral-3:3b.description": "Ministral 3 3B is the smallest and most efficient model in the Ministral 3 series, offering strong language and vision capabilities in a compact package. Designed for edge deployment, it delivers high performance on various hardware including local setups.",
  "ministral-3:8b.description": "Ministral 3 8B is a powerful and efficient model in the Ministral 3 series, delivering top-tier text and vision capabilities. Built for edge deployment, it delivers high performance on various hardware including local setups.",
  "ministral-3b-latest.description": "Ministral 3B is Mistral’s top-tier edge model.",
  "ministral-8b-latest.description": "Ministral 8B is a highly cost-effective edge model from Mistral.",
  "mistral-ai/Mistral-Large-2411.description": "Mistral’s flagship model for complex tasks needing large-scale reasoning or specialization (synthetic text generation, code generation, RAG, or agents).",
  "mistral-ai/Mistral-Nemo.description": "Mistral Nemo is a cutting-edge LLM with state-of-the-art reasoning, world knowledge, and coding for its size.",
  "mistral-ai/mistral-small-2503.description": "Mistral Small is suitable for any language-based task requiring high efficiency and low latency.",
  "mistral-large-2411.description": "Mistral Large is the flagship model, strong in multilingual tasks, complex reasoning, and code generation—ideal for high-end applications.",
  "mistral-large-2512.description": "Mistral Large 3, is a state-of-the-art, open-weight, general-purpose multimodal model with a granular Mixture-of-Experts architecture. It features 41B active parameters and 675B total parameters.",
  "mistral-large-3:675b.description": "Mistral Large 3 is a state-of-the-art open-weight general-purpose multimodal model with a refined Mixture of Experts architecture. It has 41B active parameters and 675B total parameters.",
  "mistral-large-instruct.description": "Mistral-Large-Instruct-2407 is an advanced dense LLM with 123B parameters and state-of-the-art reasoning, knowledge, and coding.",
  "mistral-large-latest.description": "Mistral Large is the flagship model, excelling at multilingual tasks, complex reasoning, and code generation for high-end applications.",
  "mistral-large.description": "Mixtral Large is Mistral’s flagship model, combining code generation, math, and reasoning with a 128K context window.",
  "mistral-medium-2508.description": "Mistral Medium 3.1 delivers state-of-the-art performance at 8× lower cost and simplifies enterprise deployment.",
  "mistral-medium-3.5.description": "Mistral Medium 3.5 is a frontier-class multimodal model optimized for agentic and coding use cases, released as open weights under a Modified MIT license.",
  "mistral-nemo-instruct.description": "Mistral-Nemo-Instruct-2407 is the instruction-tuned version of Mistral-Nemo-Base-2407.",
  "mistral-nemo.description": "Mistral Nemo is a high-efficiency 12B model from Mistral AI and NVIDIA.",
  "mistral-small-2506.description": "Mistral Small is a cost-effective, fast, and reliable option for translation, summarization, and sentiment analysis.",
  "mistral-small-2603.description": "Mistral's powerful hybrid model unifying instruct, reasoning, and coding capabilities in a single model. 119B parameters with 6.5B active.",
  "mistral-small-latest.description": "Mistral Small is a cost-effective, fast, and reliable option for translation, summarization, and sentiment analysis.",
  "mistral-small.description": "Mistral Small is suitable for any language-based task requiring high efficiency and low latency.",
  "mistral.description": "Mistral is Mistral AI’s 7B model, suitable for varied language tasks.",
  "mistral/codestral-embed.description": "A code embedding model for embedding codebases and repositories to support coding assistants.",
  "mistral/codestral.description": "Mistral Codestral 25.01 is a state-of-the-art coding model optimized for low latency and high-frequency use. It supports 80+ languages and excels at FIM, code correction, and test generation.",
  "mistral/devstral-small.description": "Devstral is an agentic LLM for software engineering tasks, making it a strong choice for software engineering agents.",
  "mistral/magistral-medium.description": "Complex thinking supported by deep understanding with transparent reasoning you can follow and verify. It maintains high-fidelity reasoning across languages, even mid-task.",
  "mistral/magistral-small.description": "Complex thinking supported by deep understanding with transparent reasoning you can follow and verify. It maintains high-fidelity reasoning across languages, even mid-task.",
  "mistral/ministral-3b.description": "A compact, efficient model for on-device tasks like assistants and local analytics, delivering low-latency performance.",
  "mistral/ministral-8b.description": "A more powerful model with faster, memory-efficient inference, ideal for complex workflows and demanding edge applications.",
  "mistral/mistral-embed.description": "A general text embedding model for semantic search, similarity, clustering, and RAG workflows.",
  "mistral/mistral-large.description": "Mistral Large is ideal for complex tasks that require strong reasoning or specialization—synthetic text generation, code generation, RAG, or agents.",
  "mistral/mistral-small.description": "Mistral Small is ideal for simple, batchable tasks like classification, customer support, or text generation, delivering great performance at an affordable price.",
  "mistral/mixtral-8x22b-instruct.description": "8x22B Instruct model. 8x22B is an open MoE model served by Mistral.",
  "mistral/pixtral-12b.description": "A 12B model with image understanding and text.",
  "mistral/pixtral-large.description": "Pixtral Large is the second model in our multimodal family with frontier-level image understanding. It handles documents, charts, and natural images while retaining Mistral Large 2’s leading text understanding.",
  "mistralai/Mistral-7B-Instruct-v0.1.description": "Mistral (7B) Instruct is known for strong performance across many language tasks.",
  "mistralai/Mistral-7B-Instruct-v0.2.description": "Mistral (7B) Instruct v0.2 improves instruction handling and result accuracy.",
  "mistralai/Mistral-7B-Instruct-v0.3.description": "Mistral (7B) Instruct v0.3 offers efficient compute and strong language understanding for many use cases.",
  "mistralai/Mistral-7B-v0.1.description": "Mistral 7B is compact but high-performing, strong for batch processing and simple tasks like classification and text generation, with solid reasoning.",
  "mistralai/Mixtral-8x22B-Instruct-v0.1.description": "Mixtral-8x22B Instruct (141B) is a very large LLM for heavy workloads.",
  "mistralai/Mixtral-8x7B-Instruct-v0.1.description": "Mixtral-8x7B Instruct (46.7B) provides high capacity for large-scale data processing.",
  "mistralai/Mixtral-8x7B-v0.1.description": "Mixtral 8x7B is a sparse MoE model that boosts inference speed, suitable for multilingual and code generation tasks.",
  "mistralai/mistral-nemo.description": "Mistral Nemo is a 7.3B model with multilingual support and strong coding performance.",
  "mixtral-8x7b-32768.description": "Mixtral 8x7B provides fault-tolerant parallel compute for complex tasks.",
  "mixtral.description": "Mixtral is Mistral AI’s MoE model with open weights, supporting code generation and language understanding.",
  "mixtral:8x22b.description": "Mixtral is Mistral AI’s MoE model with open weights, supporting code generation and language understanding.",
  "moonshot-v1-128k-vision-preview.description": "Kimi vision models (including moonshot-v1-8k-vision-preview/moonshot-v1-32k-vision-preview/moonshot-v1-128k-vision-preview) can understand image content such as text, colors, and object shapes.",
  "moonshot-v1-128k.description": "Moonshot V1 128K provides ultra-long context for very long text generation, handling up to 128,000 tokens for research, academic, and large-document scenarios.",
  "moonshot-v1-32k-vision-preview.description": "Kimi vision models (including moonshot-v1-8k-vision-preview/moonshot-v1-32k-vision-preview/moonshot-v1-128k-vision-preview) can understand image content such as text, colors, and object shapes.",
  "moonshot-v1-32k.description": "Moonshot V1 32K supports 32,768 tokens for medium-length context, ideal for long documents and complex dialogues in content creation, reports, and chat systems.",
  "moonshot-v1-8k-vision-preview.description": "Kimi vision models (including moonshot-v1-8k-vision-preview/moonshot-v1-32k-vision-preview/moonshot-v1-128k-vision-preview) can understand image content such as text, colors, and object shapes.",
  "moonshot-v1-8k.description": "Moonshot V1 8K is optimized for short text generation with efficient performance, handling 8,192 tokens for short chats, notes, and quick content.",
  "moonshotai/kimi-k2-0711.description": "Kimi K2 0711 is the instruct variant in the Kimi series, suited for high-quality code and tool use.",
  "moonshotai/kimi-k2-0905.description": "Kimi K2 0905 is an update that expands context and reasoning performance with coding optimizations.",
  "moonshotai/kimi-k2-thinking-turbo.description": "Kimi K2 Thinking Turbo is a high-speed version of Kimi K2 Thinking, significantly lowering latency while retaining deep reasoning.",
  "moonshotai/kimi-k2-thinking.description": "Kimi K2 Thinking is Moonshot’s reasoning model optimized for deep reasoning tasks, with general agent capabilities.",
  "moonshotai/kimi-k2.description": "Kimi K2 is a large MoE model from Moonshot AI with 1T total parameters and 32B active per forward pass, optimized for agent capabilities including advanced tool use, reasoning, and code synthesis.",
  "morph/morph-v3-fast.description": "Morph provides a specialized model to apply code changes suggested by frontier models (e.g., Claude or GPT-4o) to your existing files at FAST 4500+ tokens/sec. It is the final step in an AI coding workflow and supports 16k input/output tokens.",
  "morph/morph-v3-large.description": "Morph provides a specialized model to apply code changes suggested by frontier models (e.g., Claude or GPT-4o) to your existing files at FAST 2500+ tokens/sec. It is the final step in an AI coding workflow and supports 16k input/output tokens.",
  "musesteamer-2.0-lite-i2v.description": "Compared to Turbo, it offers superior performance with excellent cost-effectiveness.",
  "musesteamer-2.0-pro-i2v.description": "Based on Turbo, supports 1080P dynamic video generation, offering higher visual quality and enhanced video expressiveness.",
  "musesteamer-2.0-turbo-i2v-audio.description": "Supports 5s and 10s 720P dynamic video generation with sound. Enables multi-person conversational audio-visual creation, with synchronized sound and visuals, cinematic-quality imagery, and master-level camera movements.",
  "musesteamer-2.0-turbo-i2v.description": "Supports 5-second 720P silent dynamic video generation, featuring cinematic-quality visuals, complex camera movements, and realistic character emotions and actions.",
  "musesteamer-air-i2v.description": "The Baidu MuseSteamer Air video generation model performs well in subject consistency, physical realism, camera movement effects, and generation speed. It supports 5-second 720P silent dynamic video generation, delivering cinematic-quality visuals, fast generation, and excellent cost-effectiveness.",
  "musesteamer-air-image.description": "musesteamer-air-image is an image-generation model developed by Baidu’s search team to deliver exceptional cost-performance. It can quickly generate clear, action-coherent images based on user prompts, turning user descriptions effortlessly into visuals.",
  "nemotron-3-super-free.description": "Nemotron 3 Super Free by Nvidia — free tier reasoning model with strong coding support.",
  "nousresearch/hermes-2-pro-llama-3-8b.description": "Hermes 2 Pro Llama 3 8B is an updated Nous Hermes 2 version with the latest internally developed datasets.",
  "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF.description": "Llama 3.1 Nemotron 70B is an NVIDIA-customized LLM to improve helpfulness. It performs strongly on Arena Hard, AlpacaEval 2 LC, and GPT-4-Turbo MT-Bench, ranking #1 on all three auto-alignment benchmarks as of Oct 1, 2024. It is trained from Llama-3.1-70B-Instruct using RLHF (REINFORCE), Llama-3.1-Nemotron-70B-Reward, and HelpSteer2-Preference prompts.",
  "nvidia/llama-3.1-nemotron-51b-instruct.description": "A distinctive language model delivering exceptional accuracy and efficiency.",
  "nvidia/llama-3.1-nemotron-70b-instruct.description": "Llama-3.1-Nemotron-70B-Instruct is a custom NVIDIA model designed to improve the helpfulness of LLM responses.",
  "o1-mini.description": "o1-mini is a fast, cost-effective reasoning model designed for coding, math, and science. It has 128K context and an October 2023 knowledge cutoff.",
