Claude Sonnet 4.5 is Anthropic’s most advanced Sonnet model to date, optimized for real-world agents and coding workflows. It delivers state-of-the-art performance on coding benchmarks such as SWE-bench Verified, with...
Models
Every model in the catalog with source-linked pricing, context limits, provider availability, and published benchmark results.
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...
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...
Coding-optimized GPT model for repository edits, reviews, and agentic software work
Compared with GLM-4.5, this generation brings several key improvements: Longer context window: The context window has been expanded from 128K to 200K tokens, enabling the model to handle more complex...
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...
NVIDIA Nemotron 3 Ultra is an open frontier-reasoning and orchestration model from NVIDIA, with 55B active parameters out of 550B total (MoE). Built on a hybrid Transformer-Mamba mixture-of-experts architecture, it...
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%),...
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...
Inkling is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 41B active parameters out of 975B total. It is designed for general-purpose reasoning, coding, agentic and tool-use systems,...
DeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...
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...
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...
NVIDIA Nemotron 3 Ultra is an open frontier-reasoning and orchestration model from NVIDIA, with 55B active parameters out of 550B total (MoE). Built on a hybrid Transformer-Mamba mixture-of-experts architecture, it...
MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier intelligence across general reasoning,...
Mistral Large 3 2512 is Mistral’s most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.
Mistral Large 3 2512 is Mistral’s most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.
The Qwen3.5 native vision-language series Plus models are built on a hybrid architecture that integrates linear attention mechanisms with sparse mixture-of-experts models, achieving higher inference efficiency. In a variety of...
Fast Gemini workhorse for multimodal apps where latency and price matter
Gemini 2.5 Flash is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in "thinking" capabilities, enabling it to provide responses with greater...
Small GPT-5 for responsive agents, coding help, and everyday automation
GPT-5 Mini is a compact version of GPT-5, designed to handle lighter-weight reasoning tasks. It provides the same instruction-following and safety-tuning benefits as GPT-5, but with reduced latency and cost....
Claude Haiku 4.5 is Anthropic’s fastest and most efficient model, delivering near-frontier intelligence at a fraction of the cost and latency of larger Claude models. Matching Claude Sonnet 4’s performance...
Claude Haiku 4.5 is Anthropic’s fastest and most efficient model, delivering near-frontier intelligence at a fraction of the cost and latency of larger Claude models. Matching Claude Sonnet 4’s performance...
As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning,...
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...
Long-lived GPT workhorse for coding, instruction following, and production apps
GPT-4.1 is a flagship large language model optimized for advanced instruction following, real-world software engineering, and long-context reasoning. It supports a 1 million token context window and outperforms GPT-4o and...
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...
Coding-optimized GPT model for repository edits, reviews, and agentic software work
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-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...
Qwen3-235B-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,...
Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs
GPT-5-Nano is the smallest and fastest variant in the GPT-5 system, optimized for developer tools, rapid interactions, and ultra-low latency environments. While limited in reasoning depth compared to its larger...
Low-latency Gemini model for high-volume multimodal and agent workloads
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...
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...
Affordable GPT-4.1 lane for fast coding help and structured extraction
GPT-4.1 Mini is a mid-sized model delivering performance competitive with GPT-4o at substantially lower latency and cost. It retains a 1 million token context window and scores 45.1% on hard...
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)
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)
Reasoning model for deliberate analysis, multi-step problem solving, and tool use
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...
Fast o-series model for compact reasoning, coding, and tool use
OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining strong multimodal and agentic capabilities. It supports tool use and demonstrates competitive reasoning...
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...
Qwen3, the latest generation in the Qwen large language model series, features both dense and mixture-of-experts (MoE) architectures to excel in reasoning, multilingual support, and advanced agent tasks. Its unique...
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...
