Qwen3-Max is an updated release built on the Qwen3 series, offering major improvements in reasoning, instruction following, multilingual support, and long-tail knowledge coverage compared to the January 2025 version. It...
Models
Every model in the catalog with source-linked pricing, context limits, provider availability, and published benchmark results.
Qwen3 Coder Plus is Alibaba's proprietary version of the Open Source Qwen3 Coder 480B A35B. It is a powerful coding agent model specializing in autonomous programming via tool calling and...
DeepSeek-V3.1 Terminus is an update to [DeepSeek V3.1](/deepseek/deepseek-chat-v3.1) that maintains the model's original capabilities while addressing issues reported by users, including language consistency and agent capabilities, further optimizing the model's...
Qwen3 Coder Flash is Alibaba's fast and cost efficient version of their proprietary Qwen3 Coder Plus. It is a powerful coding agent model specializing in autonomous programming via tool calling...
Qwen3-Next-80B-A3B-Thinking is a reasoning-first chat model in the Qwen3-Next line that outputs structured “thinking” traces by default. It’s designed for hard multi-step problems; math proofs, code synthesis/debugging, logic, and agentic...
Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model in the Qwen3-Next series optimized for fast, stable responses without “thinking” traces. It targets complex tasks across reasoning, code generation, knowledge QA, and multilingual...
Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model in the Qwen3-Next series optimized for fast, stable responses without “thinking” traces. It targets complex tasks across reasoning, code generation, knowledge QA, and multilingual...
Qwen Plus 0728, based on the Qwen3 foundation model, is a 1 million context hybrid reasoning model with a balanced performance, speed, and cost combination.
Qwen Plus 0728, based on the Qwen3 foundation model, is a 1 million context hybrid reasoning model with a balanced performance, speed, and cost combination.
NVIDIA-Nemotron-Nano-9B-v2 is a large language model (LLM) trained from scratch by NVIDIA, and designed as a unified model for both reasoning and non-reasoning tasks. It responds to user queries and...
Hermes 4 70B is a hybrid reasoning model from Nous Research, built on Meta-Llama-3.1-70B. It introduces the same hybrid mode as the larger 405B release, allowing the model to either...
Mistral Medium 3.1 is an updated version of Mistral Medium 3, which is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances...
Jamba Large 1.7 is the latest model in the Jamba open family, offering improvements in grounding, instruction-following, and overall efficiency. Built on a hybrid SSM-Transformer architecture with a 256K context...
GPT-5 Chat is designed for advanced, natural, multimodal, and context-aware conversations for enterprise applications.
gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized...
gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for...
Claude Opus 4.1 is an updated version of Anthropic’s flagship model, offering improved performance in coding, reasoning, and agentic tasks. It achieves 74.5% on SWE-bench Verified and shows notable gains...
Mistral's cutting-edge language model for coding released end of July 2025. Codestral specializes in low-latency, high-frequency tasks such as fill-in-the-middle (FIM), code correction and test generation. [Blog Post](https://mistral.ai/news/codestral-25-08)
Qwen3-Coder-30B-A3B-Instruct is a 30.5B parameter Mixture-of-Experts (MoE) model with 128 experts (8 active per forward pass), designed for advanced code generation, repository-scale understanding, and agentic tool use. Built on the...
Qwen3-30B-A3B-Instruct-2507 is a 30.5B-parameter mixture-of-experts language model from Qwen, with 3.3B active parameters per inference. It operates in non-thinking mode and is designed for high-quality instruction following, multilingual understanding, and...
GLM-4.5 is our latest flagship foundation model, purpose-built for agent-based applications. It leverages a Mixture-of-Experts (MoE) architecture and supports a context length of up to 128k tokens. GLM-4.5 delivers significantly...
GLM-4.5-Air is the lightweight variant of our latest flagship model family, also purpose-built for agent-centric applications. Like GLM-4.5, it adopts the Mixture-of-Experts (MoE) architecture but with a more compact parameter...
Qwen3-235B-A22B-Thinking-2507 is a high-performance, open-weight Mixture-of-Experts (MoE) language model optimized for complex reasoning tasks. It activates 22B of its 235B parameters per forward pass and natively supports up to 262,144...
Qwen3-Coder-480B-A35B-Instruct is a Mixture-of-Experts (MoE) code generation model developed by the Qwen team. It is optimized for agentic coding tasks such as function calling, tool use, and long-context reasoning over...
Qwen3-Coder-480B-A35B-Instruct is a Mixture-of-Experts (MoE) code generation model developed by the Qwen team. It is optimized for agentic coding tasks such as function calling, tool use, and long-context reasoning over...
UI-TARS-1.5 is a multimodal vision-language agent optimized for GUI-based environments, including desktop interfaces, web browsers, mobile systems, and games. Built by ByteDance, it builds upon the UI-TARS framework with reinforcement...
Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following,...
Hunyuan-A13B is a 13B active parameter Mixture-of-Experts (MoE) language model developed by Tencent, with a total parameter count of 80B and support for reasoning via Chain-of-Thought. It offers competitive benchmark...