  "o1-preview.description": "o1 is OpenAI’s new reasoning model for complex tasks requiring broad knowledge. It has 128K context and an October 2023 knowledge cutoff.",
  "o1-pro.description": "The o1 series is trained with reinforcement learning to think before answering and handle complex reasoning. o1-pro uses more compute for deeper thinking and consistently higher-quality answers.",
  "o1.description": "o1 is OpenAI’s new reasoning model with text+image input and text output, suited for complex tasks requiring broad knowledge. It has a 200K context window and an October 2023 knowledge cutoff.",
  "o3-2025-04-16.description": "o3 is OpenAI’s new reasoning model with text+image input and text output for complex tasks requiring broad knowledge.",
  "o3-deep-research.description": "o3-deep-research is our most advanced deep research model for complex multi-step tasks. It can search the web and access your data via MCP connectors.",
  "o3-mini.description": "o3-mini is our latest small reasoning model, delivering higher intelligence at the same cost and latency targets as o1-mini.",
  "o3-pro-2025-06-10.description": "o3 Pro is OpenAI’s new reasoning model with text+image input and text output for complex tasks requiring broad knowledge.",
  "o3-pro.description": "o3-pro uses more compute to think deeper and consistently deliver better answers; available only via the Responses API.",
  "o3.description": "o3 is a powerful all-round model that sets a new bar for math, science, programming, and visual reasoning. It excels at technical writing and instruction following and can analyze text, code, and images for multi-step problems.",
  "o4-mini-2025-04-16.description": "o4-mini is an OpenAI reasoning model with text+image input and text output, suited for complex tasks requiring broad knowledge, with a 200K context window.",
  "o4-mini-deep-research.description": "o4-mini-deep-research is a faster, more affordable deep research model for complex multi-step research. It can search the web and also access your data via MCP connectors.",
  "o4-mini.description": "o4-mini is the latest small o-series model, optimized for fast, effective reasoning with high efficiency in coding and vision tasks.",
  "open-codestral-mamba.description": "Codestral Mamba is a Mamba 2 language model focused on code generation, supporting advanced coding and reasoning tasks.",
  "open-mistral-7b.description": "Mistral 7B is compact but high-performing, strong for batch processing and simple tasks like classification and text generation, with solid reasoning.",
  "open-mistral-nemo.description": "Mistral Nemo is a 12B model co-developed with Nvidia, offering strong reasoning and coding performance with easy integration.",
  "open-mixtral-8x22b.description": "Mixtral 8x22B is a larger MoE model for complex tasks, offering strong reasoning and higher throughput.",
  "open-mixtral-8x7b.description": "Mixtral 8x7B is a sparse MoE model that boosts inference speed, suitable for multilingual and code generation tasks.",
  "openai/gpt-3.5-turbo-instruct.description": "Similar capabilities to GPT-3-era models, compatible with legacy completion endpoints rather than chat.",
  "openai/gpt-3.5-turbo.description": "OpenAI’s most capable and cost-effective GPT-3.5 model, optimized for chat but still strong on classic completions.",
  "openai/gpt-4-turbo.description": "OpenAI’s gpt-4-turbo has broad general knowledge and domain expertise, follows complex natural-language instructions, and solves difficult problems accurately. Knowledge cutoff is April 2023 with a 128k context window.",
  "openai/gpt-4.1-mini.description": "GPT-4.1 Mini offers lower latency and better value for mid-context workloads.",
  "openai/gpt-4.1-nano.description": "GPT-4.1 Nano is an ultra-low-cost, low-latency option for high-frequency short chats or classification.",
  "openai/gpt-4.1.description": "The GPT-4.1 series provides larger context windows and stronger engineering and reasoning capabilities.",
  "openai/gpt-4o-mini.description": "GPT-4o-mini is a fast, small GPT-4o variant for low-latency multimodal use.",
  "openai/gpt-4o.description": "The GPT-4o family is OpenAI’s Omni model with text + image input and text output.",
  "openai/gpt-5-chat.description": "GPT-5 Chat is a GPT-5 variant optimized for conversations with lower latency for better interactivity.",
  "openai/gpt-5-codex.description": "GPT-5-Codex is a GPT-5 variant further optimized for coding and large-scale code workflows.",
  "openai/gpt-5-mini.description": "GPT-5 Mini is a smaller GPT-5 variant for low-latency, low-cost scenarios.",
  "openai/gpt-5-nano.description": "GPT-5 Nano is the ultra-small variant for scenarios with strict cost and latency constraints.",
  "openai/gpt-5-pro.description": "GPT-5 Pro is OpenAI’s flagship model, providing stronger reasoning, code generation, and enterprise-grade features, with test-time routing and stricter safety policies.",
  "openai/gpt-5.1-chat.description": "GPT-5.1 Chat is the lightweight member of the GPT-5.1 family, optimized for low-latency conversations while retaining strong reasoning and instruction execution.",
  "openai/gpt-5.1-codex-mini.description": "GPT-5.1-Codex-Mini is a smaller, faster version of GPT-5.1-Codex, better for latency- and cost-sensitive coding scenarios.",
  "openai/gpt-5.1-codex.description": "GPT-5.1-Codex is a GPT-5.1 variant optimized for software engineering and coding workflows, suitable for large refactors, complex debugging, and long autonomous coding tasks.",
  "openai/gpt-5.1.description": "GPT-5.1 is the latest flagship in the GPT-5 series, with significant improvements over GPT-5 in general reasoning, instruction following, and conversational naturalness, suitable for broad tasks.",
  "openai/gpt-5.2-chat.description": "GPT-5.2 Chat is the ChatGPT variant for experiencing the newest conversation improvements.",
  "openai/gpt-5.2-pro.description": "GPT-5.2 Pro: a smarter, more precise GPT-5.2 variant (Responses API only), suited for harder problems and longer multi-turn reasoning.",
  "openai/gpt-5.2.description": "GPT-5.2 is a flagship model for coding and agentic workflows with stronger reasoning and long-context performance.",
  "openai/gpt-5.description": "GPT-5 is OpenAI’s high-performance model for a wide range of production and research tasks.",
  "openai/gpt-oss-120b.description": "A highly capable general-purpose LLM with strong, controllable reasoning.",
  "openai/gpt-oss-20b.description": "A compact, open-weights language model optimized for low latency and resource-constrained environments, including local and edge deployments.",
  "openai/o1-mini.description": "o1-mini is a fast, cost-effective reasoning model designed for coding, math, and science use cases. It has 128K context and an October 2023 knowledge cutoff.",
  "openai/o1-preview.description": "o1 is OpenAI’s new reasoning model for complex tasks requiring broad knowledge. It has 128K context and an October 2023 knowledge cutoff.",
  "openai/o1.description": "OpenAI o1 is a flagship reasoning model built for complex problems that require deep thinking, delivering strong reasoning and higher accuracy on multi-step tasks.",
  "openai/o3-mini-high.description": "o3-mini (high reasoning) delivers higher intelligence at the same cost and latency targets as o1-mini.",
  "openai/o3-mini.description": "o3-mini is OpenAI’s latest small reasoning model, delivering higher intelligence at the same cost and latency targets as o1-mini.",
  "openai/o3.description": "OpenAI o3 is the most powerful reasoning model, setting new SOTA in coding, math, science, and visual perception. It excels at complex, multi-faceted queries and is particularly strong at analyzing images, charts, and diagrams.",
  "openai/o4-mini-high.description": "o4-mini high reasoning tier, optimized for fast, efficient reasoning with strong coding and vision performance.",
  "openai/o4-mini.description": "OpenAI o4-mini is a small, efficient reasoning model for low-latency scenarios.",
  "openai/text-embedding-3-large.description": "OpenAI’s most capable embedding model for English and non-English tasks.",
  "openai/text-embedding-3-small.description": "OpenAI’s improved, higher-performance ada embedding model variant.",
  "openai/text-embedding-ada-002.description": "OpenAI’s legacy text embedding model.",
  "openrouter/auto.description": "Based on context length, topic, and complexity, your request is routed to Llama 3 70B Instruct, Claude 3.5 Sonnet (self-moderated), or GPT-4o.",
  "oswe-vscode-prime.description": "Raptor mini is a preview model optimized for code-related tasks.",
  "oswe-vscode-secondary.description": "Raptor mini is a preview model optimized for code-related tasks.",
  "paratera/deepseek-v3.2.description": "DeepSeek V3.2 is a model that strikes a balance between high computational efficiency and excellent reasoning and agent performance.",
  "perplexity/sonar-pro.description": "Perplexity’s flagship product with search grounding, supporting advanced queries and follow-ups.",
  "perplexity/sonar-reasoning-pro.description": "An advanced reasoning-focused model that outputs CoT with enhanced search, including multiple search queries per request.",
  "perplexity/sonar-reasoning.description": "A reasoning-focused model that outputs chain-of-thought (CoT) with detailed, search-grounded explanations.",
  "perplexity/sonar.description": "Perplexity’s lightweight product with search grounding, faster and cheaper than Sonar Pro.",
  "phi3.description": "Phi-3 is Microsoft’s lightweight open model for efficient integration and large-scale reasoning.",
  "phi3:14b.description": "Phi-3 is Microsoft’s lightweight open model for efficient integration and large-scale reasoning.",
  "pixtral-12b-2409.description": "Pixtral is strong at chart/image understanding, document QA, multimodal reasoning, and instruction following. It ingests images at native resolution/aspect ratio and handles any number of images within a 128K context window.",
  "pixtral-large-latest.description": "Pixtral Large is a 124B-parameter open multimodal model built on Mistral Large 2, the second in our multimodal family with frontier-level image understanding.",
  "pixverse/pixverse-c1-it2v.description": "C1 is a large-scale model for the film and television industry launched by PixVerse in late March 2026. Its it2v (image-to-video) capability not only provides prompt controllability similar to t2v (text-to-video), but also preserves the color, saturation, scenes, and character features of reference images with high fidelity. Compared to V6, it offers enhanced prompt interpretation, stronger creativity, and delivers fight choreography and visual effects (such as spells) closer to professional cinematic standards. The model supports up to 15-second video generation, includes music with direct video output, and supports multiple languages. It is particularly well-suited for short-duration shots such as single-person close-ups, monologues, freeze-frame or slow-motion sequences, and transitional establishing shots.",
  "pixverse/pixverse-c1-kf2v.description": "C1 is a large-scale model for the film and television industry launched by PixVerse in late March 2026. Its kf2v (keyframe-to-video) capability enables smooth and natural transitions between any two input images. The model supports up to 15-second video generation, includes music with direct video output, and supports multiple languages.",
  "pixverse/pixverse-c1-r2v.description": "C1 is a large-scale model for the film and television industry launched by PixVerse in late March 2026. Its r2v (reference-to-video) capability supports inputting 2–7 images, intelligently blending multiple subjects while retaining prompt controllability similar to t2v (text-to-video), as well as the consistency and creativity of it2v (image-to-video). It delivers fight choreography and visual effects (e.g., spells and action sequences) closer to professional cinematic standards. The model supports up to 15-second video generation, includes music with direct video output, and handles multiple languages. It is well-suited for complex scenes such as multi-character group shots, dialogues, and interactions, particularly in medium and wide shots. If a single multi-panel storyboard image is provided (supporting up to a 9-panel grid), it can generate a continuous multi-shot video sequence in one click.",
  "pixverse/pixverse-c1-t2v.description": "C1 is a large-scale model for the film and television industry launched by PixVerse in late March 2026. Its t2v (text-to-video) capability enables precise control over video generation through prompts, accurately reproducing various cinematic language techniques such as push, pull, pan, tilt, and tracking shots, with smooth camera movements and well-controlled perspective transitions. The model supports up to 15-second video generation, includes music with direct video output, and supports multiple languages.",
