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...
Models
Every model in the catalog with source-linked pricing, context limits, provider availability, and published benchmark results.
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...
DeepSeek chat model for instruction following, coding, and analysis
DeepSeek chat model for instruction following, coding, and analysis
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...
Fast Gemini workhorse for multimodal apps where latency and price matter
Thinking Kimi model for slower research passes, planning, and hard technical questions
Coding-optimized GPT model for repository edits, reviews, and agentic software work
September 2025 Kimi K2 instruction update with a 256K context and improved agentic coding
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...
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...
Low-latency Gemini model for high-volume multimodal and agent workloads
The largest model in the Ministral 3 family, Ministral 3 14B offers frontier capabilities and performance comparable to its larger Mistral Small 3.2 24B counterpart. A powerful and efficient language...
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...
A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.
A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.
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,...
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...
Kimi model for long-context chat, coding, and agentic reasoning
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...
Deliberate o-series reasoner for hard math, coding, and multi-step analysis
o3 is a well-rounded and powerful model across domains. It sets a new standard for math, science, coding, and visual reasoning tasks. It also excels at technical writing and instruction-following....
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...
The smallest model in the Ministral 3 family, Ministral 3 3B is a powerful, efficient tiny language model with vision capabilities.
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)
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...
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...
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...
Tiny GPT-4.1 option for classification, routing, and very high-volume tasks
For tasks that demand low latency, GPT‑4.1 nano is the fastest and cheapest model in the GPT-4.1 series. It delivers exceptional performance at a small size with its 1 million...
Open GPT reasoning model for self-hosted agents and controllable deployments
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...
Qwen3-30B-A3B-Thinking-2507 is a 30B parameter Mixture-of-Experts reasoning model optimized for complex tasks requiring extended multi-step thinking. The model is designed specifically for “thinking mode,” where internal reasoning traces are separated...
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...
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...
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...
Open GPT reasoning model for self-hosted agents and controllable deployments
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...
Amazon Nova Premier is the most capable of Amazon’s multimodal models for complex reasoning tasks and for use as the best teacher for distilling custom models.
Omni-era GPT for multimodal chat, practical coding, and general assistants
GPT-4o ("o" for "omni") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of [GPT-4 Turbo](/models/openai/gpt-4-turbo) while being twice as...
Flagship model for demanding analysis, coding, and production agent workflows
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...
| Model | Creator | Score | Inputs | Context | Input | Output | Released | Compare |
|---|---|---|---|---|---|---|---|---|
| Anthropic: Claude Haiku 4.5anthropic/claude-haiku-4.5 | 1122.0 | 200K | $1 | $5 | — | |||
| Anthropic: Claude Haiku 4.5 (batch)anthropic/claude-haiku-4.5:batch | 1122.0 | 200K | $0.5 | $2.5 | — | |||
| DeepSeek V3.1deepseek/deepseek-chat-v3.1 | 1122.0 | 163.84K | $0.19 | $0.79 | 2025-08-21 | |||
| DeepSeek Chatdeepseek/deepseek-chat | 1118.0 | 1M | $0.15 | $0.6 | 2025-12-01 | |||