Mistral-Small-3.2-24B-Instruct-2506 is an updated 24B parameter model from Mistral optimized for instruction following, repetition reduction, and improved function calling. Compared to the 3.1 release, version 3.2 significantly improves accuracy on...
MiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom "lightning attention" mechanism, allowing it...
Claude Opus 4 is benchmarked as the world’s best coding model, at time of release, bringing sustained performance on complex, long-running tasks and agent workflows. It sets new benchmarks in...
Claude Sonnet 4 significantly enhances the capabilities of its predecessor, Sonnet 3.7, excelling in both coding and reasoning tasks with improved precision and controllability. Achieving state-of-the-art performance on SWE-bench (72.7%),...
Mistral Medium 3 is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances state-of-the-art reasoning and multimodal performance with 8× lower cost...
Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy...
Virtuoso‑Large is Arcee's top‑tier general‑purpose LLM at 72 B parameters, tuned to tackle cross‑domain reasoning, creative writing and enterprise QA. Unlike many 70 B peers, it retains the 128 k...
Llama Guard 4 is a Llama 4 Scout-derived multimodal pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM...
Qwen3-8B is a dense 8.2B parameter causal language model from the Qwen3 series, designed for both reasoning-heavy tasks and efficient dialogue. It supports seamless switching between "thinking" mode for math,...
Qwen3-235B-A22B is a 235B parameter mixture-of-experts (MoE) model developed by Qwen, activating 22B parameters per forward pass. It supports seamless switching between a "thinking" mode for complex reasoning, math, and...
OpenAI o4-mini-high is the same model as [o4-mini](/openai/o4-mini) with reasoning_effort set to high. OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining...
Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward...
Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...
Mistral Small 3.1 24B Instruct is an upgraded variant of Mistral Small 3 (2501), featuring 24 billion parameters with advanced multimodal capabilities. It provides state-of-the-art performance in text-based reasoning and...
GPT-4o mini Search Preview is a specialized model for web search in Chat Completions. It is trained to understand and execute web search queries.
GPT-4o Search Previewis a specialized model for web search in Chat Completions. It is trained to understand and execute web search queries.
OpenAI o3-mini-high is the same model as [o3-mini](/openai/o3-mini) with reasoning_effort set to high. o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and...
Qwen2.5-VL is proficient in recognizing common objects such as flowers, birds, fish, and insects. It is also highly capable of analyzing texts, charts, icons, graphics, and layouts within images.
Qwen-Plus, based on the Qwen2.5 foundation model, is a 131K context model with a balanced performance, speed, and cost combination.
MiniMax-01 is a combines MiniMax-Text-01 for text generation and MiniMax-VL-01 for image understanding. It has 456 billion parameters, with 45.9 billion parameters activated per inference, and can handle a context...
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...
This is Mistral AI's flagship model, Mistral Large 2 (version mistral-large-2407). It's a proprietary weights-available model and excels at reasoning, code, JSON, chat, and more. Read the launch announcement [here](https://mistral.ai/news/mistral-large-2407/)....
| Model | Creator | Inputs | Context | Input | Output | Released | Compare |
|---|---|---|---|---|---|---|---|
| Qwen: Qwen3 Maxqwen/qwen3-max | 262.144K | $0.78 | $3.9 | — | |||
| Qwen: Qwen3 Coder Plusqwen/qwen3-coder-plus | 1M | $0.65 | $3.25 | — | |||
| DeepSeek: DeepSeek V3.1 Terminusdeepseek/deepseek-v3.1-terminus | 163.84K | $0.27 | $1 | — | |||
| Qwen: Qwen3 Coder Flashqwen/qwen3-coder-flash | 1M | $0.195 | $0.975 | — | |||