  "pixverse/pixverse-v5.6-it2v.description": "Upload any image to freely customize the story, pacing, and style, generating vivid and coherent videos. PixVerse V5.6 is a self-developed video generation large model by Aishi Technology, offering comprehensive upgrades in both text-to-video and image-to-video capabilities. The model significantly enhances image clarity, stability in complex motion, and audio-visual synchronization. Lip-sync accuracy and natural emotional expression are improved in multi-character dialogue scenes. Composition, lighting, and texture consistency are also optimized, further elevating overall generation quality. PixVerse V5.6 ranks in the top global tier on the Artificial Analysis text-to-video and image-to-video leaderboard.",
  "pixverse/pixverse-v5.6-kf2v.description": "Achieve seamless transitions between any two images, creating smoother and more natural scene changes with visually striking effects. PixVerse V5.6 is a self-developed video generation large model by Aishi Technology, offering comprehensive upgrades in both text-to-video and image-to-video capabilities. The model significantly improves image clarity, stability in complex motion, and audio-visual synchronization. Lip-sync accuracy and natural emotional expression are enhanced in multi-character dialogue scenes. Composition, lighting, and texture consistency are also optimized, further elevating overall generation quality. PixVerse V5.6 ranks in the top global tier on the Artificial Analysis text-to-video and image-to-video leaderboard.",
  "pixverse/pixverse-v5.6-r2v.description": "Input 2–7 images to intelligently merge different subjects while maintaining unified style and coordinated motion, easily building rich narrative scenes and enhancing content controllability and creative freedom. PixVerse V5.6 is a self-developed video generation large model by Aishi Technology, offering comprehensive upgrades in both text-to-video and image-to-video capabilities. The model significantly improves image clarity, stability in complex motion, and audio-visual synchronization. Lip-sync accuracy and natural emotional expression are enhanced in multi-character dialogue scenes. Composition, lighting, and texture consistency are also optimized, further elevating overall generation quality. PixVerse V5.6 ranks in the top global tier on the Artificial Analysis text-to-video and image-to-video leaderboard.",
  "pixverse/pixverse-v5.6-t2v.description": "Input a text description to generate high-quality videos with second-level speed and precise semantic alignment, supporting multiple styles. PixVerse V5.6 is a self-developed video generation large model by Aishi Technology, offering comprehensive upgrades in both text-to-video and image-to-video capabilities. The model significantly improves image clarity, stability in complex motion, and audio-visual synchronization. Lip-sync accuracy and natural emotional expression are enhanced in multi-character dialogue scenes. Composition, lighting, and texture consistency are also optimized, further raising overall generation quality. PixVerse V5.6 ranks in the top global tier on the Artificial Analysis text-to-video and image-to-video leaderboard.",
  "pixverse/pixverse-v6-it2v.description": "V6 is PixVerse’s new model launched at the end of March 2026. Its it2v (image-to-video) model ranks second globally. In addition to the prompt-control capabilities of t2v (text-to-video), it2v can accurately reproduce the colors, saturation, scenes, and character features of reference images, delivering stronger character emotions and high-speed motion performance. It supports up to 15-second videos, direct output of music and video, and multiple languages. Ideal for scenarios such as e-commerce product close-ups, advertising promos, and simulated C4D modeling to showcase product structures, with one-click direct output.",
  "pixverse/pixverse-v6-kf2v.description": "V6 is PixVerse’s new model launched at the end of March 2026. Its kf2v (keyframe-to-video) model can seamlessly connect any two images, producing smoother and more natural video transitions. It supports up to 15-second videos, direct output of music and video, and multiple languages.",
  "pixverse/pixverse-v6-t2v.description": "V6 is PixVerse’s new model launched at the end of March 2026. Its t2v (text-to-video) model allows precise control of video visuals through prompts, accurately reproducing various cinematic techniques. Camera movements such as push, pull, pan, tilt, tracking, and follow are smooth and natural, with precise and controllable perspective switching. It supports up to 15-second videos, direct output of music and video, and multiple languages.",
  "pro-128k.description": "Spark Pro 128K provides a very large context capacity, handling up to 128K context, ideal for long-form documents requiring full-text analysis and long-range coherence, with smooth logic and diverse citation support in complex discussions.",
  "pro-deepseek-r1.description": "Enterprise dedicated service model with bundled concurrency.",
  "pro-deepseek-v3.description": "Enterprise dedicated service model with bundled concurrency.",
  "qianfan-70b.description": "Qianfan 70B is a large Chinese model for high-quality generation and complex reasoning.",
  "qianfan-8b.description": "Qianfan 8B is a mid-size general model balancing cost and quality for text generation and QA.",
  "qianfan-agent-intent-32k.description": "Qianfan Agent Intent 32K targets intent recognition and agent orchestration with long context support.",
  "qianfan-agent-lite-8k.description": "Qianfan Agent Lite 8K is a lightweight agent model for low-cost multi-turn dialogue and workflows.",
  "qianfan-check-vl.description": "Qianfan Check VL is a multimodal content review model for image-text compliance and recognition tasks.",
  "qianfan-composition.description": "Qianfan Composition is a multimodal creation model for mixed image-text understanding and generation.",
  "qianfan-engcard-vl.description": "Qianfan EngCard VL is a multimodal recognition model focused on English scenarios.",
  "qianfan-multipicocr.description": "Qianfan MultiPicOCR is a multi-image OCR model for text detection and recognition across images.",
  "qianfan-qi-vl.description": "Qianfan QI VL is a multimodal QA model for accurate retrieval and QA in complex image-text scenarios.",
  "qianfan-singlepicocr.description": "Qianfan SinglePicOCR is a single-image OCR model with high-accuracy character recognition.",
  "qianfan-vl-70b.description": "Qianfan VL 70B is a large VLM for complex image-text understanding.",
  "qianfan-vl-8b.description": "Qianfan VL 8B is a lightweight VLM for daily image-text QA and analysis.",
  "qvq-72b-preview.description": "QVQ-72B-Preview is an experimental research model from Qwen focused on improving visual reasoning.",
  "qvq-max.description": "Qwen QVQ visual reasoning model supports vision input and chain-of-thought output, with stronger performance in math, coding, visual analysis, creative, and general tasks.",
  "qvq-plus.description": "Visual reasoning model with vision input and chain-of-thought output. The qvq-plus series follows qvq-max and offers faster reasoning with a better quality-cost balance.",
  "qwen-coder-plus.description": "Qwen code model.",
  "qwen-coder-turbo-latest.description": "Qwen code model.",
  "qwen-coder-turbo.description": "Qwen code model.",
  "qwen-flash.description": "Fastest and lowest-cost Qwen model, ideal for simple tasks.",
  "qwen-image-2.0-pro-2026-04-22.description": "The Qwen-Image-2.0 series full-version model integrates image generation and image editing into a unified capability. It supports more professional text rendering with up to 1k token instruction capacity, delivers more delicate and realistic visual textures, enables fine-grained depiction of realistic scenes, and demonstrates stronger semantic alignment with prompts. The full-version model provides the strongest text rendering capability and the highest level of realism within the 2.0 series.",
  "qwen-image-2.0-pro.description": "The Qwen-Image-2.0 series full-version model integrates image generation and image editing into a unified capability. It supports more professional text rendering with up to 1k token instruction capacity, delivers more delicate and realistic visual textures, enables fine-grained depiction of realistic scenes, and demonstrates stronger semantic alignment with prompts. The full-version model provides the strongest text rendering capability and the highest level of realism within the 2.0 series.",
  "qwen-image-2.0.description": "The Qwen-Image-2.0 series accelerated version model integrates image generation and image editing into a unified capability. It supports more professional text rendering with up to 1k token instruction capacity, provides more refined and realistic visual textures, enables fine-grained depiction of realistic scenes, and demonstrates stronger semantic adherence to prompts. The accelerated version effectively achieves the optimal balance between model quality and performance.",
  "qwen-image-edit-max.description": "Qwen Image Editing Model supports multi-image input and multi-image output, enabling precise in-image text editing, object addition, removal, or relocation, subject action modification, image style transfer, and enhanced visual detail.",
  "qwen-image-edit-plus.description": "Qwen Image Editing Model supports multi-image input and multi-image output, enabling precise in-image text editing, object addition, removal, or relocation, subject action modification, image style transfer, and enhanced visual detail.",
  "qwen-image-edit.description": "Qwen Image Edit is an image-to-image model that edits images based on input images and text prompts, enabling precise adjustments and creative transformations.",
  "qwen-image-max.description": "Qwen Image Generation Model (Max series) delivers enhanced realism and visual naturalness compared with the Plus series, effectively reducing AI-generated artifacts, and demonstrating outstanding performance in human appearance, texture details, and text rendering.",
  "qwen-image-plus.description": "It supports a wide range of artistic styles and is particularly proficient at rendering complex text within images, enabling integrated image–text layout design.",
  "qwen-image.description": "Qwen-Image is a general image generation model supporting multiple art styles and strong complex text rendering, especially Chinese and English. It supports multi-line layouts, paragraph-level text, and fine detail for complex text-image layouts.",
  "qwen-long.description": "Ultra-large Qwen model with long context and chat across long- and multi-document scenarios.",
  "qwen-math-plus-latest.description": "Qwen Math is a language model specialized for solving math problems.",
  "qwen-math-plus.description": "Qwen Math is a language model specialized for solving math problems.",
  "qwen-math-turbo-latest.description": "Qwen Math is a language model specialized for solving math problems.",
  "qwen-math-turbo.description": "Qwen Math is a language model specialized for solving math problems.",
  "qwen-max.description": "Hundred-billion-scale ultra-large Qwen model supporting Chinese, English, and other languages; the API model behind current Qwen2.5 products.",
  "qwen-omni-turbo.description": "Qwen-Omni models support multimodal inputs (video, audio, images, text) and output audio and text.",
  "qwen-plus.description": "Enhanced ultra-large Qwen model supporting Chinese, English, and other languages.",
  "qwen-turbo.description": "Qwen Turbo will no longer be updated; replace it with Qwen Flash. Ultra-large Qwen model supporting Chinese, English, and other languages.",
  "qwen-vl-chat-v1.description": "Qwen VL supports flexible interactions including multi-image input, multi-turn QA, and creative tasks.",
  "qwen-vl-max-latest.description": "Ultra-large Qwen vision-language model. Compared to the enhanced version, it further improves visual reasoning and instruction following for stronger perception and cognition.",
  "qwen-vl-max.description": "Ultra-large Qwen vision-language model. Compared to the enhanced version, it further improves visual reasoning and instruction following for stronger visual perception and cognition.",
  "qwen-vl-ocr.description": "Qwen OCR is a text extraction model for documents, tables, exam images, and handwriting. It supports Chinese, English, French, Japanese, Korean, German, Russian, Italian, Vietnamese, and Arabic.",
  "qwen-vl-plus-latest.description": "Enhanced large-scale Qwen vision-language model with major gains in detail and text recognition, supporting over one-megapixel resolution and arbitrary aspect ratios.",
