Coding-optimized GPT model for repository edits, reviews, and agentic software work
Models
Every model in the catalog with source-linked pricing, context limits, provider availability, and published benchmark results.
Low-latency Gemini model for high-volume multimodal and agent workloads
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...
Reasoning-optimized 398B MoE agent model with extended thinking for long-horizon and multi-turn tool use
Kimi model for long-context chat, coding, and agentic reasoning
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...
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)
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....
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...
Reasoning model for deliberate analysis, multi-step problem solving, and tool use
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...
Qwen3-235B-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...
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,...
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...
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, 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...
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...
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...
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...
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...
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 |
|---|---|---|---|---|---|---|---|---|
| GPT-5.1 Codex miniopenai/gpt-5.1-codex-mini | 1076.0 | 400K | $0.22 | $1.8 | 2025-11-13 | |||
| Gemini 3.1 Flash Lite Previewgoogle/gemini-3.1-flash-lite-preview | 1066.0 | 1.04858M | $0.25 | $1.5 | 2026-03-03 | |||
| GPT-5 Nanoopenai/gpt-5-nano | 1061.0 | 400K | $0.05 | $0.4 | 2025-08-07 | |||
| OpenAI: GPT-5 Nano (batch)openai/gpt-5-nano:batch | 1061.0 | 400K | $0.025 | $0.2 | — | |||
| Qwen: Qwen3 Coder 30B A3B Instructqwen/qwen3-coder-30b-a3b-instruct | 1041.0 | 262.144K | $0.07 | $0.28 | — | |||
| Trinity Large Thinkingarcee-ai/trinity-large-thinking | 1040.0 | 524.288K | $0.25 | $0.8 | 2026-04-01 | |||
| Kimi K2 0711moonshotai/kimi-k2 | 1025.0 | 131.072K | $0.4 | $1.8 | 2025-07-11 | |||
| Mistral: Mistral Medium 3mistralai/mistral-medium-3 | 1019.0 | 131.072K | $0.4 | $2 | — | |||
| Mistral: Codestral 2508mistralai/codestral-2508 | 1012.0 | 256K | $0.3 | $0.9 | — | |||
| Mistral: Codestral 2508 (batch)mistralai/codestral-2508:batch | 1012.0 | 256K | $0.15 | $0.45 | — | |||
| o3openai/o3 | 1011.0 | 200K | $2 | $8 | 2025-04-16 | |||
| OpenAI: o3 (batch)openai/o3:batch | 1011.0 | 200K | $1 | $4 | — | |||
| GPT-4.1openai/gpt-4.1 | 995.0 | 1.04758M | $2 | $8 | 2025-04-14 | |||
| OpenAI: GPT-4.1 (batch)openai/gpt-4.1:batch | 995.0 | 1.04758M | $1 | $4 | — | |||
| Mercury 2inception/mercury-2 | 991.0 | 128K | $0.25 | $0.75 | 2026-02-24 | |||
| o4-miniopenai/o4-mini | 978.0 | 200K | $1.1 | $4.4 | 2025-04-16 | |||
| OpenAI: o4 Mini (batch)openai/o4-mini:batch | 978.0 | 200K | $0.55 | $2.2 | — | |||
| OpenAI: gpt-oss-120b (free)openai/gpt-oss-120b:free | 973.0 | 131.072K | Free | Free | — | |||
| Qwen: Qwen3 235B A22Bqwen/qwen3-235b-a22b | 962.0 | 131.072K | $0.455 | $1.82 | — | |||
| Qwen: Qwen3 235B A22B Instruct 2507qwen/qwen3-235b-a22b-2507 | 960.0 | 262.144K | $0.09 | $0.55 | — | |||
| GPT-4.1 miniopenai/gpt-4.1-mini | 956.0 | 1.04758M | $0.4 | $1.6 | 2025-04-14 | |||
| OpenAI: GPT-4.1 Mini (batch)openai/gpt-4.1-mini:batch | 956.0 | 1.04758M | $0.2 | $0.8 | — | |||
| Qwen: Qwen3 235B A22B Thinking 2507qwen/qwen3-235b-a22b-thinking-2507 | 940.0 | 128K | $0.45 | $3.5 | — | |||
| Qwen: Qwen3 30B A3Bqwen/qwen3-30b-a3b | 940.0 | 40.96K | $0.12 | $0.5 | — | |||
| GPT OSS 120Bopenai/gpt-oss-120b | 921.0 | 131.072K | $0.03 | $0.15 | 2025-08-05 | |||
| OpenAI: gpt-oss-120b (batch)openai/gpt-oss-120b:batch | 921.0 | 131.072K | $0.03 | $0.136 | — | |||
| GPT-4.1 nanoopenai/gpt-4.1-nano | 911.0 | 1.04758M | $0.1 | $0.4 | 2025-04-14 | |||
| OpenAI: GPT-4.1 Nano (batch)openai/gpt-4.1-nano:batch | 911.0 | 1.04758M | $0.05 | $0.2 | — | |||
| Mistral: Mistral Small 3.2 24Bmistralai/mistral-small-3.2-24b-instruct | 902.0 | 128K | $0.075 | $0.2 | — | |||
| Meta: Llama 4 Maverickmeta-llama/llama-4-maverick | 894.0 | 128K | $0.188 | $0.652 | — | |||
| GPT-4oopenai/gpt-4o | 880.0 | 128K | $2.5 | $10 | 2024-05-13 | |||
| OpenAI: GPT-4o (batch)openai/gpt-4o:batch | 880.0 | 128K | $1.25 | $5 | — | |||
| Meta: Llama 4 Scoutmeta-llama/llama-4-scout | 762.0 | 327.68K | $0.1 | $0.3 | — |