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...
| Model | Creator | Score | Inputs | Context | Input | Output | Released | Compare |
|---|---|---|---|---|---|---|---|---|
| Anthropic: Claude Sonnet 4.5 (batch)anthropic/claude-sonnet-4.5:batch | 1167.0 | 1M | $1.5 | $7.5 | — | |||
| Anthropic: Claude Opus 4.1anthropic/claude-opus-4.1 | 1166.0 | 200K | $15 | $75 | — | |||
| Anthropic: Claude Opus 4.1 (batch)anthropic/claude-opus-4.1:batch | 1166.0 | 200K | $7.5 | $37.5 | — | |||
| GPT-5.3 Codexopenai/gpt-5.3-codex | 1164.0 | 400K | $1.75 | $14 | 2026-02-05 | |||
| Z.ai: GLM 4.6z-ai/glm-4.6 | 1161.0 | 204.8K | $0.55 | $2.2 | — | |||
| Anthropic: Claude Opus 4anthropic/claude-opus-4 | 1160.0 | 200K | $15 | $75 | — | |||
| NVIDIA: Nemotron 3 Ultra (batch)nvidia/nemotron-3-ultra-550b-a55b:batch | 1160.0 | 512.288K | $0.6 | $3.6 | — | |||
| Anthropic: Claude Sonnet 4anthropic/claude-sonnet-4 | 1159.0 | 200K | $3 | $15 | — | |||
| Z.ai: GLM 4.5z-ai/glm-4.5 | 1159.0 | 131.072K | $0.6 | $2.2 | — | |||
| Thinking Machines: Inkling (free)thinkingmachines/inkling:free | 1156.0 | 1.04858M | Free | Free | — | |||
| DeepSeek: DeepSeek V3.2 Expdeepseek/deepseek-v3.2-exp | 1152.0 | 163.84K | $0.27 | $0.41 | — | |||
| Mistral: Mistral Medium 3.1mistralai/mistral-medium-3.1 | 1144.0 | 131.072K | $0.4 | $2 | — | |||
| Mistral: Mistral Medium 3.1 (batch)mistralai/mistral-medium-3.1:batch | 1144.0 | 131.072K | $0.2 | $1 | — | |||
| NVIDIA: Nemotron 3 Ultra (free)nvidia/nemotron-3-ultra-550b-a55b:free | 1141.0 | 1M | Free | Free | — | |||
| MiniMax: MiniMax M2minimax/minimax-m2 | 1140.0 | 204.8K | $0.255 | $1.02 | — | |||
| Mistral: Mistral Large 3 2512mistralai/mistral-large-2512 | 1136.0 | 262.144K | $0.5 | $1.5 | — | |||
| Mistral: Mistral Large 3 2512 (batch)mistralai/mistral-large-2512:batch | 1136.0 | 262.144K | $0.25 | $0.75 | — | |||
| Qwen: Qwen3.5 Plus 2026-02-15qwen/qwen3.5-plus-02-15 | 1135.0 | 1M | $0.26 | $1.56 | — | |||
| Gemini 2.5 Flashgoogle/gemini-2.5-flash | 1134.0 | 1.04858M | $0.3 | $2.5 | 2025-06-17 | |||
| Google: Gemini 2.5 Flash (batch)google/gemini-2.5-flash:batch | 1133.0 | 1.04858M | $0.15 | $1.25 | — | |||
| GPT-5 Miniopenai/gpt-5-mini | 1131.0 | 400K | $0.25 | $2 | 2025-08-07 | |||
| OpenAI: GPT-5 Mini (batch)openai/gpt-5-mini:batch | 1131.0 | 400K | $0.125 | $1 | — | |||
| Anthropic: Claude Haiku 4.5anthropic/claude-haiku-4.5 | 1124.0 | 200K | $1 | $5 | — | |||