  "qwen-vl-plus.description": "Enhanced large-scale Qwen vision-language model with major gains in detail and text recognition, supporting over one-megapixel resolution and arbitrary aspect ratios.",
  "qwen-vl-v1.description": "Pretrained model initialized from Qwen-7B with an added vision module and 448 image resolution input.",
  "qwen/qwen-2-7b-instruct.description": "Qwen2 is the new Qwen LLM series. Qwen2 7B is a transformer-based model that excels in language understanding, multilingual capability, programming, math, and reasoning.",
  "qwen/qwen-2-vl-72b-instruct.description": "Qwen2-VL is the latest iteration of Qwen-VL, reaching state-of-the-art performance on vision benchmarks such as MathVista, DocVQA, RealWorldQA, and MTVQA. It can understand 20+ minutes of video for high-quality video Q&A, dialogue, and content creation. It also handles complex reasoning and decision-making, integrating with mobile devices and robots to act based on visual context and text instructions. Beyond English and Chinese, it also reads text in images across many languages, including most European languages, Japanese, Korean, Arabic, and Vietnamese.",
  "qwen/qwen-2.5-72b-instruct.description": "Qwen2.5-72B-Instruct is one of Alibaba Cloud’s latest LLM releases. The 72B model brings notable improvements in coding and math, supports over 29 languages (including Chinese and English), and significantly improves instruction following, structured data understanding, and structured output (especially JSON).",
  "qwen/qwen2.5-32b-instruct.description": "Qwen2.5-32B-Instruct is one of Alibaba Cloud’s latest LLM releases. The 32B model brings notable improvements in coding and math, supports over 29 languages (including Chinese and English), and significantly improves instruction following, structured data understanding, and structured output (especially JSON).",
  "qwen/qwen3-14b.description": "Qwen3-14B is the 14B variant for general reasoning and chat scenarios.",
  "qwen/qwen3-235b-a22b-2507.description": "Qwen3-235B-A22B-Instruct-2507 is the Instruct variant in the Qwen3 series, balancing multilingual instruction use with long-context scenarios.",
  "qwen/qwen3-235b-a22b-thinking-2507.description": "Qwen3-235B-A22B-Thinking-2507 is the Thinking variant of Qwen3, strengthened for complex math and reasoning tasks.",
  "qwen/qwen3-235b-a22b.description": "Qwen3-235B-A22B is a 235B-parameter MoE model from Qwen with 22B active per forward pass. It switches between a thinking mode for complex reasoning, math, and code and a non-thinking mode for efficient chat. It offers strong reasoning, multilingual support (100+ languages/dialects), advanced instruction following, and agent tool use. It natively handles 32K context and scales to 131K with YaRN.",
  "qwen/qwen3-30b-a3b.description": "Qwen3 is the latest Qwen LLM generation with dense and MoE architectures, excelling at reasoning, multilingual support, and advanced agent tasks. Its unique ability to switch between a thinking mode for complex reasoning and a non-thinking mode for efficient chat ensures versatile, high-quality performance.\n\nQwen3 significantly outperforms prior models like QwQ and Qwen2.5, delivering excellent math, coding, commonsense reasoning, creative writing, and interactive chat. The Qwen3-30B-A3B variant has 30.5B parameters (3.3B active), 48 layers, 128 experts (8 active per task), and supports up to 131K context with YaRN, setting a new bar for open models.",
  "qwen/qwen3-32b.description": "Qwen3-32B is a dense 32.8B-parameter causal LLM optimized for complex reasoning and efficient chat. It switches between a thinking mode for math, coding, and logic and a non-thinking mode for faster general chat. It performs strongly on instruction following, agent tool use, and creative writing across 100+ languages and dialects. It natively handles 32K context and scales to 131K with YaRN.",
  "qwen/qwen3-coder-plus.description": "Qwen3-Coder-Plus is a Qwen-series coding agent model optimized for more complex tool use and long-running sessions.",
  "qwen/qwen3-coder.description": "Qwen3-Coder is the Qwen3 code-generation family, strong at long-document code understanding and generation.",
  "qwen/qwen3-max-preview.description": "Qwen3 Max (preview) is the Max variant for advanced reasoning and tool integration.",
  "qwen/qwen3-max.description": "Qwen3 Max is the high-end reasoning model in the Qwen3 series for multilingual reasoning and tool integration.",
  "qwen/qwen3-vl-plus.description": "Qwen3 VL-Plus is the vision-enhanced Qwen3 variant with improved multimodal reasoning and video processing.",
  "qwen2.5-14b-instruct-1m.description": "Qwen2.5 open-source 72B model.",
  "qwen2.5-14b-instruct.description": "Qwen2.5 open-source 14B model.",
  "qwen2.5-32b-instruct.description": "Qwen2.5 open-source 32B model.",
  "qwen2.5-72b-instruct.description": "Qwen2.5 open-source 72B model.",
  "qwen2.5-7b-instruct.description": "Qwen2.5 open-source 7B model.",
  "qwen2.5-coder-1.5b-instruct.description": "Open-source Qwen code model.",
  "qwen2.5-coder-14b-instruct.description": "Open-source Qwen code model.",
  "qwen2.5-coder-32b-instruct.description": "Open-source Qwen code model.",
  "qwen2.5-coder-7b-instruct.description": "Open-source Qwen code model.",
  "qwen2.5-coder-instruct.description": "Qwen2.5-Coder is the latest code-focused LLM in the Qwen family (formerly CodeQwen).",
  "qwen2.5-instruct.description": "Qwen2.5 is the latest Qwen LLM series, with base and instruction-tuned models ranging from 0.5B to 72B parameters.",
  "qwen2.5-math-1.5b-instruct.description": "Qwen-Math delivers strong math problem-solving.",
  "qwen2.5-math-72b-instruct.description": "Qwen-Math delivers strong math problem-solving.",
  "qwen2.5-math-7b-instruct.description": "Qwen-Math delivers strong math problem-solving.",
  "qwen2.5-omni-7b.description": "Qwen-Omni models support multimodal inputs (video, audio, images, text) and output audio and text.",
  "qwen2.5-vl-32b-instruct.description": "Qwen2.5VL series model that reaches near Qwen2.5VL-72B performance on math and subject QA. Response style is tuned for human preference, especially for objective queries like math, logical reasoning, and knowledge QA, with clearer and more detailed outputs. This is the 32B version.",
  "qwen2.5-vl-72b-instruct.description": "Improved instruction following, math, problem solving, and coding, with stronger general object recognition. Supports precise visual element localization across formats, long video understanding (up to 10 minutes) with second-level event timing, temporal ordering and speed understanding, and agents that can control OS or mobile via parsing and localization. Strong key info extraction and JSON output. This is the 72B, strongest version in the series.",
  "qwen2.5-vl-7b-instruct.description": "Improved instruction following, math, problem solving, and coding, with stronger general object recognition. Supports precise visual element localization across formats, long video understanding (up to 10 minutes) with second-level event timing, temporal ordering and speed understanding, and agents that can control OS or mobile via parsing and localization. Strong key info extraction and JSON output. This is the 72B, strongest version in the series.",
  "qwen2.5-vl-instruct.description": "Qwen2.5-VL is the latest vision-language model in the Qwen family.",
  "qwen2.5.description": "Qwen2.5 is Alibaba’s next-generation large language model with strong performance across diverse use cases.",
  "qwen2.5:0.5b.description": "Qwen2.5 is Alibaba’s next-generation large language model with strong performance across diverse use cases.",
  "qwen2.5:1.5b.description": "Qwen2.5 is Alibaba’s next-generation large language model with strong performance across diverse use cases.",
  "qwen2.5:72b.description": "Qwen2.5 is Alibaba’s next-generation large language model with strong performance across diverse use cases.",
  "qwen2.description": "Qwen2 is Alibaba’s next-generation large language model with strong performance across diverse use cases.",
  "qwen2:0.5b.description": "Qwen2 is Alibaba’s next-generation large language model with strong performance across diverse use cases.",
  "qwen2:1.5b.description": "Qwen2 is Alibaba’s next-generation large language model with strong performance across diverse use cases.",
  "qwen2:72b.description": "Qwen2 is Alibaba’s next-generation large language model with strong performance across diverse use cases.",
  "qwen3-0.6b.description": "Qwen3 is a next-gen Tongyi Qwen model with major gains in reasoning, general ability, agent capabilities, and multilingual performance, and supports switching thinking modes.",
  "qwen3-1.7b.description": "Qwen3 is a next-gen Tongyi Qwen model with major gains in reasoning, general ability, agent capabilities, and multilingual performance, and supports switching thinking modes.",
  "qwen3-14b.description": "Qwen3 14B is a mid-size model for multilingual QA and text generation.",
  "qwen3-235b-a22b-instruct-2507.description": "Qwen3 235B A22B Instruct 2507 is a flagship instruct model for a wide range of generation and reasoning tasks.",
  "qwen3-235b-a22b-thinking-2507.description": "Qwen3 235B A22B Thinking 2507 is an ultra-large thinking model for hard reasoning.",
  "qwen3-235b-a22b.description": "Qwen3 is a next-gen Tongyi Qwen model with major gains in reasoning, general ability, agent capabilities, and multilingual performance, and supports switching thinking modes.",
  "qwen3-30b-a3b-instruct-2507.description": "Qwen3 30B A3B Instruct 2507 is a mid-large instruct model for high-quality generation and QA.",
  "qwen3-30b-a3b-thinking-2507.description": "Qwen3 30B A3B Thinking 2507 is a mid-large thinking model balancing accuracy and cost.",
  "qwen3-30b-a3b.description": "Qwen3 30B A3B is a mid-large general model balancing cost and quality.",
  "qwen3-32b.description": "Qwen3 32B is suited for general tasks requiring stronger understanding.",
  "qwen3-4b.description": "Qwen3 is a next-gen Tongyi Qwen model with major gains in reasoning, general ability, agent capabilities, and multilingual performance, and supports switching thinking modes.",
  "qwen3-8b.description": "Qwen3 8B is a lightweight model with flexible deployment for high-concurrency workloads.",
  "qwen3-coder-30b-a3b-instruct.description": "Open-source Qwen code model. The latest qwen3-coder-30b-a3b-instruct is based on Qwen3 and delivers strong coding-agent abilities, tool use, and environment interaction for autonomous programming, with excellent code performance and solid general capability.",
  "qwen3-coder-480b-a35b-instruct.description": "Qwen3 Coder 480B A35B Instruct is a flagship code model for multilingual programming and complex code understanding.",
  "qwen3-coder-flash.description": "Qwen code model. The latest Qwen3-Coder series is based on Qwen3 and delivers strong coding-agent abilities, tool use, and environment interaction for autonomous programming, with excellent code performance and solid general capability.",
  "qwen3-coder-next.description": "Next‑gen Qwen coder optimized for complex multi-file code generation, debugging, and high‑throughput agent workflows. Designed for strong tool integration and improved reasoning performance.",
  "qwen3-coder-plus.description": "Qwen code model. The latest Qwen3-Coder series is based on Qwen3 and delivers strong coding-agent abilities, tool use, and environment interaction for autonomous programming, with excellent code performance and solid general capability.",
  "qwen3-coder:480b.description": "Alibaba's high-performance long-context model for agent and coding tasks.",
  "qwen3-max-2026-01-23.description": "Qwen3 Max: Best-performing Qwen model for complex, multi-step coding tasks with thinking support.",
  "qwen3-max-preview.description": "Best-performing Qwen model for complex, multi-step tasks. The preview supports thinking.",
  "qwen3-max.description": "Qwen3 Max models deliver large gains over the 2.5 series in general ability, Chinese/English understanding, complex instruction following, subjective open tasks, multilingual ability, and tool use, with fewer hallucinations. The latest qwen3-max improves agentic programming and tool use over qwen3-max-preview. This release reaches field SOTA and targets more complex agent needs.",
  "qwen3-next-80b-a3b-instruct.description": "Next-gen Qwen3 non-thinking open-source model. Compared to the prior version (Qwen3-235B-A22B-Instruct-2507), it has better Chinese understanding, stronger logical reasoning, and improved text generation.",
  "qwen3-next-80b-a3b-thinking.description": "Qwen3 Next 80B A3B Thinking is a flagship reasoning model version for complex tasks.",