| Google: Gemini 2.5 Flash (batch)google/gemini-2.5-flash:batch | 1115.0 | 1.04858M | $0.15 | $1.25 | — | |||
| Gemini 2.5 Flashgoogle/gemini-2.5-flash | 1113.0 | 1.04858M | $0.3 | $2.5 | 2025-06-17 | |||
| Kimi K2 Thinkingmoonshotai/kimi-k2-thinking | 1113.0 | 262.144K | $0.4 | $2.5 | 2025-11-06 | |||
| GPT-5.1 Codex miniopenai/gpt-5.1-codex-mini | 1109.0 | 400K | $0.22 | $1.8 | 2025-11-13 | |||
| Kimi K2 Instruct 0905moonshotai/kimi-k2-0905 | 1107.0 | 262.144K | $0.6 | $2.5 | 2025-09-05 | |||
| GPT-5 Nanoopenai/gpt-5-nano | 1101.0 | 400K | $0.05 | $0.4 | 2025-08-07 | |||
| OpenAI: GPT-5 Nano (batch)openai/gpt-5-nano:batch | 1101.0 | 400K | $0.025 | $0.2 | — | |||
| Qwen: Qwen3 Coder 30B A3B Instructqwen/qwen3-coder-30b-a3b-instruct | 1087.0 | 262.144K | $0.07 | $0.28 | — | |||
| Gemini 3.1 Flash Lite Previewgoogle/gemini-3.1-flash-lite-preview | 1081.0 | 1.04858M | $0.25 | $1.5 | 2026-03-03 | |||
| Mistral: Ministral 3 14B 2512mistralai/ministral-14b-2512 | 1081.0 | 262.144K | $0.2 | $0.2 | — | |||
| Mistral: Mistral Medium 3mistralai/mistral-medium-3 | 1077.0 | 131.072K | $0.4 | $2 | — | |||
| Mistral: Ministral 3 8B 2512mistralai/ministral-8b-2512 | 1063.0 | 262.144K | $0.15 | $0.15 | — | |||
| Mistral: Ministral 3 8B 2512 (batch)mistralai/ministral-8b-2512:batch | 1063.0 | 262.144K | $0.075 | $0.075 | — | |||
| Qwen: Qwen3 235B A22B Instruct 2507qwen/qwen3-235b-a22b-2507 | 1056.0 | 262.144K | $0.09 | $0.55 | — | |||
| Qwen: Qwen3 235B A22B Thinking 2507qwen/qwen3-235b-a22b-thinking-2507 | 1051.0 | 128K | $0.45 | $3.5 | — | |||
| Kimi K2 0711moonshotai/kimi-k2 | 1050.0 | 131.072K | $0.4 | $1.8 | 2025-07-11 | |||
| GPT-4.1openai/gpt-4.1 | 1037.0 | 1.04758M | $2 | $8 | 2025-04-14 | |||
| OpenAI: GPT-4.1 (batch)openai/gpt-4.1:batch | 1037.0 | 1.04758M | $1 | $4 | — | |||
| o3openai/o3 | 1036.0 | 200K | $2 | $8 | 2025-04-16 | |||
| OpenAI: o3 (batch)openai/o3:batch | 1036.0 | 200K | $1 | $4 | — | |||
| Mercury 2inception/mercury-2 | 1035.0 | 128K | $0.25 | $0.75 | 2026-02-24 | |||
| Qwen: Qwen3 235B A22Bqwen/qwen3-235b-a22b | 1035.0 | 131.072K | $0.455 | $1.82 | — | |||
| Mistral: Ministral 3 3B 2512mistralai/ministral-3b-2512 | 1026.0 | 131.072K | $0.1 | $0.1 | — | |||
| Mistral: Codestral 2508mistralai/codestral-2508 | 1011.0 | 256K | $0.3 | $0.9 | — | |||
| Mistral: Codestral 2508 (batch)mistralai/codestral-2508:batch | 1011.0 | 256K | $0.15 | $0.45 | — | |||
| OpenAI: gpt-oss-120b (free)openai/gpt-oss-120b:free | 1003.0 | 131.072K | Free | Free | — | |||
| GPT-4.1 miniopenai/gpt-4.1-mini | 997.0 | 1.04758M | $0.4 | $1.6 | 2025-04-14 | |||
| OpenAI: GPT-4.1 Mini (batch)openai/gpt-4.1-mini:batch | 997.0 | 1.04758M | $0.2 | $0.8 | — | |||
| o4-miniopenai/o4-mini | 985.0 | 200K | $1.1 | $4.4 | 2025-04-16 | |||
| OpenAI: o4 Mini (batch)openai/o4-mini:batch | 985.0 | 200K | $0.55 | $2.2 | — | |||
| GPT-4.1 nanoopenai/gpt-4.1-nano | 971.0 | 1.04758M | $0.1 | $0.4 | 2025-04-14 | |||
| OpenAI: GPT-4.1 Nano (batch)openai/gpt-4.1-nano:batch | 971.0 | 1.04758M | $0.05 | $0.2 | — | |||
| GPT OSS 120Bopenai/gpt-oss-120b | 966.0 | 131.072K | $0.03 | $0.15 | 2025-08-05 | |||
| OpenAI: gpt-oss-120b (batch)openai/gpt-oss-120b:batch | 966.0 | 131.072K | $0.03 | $0.136 | — | |||
| Qwen: Qwen3 30B A3Bqwen/qwen3-30b-a3b | 953.0 | 40.96K | $0.12 | $0.5 | — | |||
| Qwen: Qwen3 30B A3B Thinking 2507qwen/qwen3-30b-a3b-thinking-2507 | 935.0 | 81.92K | $0.2 | $2.4 | — | |||
| Mistral: Mistral Small 3.2 24Bmistralai/mistral-small-3.2-24b-instruct | 894.0 | 128K | $0.075 | $0.2 | — | |||
| Meta: Llama 4 Maverickmeta-llama/llama-4-maverick | 869.0 | 128K | $0.188 | $0.652 | — | |||
| OpenAI: gpt-oss-20b (free)openai/gpt-oss-20b:free | 864.0 | 131.072K | Free | Free | — | |||
| GPT OSS 20Bopenai/gpt-oss-20b | 852.0 | 131.072K | $0.018 | $0.09 | 2025-08-05 | |||
| OpenAI: gpt-oss-20b (batch)openai/gpt-oss-20b:batch | 852.0 | 131.072K | $0.024 | $0.112 | — | |||
| Amazon: Nova Premier 1.0amazon/nova-premier-v1 | 835.0 | 1M | $2.5 | $12.5 | — | |||
| GPT-4oopenai/gpt-4o | 831.0 | 128K | $2.5 | $10 | 2024-05-13 | |||
| OpenAI: GPT-4o (batch)openai/gpt-4o:batch | 831.0 | 128K | $1.25 | $5 | — | |||
| Nova Pro 1.0amazon/nova-pro-v1 | 796.0 | 300K | $0.799 | $3.196 | 2024-12-05 | |||
| Meta: Llama 4 Scoutmeta-llama/llama-4-scout | 750.0 | 327.68K | $0.1 | $0.3 | — |