| Anthropic: Claude Haiku 4.5 (batch)anthropic/claude-haiku-4.5:batch | 1124.0 | 200K | $0.5 | $2.5 | — | |||
| Z.ai: GLM 4.7 Flashz-ai/glm-4.7-flash | 1123.0 | 131.072K | $0.061 | $0.4 | — | |||
| Qwen: Qwen3 Coder 480B A35B (free)qwen/qwen3-coder:free | 1116.0 | 262K | Free | Free | — | |||
| GPT-4.1openai/gpt-4.1 | 1104.0 | 1.04758M | $2 | $8 | 2025-04-14 | |||
| OpenAI: GPT-4.1 (batch)openai/gpt-4.1:batch | 1104.0 | 1.04758M | $1 | $4 | — | |||
| Qwen: Qwen3 Maxqwen/qwen3-max | 1103.0 | 262.144K | $0.78 | $3.9 | — | |||
| GPT-5.1 Codex miniopenai/gpt-5.1-codex-mini | 1097.0 | 400K | $0.22 | $1.8 | 2025-11-13 | |||
| Qwen: Qwen3 Coder 30B A3B Instructqwen/qwen3-coder-30b-a3b-instruct | 1085.0 | 262.144K | $0.07 | $0.28 | — | |||
| Qwen: Qwen3 Coder 480B A35Bqwen/qwen3-coder | 1084.0 | 262.144K | $0.3 | $1 | — | |||
| Qwen: Qwen3 235B A22B Instruct 2507qwen/qwen3-235b-a22b-2507 | 1070.0 | 262.144K | $0.09 | $0.55 | — | |||
| GPT-5 Nanoopenai/gpt-5-nano | 1056.0 | 400K | $0.05 | $0.4 | 2025-08-07 | |||
| OpenAI: GPT-5 Nano (batch)openai/gpt-5-nano:batch | 1056.0 | 400K | $0.025 | $0.2 | — | |||
| Gemini 3.1 Flash Lite Previewgoogle/gemini-3.1-flash-lite-preview | 1045.0 | 1.04858M | $0.25 | $1.5 | 2026-03-03 | |||
| OpenAI: gpt-oss-120b (free)openai/gpt-oss-120b:free | 1040.0 | 131.072K | Free | Free | — | |||
| Mistral: Mistral Medium 3mistralai/mistral-medium-3 | 1034.0 | 131.072K | $0.4 | $2 | — | |||
| GPT-4.1 miniopenai/gpt-4.1-mini | 1034.0 | 1.04758M | $0.4 | $1.6 | 2025-04-14 | |||
| OpenAI: GPT-4.1 Mini (batch)openai/gpt-4.1-mini:batch | 1034.0 | 1.04758M | $0.2 | $0.8 | — | |||
| Mistral: Codestral 2508mistralai/codestral-2508 | 1017.0 | 256K | $0.3 | $0.9 | — | |||
| Mistral: Codestral 2508 (batch)mistralai/codestral-2508:batch | 1017.0 | 256K | $0.15 | $0.45 | — | |||
| Mercury 2inception/mercury-2 | 1011.0 | 128K | $0.25 | $0.75 | 2026-02-24 | |||
| Qwen: Qwen3 235B A22Bqwen/qwen3-235b-a22b | 999.0 | 131.072K | $0.455 | $1.82 | — | |||
| o4-miniopenai/o4-mini | 991.0 | 200K | $1.1 | $4.4 | 2025-04-16 | |||
| OpenAI: o4 Mini (batch)openai/o4-mini:batch | 991.0 | 200K | $0.55 | $2.2 | — | |||
| OpenAI: gpt-oss-120b (batch)openai/gpt-oss-120b:batch | 987.0 | 131.072K | $0.03 | $0.136 | — | |||
| Qwen: Qwen3 30B A3Bqwen/qwen3-30b-a3b | 967.0 | 40.96K | $0.12 | $0.5 | — | |||
| OpenAI: gpt-oss-20b (free)openai/gpt-oss-20b:free | 952.0 | 131.072K | Free | Free | — | |||
| Qwen: Qwen3 235B A22B Thinking 2507qwen/qwen3-235b-a22b-thinking-2507 | 950.0 | 128K | $0.45 | $3.5 | — |