  "qwen3-omni-flash.description": "Qwen3-Omni-Flash is a multimodal large model built on a Thinker–Talker Mixture-of-Experts (MoE) architecture. It supports efficient understanding across text, images, audio, and video, along with speech generation capabilities. The model enables text-based interaction in 119 languages and voice interaction in 20 languages, producing human-like speech for precise cross-lingual communication. It features strong instruction-following capabilities and supports customizable system prompts, allowing flexible adaptation to different conversational styles and role settings. It is widely applicable in scenarios such as text creation, voice assistants, and multimedia analysis, delivering a natural and seamless multimodal interaction experience.",
  "qwen3-vl-235b-a22b-instruct.description": "Qwen3 VL 235B A22B Instruct is a flagship multimodal model for demanding understanding and creation.",
  "qwen3-vl-235b-a22b-thinking.description": "Qwen3 VL 235B A22B Thinking is the flagship thinking version for complex multimodal reasoning and planning.",
  "qwen3-vl-30b-a3b-instruct.description": "Qwen3 VL 30B A3B Instruct is a large multimodal model balancing accuracy and reasoning performance.",
  "qwen3-vl-30b-a3b-thinking.description": "Qwen3 VL 30B A3B Thinking is a deep-thinking version for complex multimodal tasks.",
  "qwen3-vl-32b-instruct.description": "Qwen3 VL 32B Instruct is a multimodal instruction-tuned model for high-quality image-text QA and creation.",
  "qwen3-vl-32b-thinking.description": "Qwen3 VL 32B Thinking is a deep-thinking multimodal version for complex reasoning and long-chain analysis.",
  "qwen3-vl-8b-instruct.description": "Qwen3 VL 8B Instruct is a lightweight multimodal model for daily visual QA and app integration.",
  "qwen3-vl-8b-thinking.description": "Qwen3 VL 8B Thinking is a multimodal chain-of-thought model for detailed visual reasoning.",
  "qwen3-vl-flash.description": "Qwen3 VL Flash: lightweight, high-speed reasoning version for latency-sensitive or high-volume requests.",
  "qwen3-vl-plus.description": "Qwen VL is a text generation model with vision understanding. It can do OCR and also summarize and reason, such as extracting attributes from product photos or solving problems from images.",
  "qwen3.5-122b-a10b.description": "Supports text, image, and video inputs. For text-only tasks, its performance is comparable to Qwen3 Max, offering higher efficiency and lower cost. In multimodal capabilities, it delivers significant improvements over the Qwen3 VL series.",
  "qwen3.5-27b.description": "Supports text, image, and video inputs. For text-only tasks, its performance is comparable to Qwen3 Max, offering higher efficiency and lower cost. In multimodal capabilities, it delivers significant improvements over the Qwen3 VL series.",
  "qwen3.5-35b-a3b.description": "Supports text, image, and video inputs. For text-only tasks, its performance is comparable to Qwen3 Max, offering higher efficiency and lower cost. In multimodal capabilities, it delivers significant improvements over the Qwen3 VL series.",
  "qwen3.5-397b-a17b.description": "Supports text, image, and video inputs. For text-only tasks, its performance is comparable to Qwen3 Max, offering higher efficiency and lower cost. In multimodal capabilities, it delivers significant improvements over the Qwen3 VL series.",
  "qwen3.5-flash.description": "The Qwen3.5 native vision-language Flash model is built on a hybrid architecture that combines a linear attention mechanism with a sparse Mixture-of-Experts (MoE) design, achieving higher inference efficiency. Compared to the 3 series, it delivers substantial improvements in both pure text and multimodal performance. It also offers fast response times, balancing inference speed and overall capability.",
  "qwen3.5-omni-flash.description": "Qwen3.5 Omni Flash is a fast, cost-effective full-modal Qwen model that supports text, image, and video input.",
  "qwen3.5-omni-plus.description": "Qwen3.5 Omni Plus supports text, image, and video input. It is the latest full-modal Qwen model for high-quality multimodal understanding and generation.",
  "qwen3.5-plus-2026-04-20.description": "Qwen 3.5 is a native vision-language Plus model. Compared to the February 15 snapshot, this version delivers substantial improvements in agentic coding capabilities and significantly faster inference speed. Its knowledge, reasoning, and long-context abilities remain at a high level, meeting the demands of complex agent tasks. It is well-suited for coding agents, production workflows, and high-throughput scenarios. This version corresponds to the April 20, 2026 snapshot.",
  "qwen3.5-plus.description": "Qwen3.5 Plus supports text, image, and video input. Its performance on pure text tasks is comparable to Qwen3 Max, with better performance and lower cost. Its multimodal capabilities are significantly improved compared to the Qwen3 VL series.",
  "qwen3.5:397b.description": "Qwen3.5 is a unified vision–language foundation model with a hybrid architecture (Mixture-of-Experts + linear attention), offering strong multimodal reasoning, coding, and long-context capabilities with a 256K context window.",
  "qwen3.6-27b.description": "Qwen3.6 27B is an open-source dense model with strong performance in reasoning, coding, and general capabilities. It supports thinking mode by default, offering balanced performance and efficiency.",
  "qwen3.6-35b-a3b.description": "The Qwen3.6 35B-A3B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse Mixture-of-Experts (MoE) design, achieving higher inference efficiency. Compared to the 3.5-35B-A3B model, it delivers significant improvements in agentic coding capabilities, mathematical reasoning, code reasoning, spatial intelligence, as well as object localization and target detection.",
  "qwen3.6-flash.description": "Qwen3.6 native vision-language Flash model delivers significantly improved performance compared to the 3.5-Flash version. This model focuses on enhancing agentic coding capabilities (substantially outperforming its predecessor across multiple code-agent benchmarks), as well as improving mathematical reasoning and code reasoning abilities. On the vision side, it shows notable gains in spatial intelligence, with particularly strong improvements in object localization and target detection.",
  "qwen3.6-max-preview.description": "The largest closed-source model in the Qwen3.6 series. It delivers stronger world knowledge, instruction following, and agentic coding performance for complex tasks. It is text-only, supports thinking mode by default, explicit caching, and function calling.",
  "qwen3.6-plus.description": "Qwen3.6 Plus supports text, image, and video input. It delivers a balanced performance across quality, speed, and cost. Its multimodal capabilities are significantly improved compared to the Qwen3 VL series.",
  "qwen3.7-max.description": "Qwen3.7 Max is the flagship omnipotent model of the AI agent era, offering comprehensive capabilities across text, image, and video understanding. It provides superior reasoning, function calling, and agent task execution performance.",
  "qwen3.7-plus.description": "Qwen3.7 Plus is a multimodal interactive hybrid agent model, building upon the Qwen3.7 series text capabilities to unify vision and language. It excels at GUI operation, visual coding, and complex agentic workflows.",
  "qwen3.description": "Qwen3 is Alibaba’s next-generation large language model with strong performance across diverse use cases.",
  "qwq-32b-preview.description": "QwQ is an experimental research model from Qwen focused on improved reasoning.",
  "qwq-32b.description": "QwQ is a reasoning model in the Qwen family. Compared with standard instruction-tuned models, it brings thinking and reasoning that significantly boost downstream performance, especially on complex problems. QwQ-32B is a mid-sized reasoning model that rivals top reasoning models like DeepSeek-R1 and o1-mini.",
  "qwq-plus.description": "QwQ reasoning model trained on Qwen2.5 uses RL to greatly improve reasoning. Core metrics in math/code (AIME 24/25, LiveCodeBench) and some general benchmarks (IFEval, LiveBench) reach the full DeepSeek-R1 level.",
  "qwq.description": "QwQ is a reasoning model in the Qwen family. Compared with standard instruction-tuned models, it brings thinking and reasoning abilities that significantly improve downstream performance, especially on hard problems. QwQ-32B is a mid-sized reasoning model that competes well with top reasoning models like DeepSeek-R1 and o1-mini.",
  "qwq_32b.description": "Mid-sized reasoning model in the Qwen family. Compared with standard instruction-tuned models, QwQ’s thinking and reasoning abilities significantly boost downstream performance, especially on hard problems.",
  "r1-1776.description": "R1-1776 is a post-trained variant of DeepSeek R1 designed to provide uncensored, unbiased factual information.",
  "seedance-1-5-pro-251215.description": "Seedance 1.5 Pro by ByteDance supports text-to-video, image-to-video (first frame, first+last frame), and audio generation synchronized with visuals.",
  "seedream-5-0-260128.description": "ByteDance-Seedream-5.0-lite by BytePlus features web-retrieval-augmented generation for real-time information, enhanced complex prompt interpretation, and improved reference consistency for professional visual creation.",
  "sensenova-6.7-flash-lite.description": "A lightweight multimodal agent model designed for real-world workflows, supporting both text-based conversations and image understanding. Lightweight and efficient, balancing performance, cost, and deployability. Native multimodal architecture with support for image understanding, including OCR and chart interpretation. Enhanced for office and productivity scenarios, with stable support for complex long-chain tasks. Improved token efficiency, enabling better cost control for complex workloads. Context length of 256K tokens (maximum input: 252K, maximum output: 64K)",
  "sensenova-u1-fast.description": "An accelerated version based on SenseNova U1, specifically optimized for infographic generation.",
  "solar-mini-ja.description": "Solar Mini (Ja) extends Solar Mini with a focus on Japanese while maintaining efficient, strong performance in English and Korean.",
  "solar-mini.description": "Solar Mini is a compact LLM that outperforms GPT-3.5, with strong multilingual capability supporting English and Korean, offering an efficient small-footprint solution.",
  "solar-pro.description": "Solar Pro is a high-intelligence LLM from Upstage, focused on instruction following on a single GPU, with IFEval scores above 80. It currently supports English; the full release was planned for November 2024 with expanded language support and longer context.",
  "sonar-deep-research.description": "Deep Research performs comprehensive expert-level research and synthesizes it into accessible, actionable reports.",
  "sonar-pro.description": "An advanced search product with search grounding for complex queries and follow-ups.",
  "sonar-reasoning-pro.description": "An advanced search product with search grounding for complex queries and follow-ups.",
  "sonar-reasoning.description": "An advanced search product with search grounding for complex queries and follow-ups.",
  "sonar.description": "A lightweight search-grounded product, faster and cheaper than Sonar Pro.",
  "sophnet/deepseek-v3.2.description": "DeepSeek V3.2 is a model that strikes a balance between high computational efficiency and excellent reasoning and agent performance.",
  "sora-2-pro.description": "Sora 2 Pro is our state-of-the-art, most advanced media generation model, generating videos with synced audio. It can create richly detailed, dynamic clips from natural language or images.",
  "sora-2.description": "Sora 2 is our new powerful media generation model, generating videos with synced audio. It can create richly detailed, dynamic clips from natural language or images.",
  "spark-x1.5.description": "X1.5 updates: (1) adds dynamic thinking mode controlled by the `thinking` field; (2) larger context length with 64K input and 64K output; (3) supports FunctionCall.",
  "spark-x2-flash.description": "Spark X2-Flash adopts an MoE (Mixture of Experts) architecture with 30 billion total parameters and supports up to a 256K context window. It claims significant improvements in agentic and coding capabilities, and was trained on a cluster of Ascend 910B AI processors.",
  "spark-x2.description": "X2 Capabilities Overview: 1. Introduces dynamic adjustment of reasoning mode, controlled via the `thinking` field. 2. Expanded context length: 64K input tokens and 128K output tokens. 3. Supports Function Call functionality.",