| Qwen: Qwen3 Next 80B A3B Thinkingqwen/qwen3-next-80b-a3b-thinking | 262.144K | $0.15 | $1.2 | — | |||
| Qwen: Qwen3 Next 80B A3B Instruct (free)qwen/qwen3-next-80b-a3b-instruct:free | 262.144K | Free | Free | — | |||
| Qwen: Qwen3 Next 80B A3B Instructqwen/qwen3-next-80b-a3b-instruct | 262.144K | $0.09 | $1.1 | — | |||
| Qwen: Qwen Plus 0728 (thinking)qwen/qwen-plus-2025-07-28:thinking | 1M | $0.26 | $0.78 | — | |||
| Qwen: Qwen Plus 0728qwen/qwen-plus-2025-07-28 | 1M | $0.26 | $0.78 | — | |||
| NVIDIA: Nemotron Nano 9B V2 (free)nvidia/nemotron-nano-9b-v2:free | 128K | Free | Free | — | |||
| Nous: Hermes 4 70Bnousresearch/hermes-4-70b | 131.072K | $0.13 | $0.4 | — | |||
| Mistral: Mistral Medium 3.1mistralai/mistral-medium-3.1 | 131.072K | $0.4 | $2 | — | |||
| AI21: Jamba Large 1.7ai21/jamba-large-1.7 | 256K | $2 | $8 | — | |||
| OpenAI: GPT-5 Chatopenai/gpt-5-chat | 128K | $1.25 | $10 | — | |||
| OpenAI: gpt-oss-120b (free)openai/gpt-oss-120b:free | 131.072K | Free | Free | — | |||
| OpenAI: gpt-oss-20b (free)openai/gpt-oss-20b:free | 131.072K | Free | Free | — | |||
| Anthropic: Claude Opus 4.1anthropic/claude-opus-4.1 | 200K | $15 | $75 | — | |||
| Mistral: Codestral 2508mistralai/codestral-2508 | 256K | $0.3 | $0.9 | — | |||
| Qwen: Qwen3 Coder 30B A3B Instructqwen/qwen3-coder-30b-a3b-instruct | 262.144K | $0.07 | $0.28 | — | |||
| Qwen: Qwen3 30B A3B Instruct 2507qwen/qwen3-30b-a3b-instruct-2507 | 262.144K | $0.09 | $0.3 | — | |||
| Z.ai: GLM 4.5z-ai/glm-4.5 | 131.072K | $0.6 | $2.2 | — | |||
| Z.ai: GLM 4.5 Airz-ai/glm-4.5-air | 131.072K | $0.13 | $0.85 | — | |||
| Qwen: Qwen3 235B A22B Thinking 2507qwen/qwen3-235b-a22b-thinking-2507 | 128K | $0.45 | $3.5 | — | |||
| Qwen: Qwen3 Coder 480B A35B (free)qwen/qwen3-coder:free | 262K | Free | Free | — | |||
| Qwen: Qwen3 Coder 480B A35Bqwen/qwen3-coder | 262.144K | $0.3 | $1 | — | |||
| ByteDance: UI-TARS 7B bytedance/ui-tars-1.5-7b | 128K | $0.1 | $0.2 | — | |||
| Qwen: Qwen3 235B A22B Instruct 2507qwen/qwen3-235b-a22b-2507 | 262.144K | $0.09 | $0.55 | — | |||
| Tencent: Hunyuan A13B Instructtencent/hunyuan-a13b-instruct | 131.072K | $0.14 | $0.57 | — | |||
| Mistral: Mistral Small 3.2 24Bmistralai/mistral-small-3.2-24b-instruct | 128K | $0.075 | $0.2 | — | |||
| MiniMax: MiniMax M1minimax/minimax-m1 | 1M | $0.55 | $2.2 | — | |||
| Anthropic: Claude Opus 4anthropic/claude-opus-4 | 200K | $15 | $75 | — | |||
| Anthropic: Claude Sonnet 4anthropic/claude-sonnet-4 | 200K | $3 | $15 | — | |||
| Mistral: Mistral Medium 3mistralai/mistral-medium-3 | 131.072K | $0.4 | $2 | — | |||
| Google: Gemini 2.5 Pro Preview 05-06google/gemini-2.5-pro-preview-05-06 | 1.04858M | $1.25 | $10 | — | |||
| Arcee AI: Virtuoso Largearcee-ai/virtuoso-large | 131.072K | $0.75 | $1.2 | — | |||
| Meta: Llama Guard 4 12Bmeta-llama/llama-guard-4-12b | 163.84K | $0.18 | $0.18 | — | |||
| Qwen: Qwen3 8Bqwen/qwen3-8b | 131.072K | $0.117 | $0.455 | — | |||
| Qwen: Qwen3 235B A22Bqwen/qwen3-235b-a22b | 131.072K | $0.455 | $1.82 | — | |||
| OpenAI: o4 Mini Highopenai/o4-mini-high | 200K | $1.1 | $4.4 | — | |||
| Meta: Llama 4 Maverickmeta-llama/llama-4-maverick | 128K | $0.188 | $0.652 | — | |||
| Meta: Llama 4 Scoutmeta-llama/llama-4-scout | 327.68K | $0.1 | $0.3 | — | |||
| Mistral: Mistral Small 3.1 24Bmistralai/mistral-small-3.1-24b-instruct | 128K | $0.351 | $0.555 | — | |||
| OpenAI: GPT-4o-mini Search Previewopenai/gpt-4o-mini-search-preview | 128K | $0.15 | $0.6 | — | |||
| OpenAI: GPT-4o Search Previewopenai/gpt-4o-search-preview | 128K | $2.5 | $10 | — | |||
| OpenAI: o3 Mini Highopenai/o3-mini-high | 200K | $1.1 | $4.4 | — | |||
| Qwen: Qwen2.5 VL 72B Instructqwen/qwen2.5-vl-72b-instruct | 128K | $0.8 | $1 | — | |||
| Qwen: Qwen-Plusqwen/qwen-plus | 1M | $0.26 | $0.78 | — | |||
| MiniMax: MiniMax-01minimax/minimax-01 | 1.00019M | $0.2 | $1.1 | — | |||
| Meta: Llama 3.3 70B Instructmeta-llama/llama-3.3-70b-instruct | 131.072K | $0.1 | $0.32 | — | |||
| Mistral Large 2407mistralai/mistral-large-2407 | 131.072K | $2 | $6 | — |