  "stable-diffusion-3-medium.description": "The latest text-to-image model from Stability AI. This version significantly improves image quality, text understanding, and style diversity, interpreting complex natural-language prompts more accurately and generating more precise, diverse images.",
  "stable-diffusion-3.5-large-turbo.description": "Stable Diffusion 3.5 Large Turbo focuses on high-quality image generation with strong detail rendering and scene fidelity.",
  "stable-diffusion-xl-base-1.0.description": "An open-source text-to-image model from Stability AI with industry-leading creative image generation. It has strong instruction understanding and supports reverse prompt definitions for precise generation.",
  "step-1-128k.description": "Balances performance and cost for general scenarios.",
  "step-1-256k.description": "Extra-long context handling, ideal for long-document analysis.",
  "step-1-32k.description": "Supports mid-length conversations for a wide range of scenarios.",
  "step-1-8k.description": "Small model suited for lightweight tasks.",
  "step-1-flash.description": "High-speed model suitable for real-time chat.",
  "step-1.5v-mini.description": "Strong video understanding capabilities.",
  "step-1o-turbo-vision.description": "Strong image understanding, outperforming 1o in math and coding. Smaller than 1o with faster output.",
  "step-1o-vision-32k.description": "Strong image understanding with better visual performance than the Step-1V series.",
  "step-1v-32k.description": "Supports vision inputs for richer multimodal interaction.",
  "step-1v-8k.description": "Small vision model for basic image-and-text tasks.",
  "step-1x-edit.description": "This model focuses on image editing, modifying and enhancing images based on user-provided images and text. It supports multiple input formats, including text descriptions and example images, and generates edits aligned with user intent.",
  "step-1x-medium.description": "This model offers strong image generation with text prompt input. With native Chinese support, it better understands Chinese descriptions, captures their semantics, and converts them into visual features for more accurate generation. It produces high-resolution, high-quality images and supports a degree of style transfer.",
  "step-2-16k-exp.description": "Experimental Step-2 build with the latest features and rolling updates. Not recommended for production.",
  "step-2-16k.description": "Supports large-context interactions for complex dialogues.",
  "step-2-mini.description": "Built on the next-generation in-house MFA attention architecture, delivering Step-1-like results at much lower cost while achieving higher throughput and faster latency. Handles general tasks with strong coding ability.",
  "step-2x-large.description": "A new-generation StepFun image model focused on image generation, producing high-quality images from text prompts. It delivers more realistic texture and stronger Chinese/English text rendering.",
  "step-3.5-flash-2603.description": "Built on Step 3.5 Flash and optimized for high-frequency agent scenarios, it further improves token efficiency and inference speed while retaining flagship-level reasoning and tool-calling capabilities. It also supports switching to a low-reasoning mode to reduce resource consumption. Additionally, targeted optimizations have been made to enhance compatibility with coding tasks and agent frameworks.",
  "step-3.5-flash.description": "Stepfun’s flagship language reasoning model.This model has top-notch reasoning capabilities and fast and reliable execution capabilities.Able to decompose and plan complex tasks, call tools quickly and reliably to perform tasks, and be competent in various complex tasks such as logical reasoning, mathematics, software engineering, and in-depth research.",
  "step-3.7-flash.description": "The flagship multimodal reasoning model from StepFun. Building on the high-speed reasoning and tool-calling capabilities of step-3.5-flash, it adds native multimodal input support, enabling direct understanding of images and video content without relying on visual MCPs or additional vision models. The model supports three reasoning levels (low / medium / high), making it a fast and reliable choice for agent workflows, coding tasks, and multimodal applications.",
  "step-3.description": "This model has strong visual perception and complex reasoning, accurately handling cross-domain knowledge understanding, math-vision cross analysis, and a wide range of everyday visual analysis tasks.",
  "step-image-edit-2.description": "A lightweight editing model from Stepfun’s latest iteration that supports both text-to-image generation and image editing within a single model. Despite having fewer than 6 billion parameters, it achieves state-of-the-art performance at its scale, rivaling open-source models in the 12B–20B parameter range across tiers. Each editing task takes only 1–2 seconds, redefining the experience of real-time interactive image editing.",
  "step-r1-v-mini.description": "A reasoning model with strong image understanding that can process images and text, then generate text after deep reasoning. It excels at visual reasoning and delivers top-tier math, coding, and text reasoning, with a 100K context window.",
  "stepfun-ai/Step-3.5-Flash.description": "Step 3.5 Flash is the most powerful open-source foundation model from StepFun, using sparse Mixture of Experts (MoE) architecture with 196B total parameters, only 11B active parameters per token. Model supports 256K context window, achieving 100-300 tok/s generation throughput through 3-way Multi-Token Prediction (MTP-3). Excellent performance on programming and Agent tasks, SWE-bench Verified reaches 74.4%.",
  "taichu4_vl_2b_nothinking.description": "The No-Thinking version of the Taichu4.0-VL 2B model features lower memory usage, a lightweight design, fast response speed, and strong multimodal understanding capabilities.",
  "taichu4_vl_32b.description": "The Thinking version of the Taichu4.0-VL 32B model is suited for complex multimodal understanding and reasoning tasks, demonstrating outstanding performance in multimodal mathematical reasoning, multimodal agent capabilities, and general image and visual comprehension.",
  "taichu4_vl_32b_nothinking.description": "The No-Thinking version of the Taichu4.0-VL 32B model is designed for complex image-and-text understanding and visual knowledge QA scenarios, excelling in image captioning, visual question answering, video comprehension, and visual localization tasks.",
  "taichu4_vl_3b.description": "The Thinking version of the Taichu4.0-VL 3B model efficiently performs multimodal understanding and reasoning tasks, with comprehensive upgrades in visual comprehension, visual localization, OCR recognition, and related capabilities.",
  "taichu_llm.description": "The Zidong Taichu large language model is a high-performance text-generation model developed using fully domestic full-stack technologies. Through structured compression of a hundred-billion-parameter base model and task-specific optimization, it significantly enhances complex text comprehension and knowledge reasoning capabilities. It excels in scenarios such as long-document analysis, cross-lingual information extraction, and knowledge-constrained generation.",
  "taichu_llm_14b.description": "The Zidong Taichu large language model is a high-performance text-generation model developed using fully domestic full-stack technologies. Through structured compression of a hundred-billion-parameter base model and task-specific optimization, it significantly enhances complex text comprehension and knowledge reasoning capabilities. It excels in scenarios such as long-document analysis, cross-lingual information extraction, and knowledge-constrained generation.",
  "taichu_llm_2b.description": "The Zidong Taichu large language model is a high-performance text-generation model developed using fully domestic full-stack technologies. Through structured compression of a hundred-billion-parameter base model and task-specific optimization, it significantly enhances complex text comprehension and knowledge reasoning capabilities. It excels in scenarios such as long-document analysis, cross-lingual information extraction, and knowledge-constrained generation.",
  "taichu_o1.description": "taichu_o1 is a next-generation reasoning large model that achieves human-like chain-of-thought through multimodal interaction and reinforcement learning. It supports complex decision-making simulations and, while maintaining high-precision output, reveals interpretable reasoning pathways. It is well-suited for strategy analysis, deep thinking, and similar scenarios.",
  "tencent/Hunyuan-A13B-Instruct.description": "Hunyuan-A13B-Instruct uses 80B total parameters with 13B active to match larger models. It supports fast/slow hybrid reasoning, stable long-text understanding, and leading agent ability on BFCL-v3 and τ-Bench. GQA and multi-quant formats enable efficient inference.",
  "tencent/Hunyuan-MT-7B.description": "Hunyuan Translation Model includes Hunyuan-MT-7B and the ensemble Hunyuan-MT-Chimera. Hunyuan-MT-7B is a 7B lightweight translation model supporting 33 languages plus 5 Chinese minority languages. In WMT25 it took 30 first-place results across 31 language pairs. Tencent Hunyuan uses a full training pipeline from pretraining to SFT to translation RL and ensemble RL, achieving leading performance at its size with efficient, easy deployment.",
  "text-embedding-3-large.description": "The most capable embedding model for English and non-English tasks.",
  "text-embedding-3-small.description": "An efficient, cost-effective next-generation embedding model for retrieval and RAG scenarios.",
  "thudm/glm-4-32b.description": "GLM-4-32B-0414 is a 32B bilingual (Chinese/English) open-weights model optimized for code generation, function calling, and agent tasks. It is pretrained on 15T high-quality and reasoning-heavy data and further refined with human preference alignment, rejection sampling, and RL. It excels at complex reasoning, artifact generation, and structured output, reaching GPT-4o and DeepSeek-V3-0324-level performance on multiple benchmarks.",
  "thudm/glm-4-9b-chat.description": "The open-source release of Zhipu AI’s latest GLM-4 pretraining model.",
  "togethercomputer/StripedHyena-Nous-7B.description": "StripedHyena Nous (7B) delivers enhanced compute efficiency through its architecture and strategy.",
  "tts-1-hd.description": "The latest text-to-speech model optimized for quality.",
  "tts-1.description": "The latest text-to-speech model optimized for real-time speed.",
  "upstage/SOLAR-10.7B-Instruct-v1.0.description": "Upstage SOLAR Instruct v1 (11B) is tuned for precise instruction tasks with strong language performance.",
  "us.anthropic.claude-3-5-sonnet-20241022-v2:0.description": "Claude 3.5 Sonnet raises the industry standard, outperforming competitors and Claude 3 Opus across broad evaluations while keeping mid-tier speed and cost.",
  "us.anthropic.claude-3-7-sonnet-20250219-v1:0.description": "Claude 3.7 Sonnet is Anthropic's fastest next-gen model. Compared to Claude 3 Haiku, it improves across skills and surpasses the previous flagship Claude 3 Opus on many intelligence benchmarks.",
  "v0-1.0-md.description": "v0-1.0-md is a legacy model served via the v0 API.",
  "v0-1.5-lg.description": "v0-1.5-lg is suited for advanced thinking or reasoning tasks.",
  "v0-1.5-md.description": "v0-1.5-md is suited for everyday tasks and UI generation.",
  "veo-2.0-generate-001.description": "Our state-of-the-art video generation model, available to developers on the paid tier of the Gemini API.",
  "veo-3.0-fast-generate-001.description": "Our stable video generation model, available to developers on the paid tier of the Gemini API.",
  "veo-3.0-generate-001.description": "Our stable video generation model, available to developers on the paid tier of the Gemini API.",
  "veo-3.1-fast-generate-preview.description": "Our latest video generation model, available to developers on the paid tier of the Gemini API.",
  "veo-3.1-generate-preview.description": "Our latest video generation model, available to developers on the paid tier of the Gemini API.",
  "vercel/v0-1.0-md.description": "Access the models behind v0 to generate, fix, and optimize modern web apps with framework-specific reasoning and up-to-date knowledge.",
  "vercel/v0-1.5-md.description": "Access the models behind v0 to generate, fix, and optimize modern web apps with framework-specific reasoning and up-to-date knowledge.",
  "vidu/viduq2-pro_img2video.description": "Input an image and a text description to generate video. ViduQ2-Pro image-to-video is the world’s first “Everything Can Be Referenced” video model. It supports six reference dimensions—effects, expressions, textures, actions, characters, and scenes—enabling fully evolved video editing. Through controllable addition, deletion, and modification, it achieves fine-grained video editing, designed as a production-grade creation engine for animated series, short dramas, and film production.",
  "vidu/viduq2-pro_reference2video.description": "Input reference videos, images, and a text description to generate video. ViduQ2-Pro reference-to-video is the world’s first “Everything Can Be Referenced” video model. It supports six reference dimensions—effects, expressions, textures, actions, characters, and scenes—enabling fully evolved video editing. Through controllable addition, deletion, and modification, it achieves fine-grained video editing, designed as a production-grade creation engine for animated series, short dramas, and film production.",
  "vidu/viduq2-pro_start-end2video.description": "Input the first and last frame images along with a text description to generate video. ViduQ2-Pro keyframe-to-video is the world’s first “Everything Can Be Referenced” video model. It supports six reference dimensions—effects, expressions, textures, actions, characters, and scenes—enabling fully evolved video editing. Through controllable addition, deletion, and modification, it achieves fine-grained video editing, designed as a production-grade creation engine for animated series, short dramas, and film production.",
  "vidu/viduq2-turbo_img2video.description": "Input an image and a text description to generate video. ViduQ2-Turbo image-to-video is an ultra-fast generation engine. A 5-second 720P video can be generated in as little as 19 seconds, and a 5-second 1080P video in about 27 seconds. Character actions and expressions are natural and realistic, delivering strong authenticity and excellent performance in high-dynamic scenes such as action sequences, with wide-ranging motion.",
  "vidu/viduq2-turbo_start-end2video.description": "Input the first and last frame images along with a text description to generate video. ViduQ2-Turbo keyframe-to-video is an ultra-fast generation engine. A 5-second 720P video can be produced in as little as 19 seconds, and a 5-second 1080P video in about 27 seconds. Character actions and expressions are natural and realistic, with strong authenticity, excelling in high-dynamic scenes such as action sequences, and supporting wide-ranging motion.",
  "vidu/viduq2_reference2video.description": "Input reference images along with a text description to generate video. ViduQ2 reference-to-video is a model designed for precise instruction adherence and nuanced emotion capture. It offers outstanding narrative control, accurately interpreting and expressing micro-expression changes; features rich cinematic language, smooth camera movements, and strong visual tension. Widely applicable to film and animation, advertising and e-commerce, short dramas, and cultural tourism industries.",
  "vidu/viduq2_text2video.description": "Enter a text prompt to generate video. ViduQ2 text-to-video is a model designed for precise instruction adherence and nuanced emotion capture. It offers outstanding narrative control, accurately interpreting and expressing micro-expression changes; features rich cinematic language, smooth camera movements, and strong visual tension. Widely applicable to film and animation, advertising and e-commerce, short dramas, and cultural tourism industries.",
  "vidu/viduq3-pro_img2video.description": "Input an image and a text description to generate video. ViduQ3-Pro image-to-video is a flagship-level audio-visual native model. It supports up to 16 seconds of synchronized audio-visual generation, enabling free multi-shot switching while precisely controlling pacing, emotion, and narrative continuity. With a leading parameter scale, it delivers exceptional image quality, character consistency, and emotional expression, meeting cinematic standards. Ideal for professional production scenarios such as advertising (e-commerce, TVC, performance campaigns), animated series, live-action drama, and games.",
  "vidu/viduq3-pro_start-end2video.description": "Input the first and last frame images along with a text description to generate video. ViduQ3-Pro keyframe-to-video is a flagship-level audio-visual native model. It supports up to 16 seconds of synchronized audio-visual generation, enabling free multi-shot switching while precisely controlling pacing, emotion, and narrative continuity. With a leading parameter scale, it delivers exceptional image quality, character consistency, and emotional expression, meeting cinematic standards. Ideal for professional production scenarios such as advertising (e-commerce, TVC, performance campaigns), animated series, live-action drama, and games.",
  "vidu/viduq3-pro_text2video.description": "Enter a text prompt to generate video. ViduQ3-Pro text-to-video is a flagship-level audio-visual native model. Supports up to 16 seconds of synchronized audio-visual generation, allowing free multi-shot switching while precisely controlling pacing, emotion, and narrative continuity. With a leading parameter scale, it delivers exceptional image quality, character consistency, and emotional expression, meeting cinematic standards. Ideal for professional production scenarios such as advertising (e-commerce, TVC, performance campaigns), animated series, live-action drama, and games.",
  "vidu/viduq3-turbo_img2video.description": "Input an image and a text description to generate video. ViduQ3-Turbo image-to-video is a high-performance accelerated model. It offers extremely fast generation while maintaining high-quality visuals and dynamic expression, excelling in action scenes, emotional rendering, and semantic understanding. Cost-effective and ideal for casual entertainment scenarios such as social media images, AI companions, and special effects assets.",
  "vidu/viduq3-turbo_start-end2video.description": "Input the first and last frame images along with a text description to generate video. ViduQ3-Turbo keyframe-to-video is a high-performance accelerated model. It delivers extremely fast generation while maintaining high-quality visuals and dynamic expression, excelling in action scenes, emotional rendering, and semantic understanding. Cost-effective and ideal for casual entertainment scenarios such as social media images, AI companions, and special effects assets.",
  "vidu/viduq3-turbo_text2video.description": "Enter a text prompt to generate video. ViduQ3-Turbo text-to-video is a high-performance accelerated model. It offers extremely fast generation while maintaining high-quality visuals and dynamic expression, excelling in action scenes, emotional rendering, and semantic understanding. Cost-effective and well-suited for casual entertainment scenarios such as social media images, AI companions, and special effects assets.",
  "vidu2-image.description": "Vidu 2 is a video generation foundation model designed to balance speed and quality. It focuses on image-to-video generation and start–end frame control, supporting 4-second videos at 720P resolution. The generation speed is significantly improved while costs are substantially reduced. Image-to-video generation fixes previous color shift issues, delivering stable and controllable visuals suitable for e-commerce and similar applications. In addition, semantic understanding of start and end frames and consistency across multiple reference images have been enhanced, making it an efficient tool for large-scale content production in general entertainment, internet media, animated short dramas, and advertising.",
  "vidu2-reference.description": "Vidu 2 is a video generation foundation model designed to balance speed and quality. It focuses on image-to-video generation and start–end frame control, supporting 4-second videos at 720P resolution. The generation speed is significantly improved while costs are substantially reduced. Image-to-video generation fixes previous color shift issues, delivering stable and controllable visuals suitable for e-commerce and similar applications. In addition, semantic understanding of start and end frames and consistency across multiple reference images have been enhanced, making it an efficient tool for large-scale content production in general entertainment, internet media, animated short dramas, and advertising.",
  "vidu2-start-end.description": "Vidu 2 is a video generation foundation model designed to balance speed and quality. It focuses on image-to-video generation and start–end frame control, supporting 4-second videos at 720P resolution. The generation speed is significantly improved while costs are substantially reduced. Image-to-video generation fixes previous color shift issues, delivering stable and controllable visuals suitable for e-commerce and similar applications. In addition, semantic understanding of start and end frames and consistency across multiple reference images have been enhanced, making it an efficient tool for large-scale content production in general entertainment, internet media, animated short dramas, and advertising.",
  "viduq1-image.description": "Vidu Q1 is Vidu’s next-generation video generation foundation model, focused on high-quality video creation. It produces content with fixed specifications of 5 seconds, 24 FPS, and 1080P resolution. Through deep optimization of visual clarity, the overall image quality and texture are significantly improved, while issues such as hand deformation and frame jitter are greatly reduced. The realistic style closely approaches real-world scenes, and 2D animation styles are preserved with high fidelity. Transitions between start and end frames are smoother, making it well suited for high-demand creative scenarios such as film production, advertising, and animated short dramas.",
  "viduq1-start-end.description": "Vidu Q1 is Vidu’s next-generation video generation foundation model, focused on high-quality video creation. It produces content with fixed specifications of 5 seconds, 24 FPS, and 1080P resolution. Through deep optimization of visual clarity, the overall image quality and texture are significantly improved, while issues such as hand deformation and frame jitter are greatly reduced. The realistic style closely approaches real-world scenes, and 2D animation styles are preserved with high fidelity. Transitions between start and end frames are smoother, making it well suited for high-demand creative scenarios such as film production, advertising, and animated short dramas.",
  "viduq1-text.description": "Vidu Q1 is Vidu’s next-generation video generation foundation model, focused on high-quality video creation. It produces content with fixed specifications of 5 seconds, 24 FPS, and 1080P resolution. Through deep optimization of visual clarity, the overall image quality and texture are significantly improved, while issues such as hand deformation and frame jitter are greatly reduced. The realistic style closely approaches real-world scenes, and 2D animation styles are preserved with high fidelity. Transitions between start and end frames are smoother, making it well suited for high-demand creative scenarios such as film production, advertising, and animated short dramas.",
  "volcengine/doubao-seed-2-0-code.description": "Doubao-Seed-2.0-Code is optimized for enterprise-level programming needs. Built on the excellent Agent and VLM capabilities of Seed 2.0, it specially enhances coding abilities with outstanding frontend performance and targeted optimization for common enterprise multi-language coding requirements, making it ideal for integration with various AI programming tools.",
  "volcengine/doubao-seed-2-0-lite.description": "Balances generation quality and response speed, suitable as a general-purpose production-grade model",
  "volcengine/doubao-seed-2-0-mini.description": "Points to the latest version of doubao-seed-2-0-mini",
  "volcengine/doubao-seed-2-0-pro.description": "Points to the latest version of doubao-seed-2-0-pro",
  "volcengine/doubao-seed-code.description": "Doubao-Seed-Code is ByteDance Volcano Engine’s LLM optimized for agentic programming, performing strongly on programming and agent benchmarks with 256K context support.",
  "wan2.2-i2v-flash.description": "Wanxiang 2.2 Speed Edition delivers ultra-fast generation, with more accurate prompt understanding and camera control. It maintains consistency of visual elements while significantly improving overall stability and success rate.",
  "wan2.2-i2v-plus.description": "Wanxiang 2.2 Pro Edition offers more accurate prompt understanding and controllable camera movements. It maintains consistency of visual elements while significantly improving stability and success rate, and generates richer, more detailed content.",
  "wan2.2-kf2v-flash.description": "Wanxiang 2.2 Speed Edition",
  "wan2.2-kf2v-plus.description": "Wanxiang 2.2 Plus Edition",
  "wan2.2-t2i-flash.description": "Wanxiang 2.2 Flash is the latest model with upgrades in creativity, stability, and realism, delivering fast generation and high value.",
  "wan2.2-t2i-plus.description": "Wanxiang 2.2 Plus is the latest model with upgrades in creativity, stability, and realism, producing richer details.",
  "wan2.2-t2v-plus.description": "Wanxiang 2.2 Pro Edition provides more accurate prompt understanding, delivers stable and smooth motion generation, and produces richer, more detailed visuals.",
  "wan2.5-i2i-preview.description": "Wanxiang 2.5 I2I Preview supports single-image editing and multi-image fusion.",
  "wan2.5-i2v-preview.description": "Wanxiang 2.5 Preview supports automatic voiceover generation and the ability to incorporate custom audio files.",
  "wan2.5-t2i-preview.description": "Wanxiang 2.5 T2I supports flexible selection of image dimensions within total pixel area and aspect ratio constraints.",
  "wan2.5-t2v-preview.description": "Wanxiang 2.5 Preview supports automatic voiceover generation and the ability to incorporate custom audio files.",
  "wan2.6-i2v-flash.description": "Wanxiang 2.6 introduces multi-shot narrative capabilities, while also supporting automatic voiceover generation and the ability to incorporate custom audio files.",
  "wan2.6-i2v.description": "Wanxiang 2.6 introduces multi-shot narrative capabilities, while also supporting automatic voiceover generation and the ability to incorporate custom audio files.",
  "wan2.6-image.description": "Wanxiang 2.6 Image supports image editing and mixed image–text layout output.",
  "wan2.6-r2v-flash.description": "Wanxiang 2.6 Reference-to-Video – Flash offers faster generation and better cost performance. It supports referencing specific characters or any objects, accurately maintaining consistency in appearance and voice, and enables multi-character reference for co-performance.",
  "wan2.6-r2v.description": "Wanxiang 2.6 Reference-to-Video supports referencing specific characters or any objects, accurately maintaining consistency in appearance and voice, and enabling multi-character reference for co-performance. Note: When using videos as references, the input video will also be counted toward the cost. Please refer to the model pricing documentation for details.",
  "wan2.6-t2i.description": "Wanxiang 2.6 T2I supports flexible selection of image dimensions within total pixel area and aspect ratio constraints (same as Wanxiang 2.5).",
  "wan2.6-t2v.description": "Wanxiang 2.6 introduces multi-shot narrative capabilities, while also supporting automatic voiceover generation and the ability to incorporate custom audio files.",
  "wan2.7-i2v-2026-04-25.description": "Wanxiang 2.7 Image-to-Video delivers a comprehensive upgrade in performance capabilities. Dramatic scenes feature delicate and natural emotional expression, while action sequences are intense and impactful. Combined with more dynamic and rhythmically driven shot transitions, it achieves stronger overall performance and storytelling.",
  "wan2.7-i2v.description": "Wanxiang 2.7 Image-to-Video delivers a comprehensive upgrade in performance capabilities. Dramatic scenes feature delicate and natural emotional expression, while action sequences are intense and impactful. Combined with more dynamic and rhythmically driven shot transitions, it achieves stronger overall performance and storytelling.",
  "wan2.7-image-pro.description": "Wanxiang 2.7 Image Professional Edition, supports 4K high-definition output.",
  "wan2.7-image.description": "Wanxiang 2.7 Image, faster image generation speed.",
  "wan2.7-r2v.description": "Wanxiang 2.7 Reference-to-Video offers more stable references for characters, props, and scenes. It supports up to 5 mixed reference images or videos, along with audio tone referencing. Combined with upgraded core capabilities, it delivers stronger performance and expressive power.",
  "wan2.7-t2v-2026-04-25.description": "Wanxiang 2.7 Text-to-Video delivers a comprehensive upgrade in performance capabilities. Dramatic scenes feature delicate and natural emotional expression, while action sequences are intense and impactful. Enhanced with more dynamic and rhythmically driven shot transitions, it achieves stronger overall acting and storytelling performance.",
  "wan2.7-t2v.description": "Wanxiang 2.7 Text-to-Video delivers a comprehensive upgrade in performance capabilities. Dramatic scenes feature delicate and natural emotional expression, while action sequences are intense and impactful. Enhanced with more dynamic and rhythmically driven shot transitions, it achieves stronger overall acting and storytelling performance.",
  "wanx-v1.description": "Base text-to-image model. Corresponds to Tongyi Wanxiang 1.0 General.",
  "wanx2.0-t2i-turbo.description": "Excels at textured portraits with moderate speed and lower cost. Corresponds to Tongyi Wanxiang 2.0 Speed.",
  "wanx2.1-i2v-plus.description": "Wanxiang 2.1 Pro Edition delivers more visually refined and higher-quality imagery.",
  "wanx2.1-i2v-turbo.description": "Wanxiang 2.1 Speed Edition offers high cost-performance.",
  "wanx2.1-t2i-plus.description": "Fully upgraded version with richer image details and slightly slower speed. Corresponds to Tongyi Wanxiang 2.1 Pro.",
  "wanx2.1-t2i-turbo.description": "Fully upgraded version with fast generation, strong overall quality, and high value. Corresponds to Tongyi Wanxiang 2.1 Speed.",
  "wanx2.1-t2v-plus.description": "Wanxiang 2.1 Pro Edition delivers richer visual texture and higher-quality imagery.",
  "wanx2.1-t2v-turbo.description": "Wanxiang 2.1 Speed Edition offers excellent cost-performance.",
  "whisper-1.description": "A general speech recognition model supporting multilingual ASR, speech translation, and language identification.",
  "wizardlm2.description": "WizardLM 2 is a language model from Microsoft AI that excels at complex dialogue, multilingual tasks, reasoning, and assistants.",
  "wizardlm2:8x22b.description": "WizardLM 2 is a language model from Microsoft AI that excels at complex dialogue, multilingual tasks, reasoning, and assistants.",
  "x-ai/grok-4.1-fast-non-reasoning.description": "Grok 4 Fast (Non-Reasoning) is xAI’s high-throughput, low-cost multimodal model (supports a 2M context window) for scenarios sensitive to latency and cost that do not require in-model reasoning. It sits alongside the reasoning version of Grok 4 Fast, and reasoning can be enabled via the API reasoning parameter when needed. Prompts and completions may be used by xAI or OpenRouter to improve future models.",
  "x-ai/grok-4.1-fast.description": "Grok 4 Fast is xAI’s high-throughput, low-cost model (supports a 2M context window), ideal for high-concurrency and long-context use cases.",
  "xai/grok-2-vision.description": "Grok 2 Vision excels at visual tasks, delivering SOTA performance on visual math reasoning (MathVista) and document QA (DocVQA). It handles documents, charts, graphs, screenshots, and photos.",
  "xai/grok-2.description": "Grok 2 is a frontier model with state-of-the-art reasoning, strong chat, coding, and reasoning performance, and ranks above Claude 3.5 Sonnet and GPT-4 Turbo on LMSYS.",
  "xai/grok-3-fast.description": "xAI’s flagship model excels in enterprise use cases like data extraction, coding, and summarization, with deep domain knowledge in finance, healthcare, law, and science. The fast variant runs on quicker infrastructure for much faster responses at higher per-token cost.",
  "xai/grok-3-mini-fast.description": "xAI’s lightweight model that thinks before responding, ideal for simple or logic-based tasks without deep domain knowledge. Raw reasoning traces are available. The fast variant runs on quicker infrastructure for much faster responses at higher per-token cost.",
  "xai/grok-3-mini.description": "xAI’s lightweight model that thinks before responding, ideal for simple or logic-based tasks without deep domain knowledge. Raw reasoning traces are available.",
  "xai/grok-3.description": "xAI’s flagship model excels in enterprise use cases like data extraction, coding, and summarization, with deep domain knowledge in finance, healthcare, law, and science.",
  "xai/grok-4.description": "xAI’s newest flagship model with unparalleled performance in natural language, math, and reasoning—an ideal all-rounder.",
  "yi-large-fc.description": "Built on yi-large with enhanced tool-calling, suited for agent and workflow scenarios.",
  "yi-large-preview.description": "An early version; yi-large (newer) is recommended.",
  "yi-large-rag.description": "An advanced service based on yi-large, combining retrieval and generation for precise answers with real-time web search.",
  "yi-large-turbo.description": "Exceptional value and performance, tuned for a strong balance of quality, speed, and cost.",
  "yi-large.description": "A new 100B-parameter model with strong Q&A and text generation.",
  "yi-lightning-lite.description": "A lightweight version; yi-lightning is recommended.",
  "yi-lightning.description": "A latest high-performance model with faster inference and high-quality output.",
  "yi-medium-200k.description": "A 200K long-context model for deep long-form understanding and generation.",
  "yi-medium.description": "A tuned mid-size model with balanced capability and value, optimized for instruction following.",
  "yi-spark.description": "A compact, fast model with strengthened math and coding capabilities.",
  "yi-vision-v2.description": "A vision model for complex tasks with strong multi-image understanding and analysis.",
  "yi-vision.description": "A vision model for complex tasks with strong image understanding and analysis.",
  "youtu-vita.description": "VITA is a multimodal understanding model that supports analysis of video and image content. It can be used for tasks such as video structure parsing and image object detection.",
  "yt-video-2.0.description": "It generates highly temporally consistent videos from images, suitable for demanding applications such as advertising, film clips, and product showcase videos.",
  "z-ai/glm-4.5-air.description": "GLM 4.5 Air is a lightweight GLM 4.5 variant for cost-sensitive scenarios while retaining strong reasoning.",
  "z-ai/glm-4.5.description": "GLM 4.5 is Z.AI’s flagship model with hybrid reasoning optimized for engineering and long-context tasks.",
  "z-ai/glm-4.6.description": "GLM 4.6 is Z.AI's flagship model with extended context length and coding capability.",
  "z-ai/glm-4.7.description": "GLM-4.7 is Zhipu's latest flagship model, offering improved general capabilities, simpler and more natural replies, and a more immersive writing experience.",
  "z-image-turbo.description": "Z-Image is a lightweight text-to-image generation model that can rapidly produce images, supports both Chinese and English text rendering, and flexibly adapts to multiple resolutions and aspect ratios.",
  "zai-glm-4.7.description": "GLM-4.7 is Zhipu's new generation flagship model with 355B total parameters and 32B active parameters, fully upgraded in general dialogue, reasoning, and agent capabilities. GLM-4.7 enhances Interleaved Thinking and introduces Preserved Thinking and Turn-level Thinking.",
  "zai-org/GLM-4.5-Air.description": "GLM-4.5-Air is a base model for agent applications using a Mixture-of-Experts architecture. It is optimized for tool use, web browsing, software engineering, and frontend coding, and integrates with code agents like Claude Code and Roo Code. It uses hybrid reasoning to handle both complex reasoning and everyday scenarios.",
  "zai-org/GLM-4.5V.description": "GLM-4.5V is Zhipu AI’s latest VLM, built on the GLM-4.5-Air flagship text model (106B total, 12B active) with an MoE architecture for strong performance at lower cost. It follows the GLM-4.1V-Thinking path and adds 3D-RoPE to improve 3D spatial reasoning. Optimized through pretraining, SFT, and RL, it handles images, video, and long documents and ranks top among open models on 41 public multimodal benchmarks. A Thinking mode toggle lets users balance speed and depth.",
  "zai/glm-4.5-air.description": "GLM-4.5 and GLM-4.5-Air are our latest flagships for agent applications, both using MoE. GLM-4.5 has 355B total and 32B active per forward pass; GLM-4.5-Air is slimmer with 106B total and 12B active.",
  "zai/glm-4.5.description": "The GLM-4.5 series is designed for agents. The flagship GLM-4.5 combines reasoning, coding, and agent skills with 355B total params (32B active) and offers dual operation modes as a hybrid reasoning system.",
  "zai/glm-4.5v.description": "GLM-4.5V builds on GLM-4.5-Air, inheriting proven GLM-4.1V-Thinking techniques and scaling with a strong 106B-parameter MoE architecture.",
  "zenmux/auto.description": "ZenMux auto-routing selects the best-value, best-performing model from supported options based on your request."
}
