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)
Models
Every model in the catalog with source-linked pricing, context limits, provider availability, and published benchmark results.
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)
Coding-optimized GPT model for repository edits, reviews, and agentic software work
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...
Qwen3-235B-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,...
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...
Coding-optimized GPT model for repository edits, reviews, and agentic software work
Reasoning model for deliberate analysis, multi-step problem solving, and tool use
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-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...
The smallest model in the Ministral 3 family, Ministral 3 3B is a powerful, efficient tiny language model with vision capabilities.
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...
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...
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...
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...
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...
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...
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...
| Model | Creator | Score | Inputs | Context | Input | Output | Released | Compare |
|---|---|---|---|---|---|---|---|---|
| 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 | — | |||
| GPT-5.3 Codexopenai/gpt-5.3-codex | 1005.0 | 400K | $1.75 | $14 | 2026-02-05 | |||
| Qwen: Qwen3 235B A22B Thinking 2507qwen/qwen3-235b-a22b-thinking-2507 | 995.0 | 128K | $0.45 | $3.5 | — | |||
| Qwen: Qwen3 235B A22B Instruct 2507qwen/qwen3-235b-a22b-2507 | 991.0 | 262.144K | $0.09 | $0.55 | — | |||
| Mistral: Ministral 3 14B 2512mistralai/ministral-14b-2512 | 987.0 | 262.144K | $0.2 | $0.2 | — | |||
| GPT-5.1 Codex miniopenai/gpt-5.1-codex-mini | 985.0 | 400K | $0.22 | $1.8 | 2025-11-13 | |||
| Mercury 2inception/mercury-2 | 980.0 | 128K | $0.25 | $0.75 | 2026-02-24 | |||
| OpenAI: gpt-oss-120b (free)openai/gpt-oss-120b:free | 974.0 | 131.072K | Free | Free | — | |||
| GPT-5 Nanoopenai/gpt-5-nano | 963.0 | 400K | $0.05 | $0.4 | 2025-08-07 | |||
| OpenAI: GPT-5 Nano (batch)openai/gpt-5-nano:batch | 963.0 | 400K | $0.025 | $0.2 | — | |||
| Mistral: Ministral 3 3B 2512mistralai/ministral-3b-2512 | 960.0 | 131.072K | $0.1 | $0.1 | — | |||
| GPT-4.1 nanoopenai/gpt-4.1-nano | 922.0 | 1.04758M | $0.1 | $0.4 | 2025-04-14 | |||
| OpenAI: GPT-4.1 Nano (batch)openai/gpt-4.1-nano:batch | 922.0 | 1.04758M | $0.05 | $0.2 | — | |||
| Meta: Llama 4 Maverickmeta-llama/llama-4-maverick | 898.0 | 128K | $0.188 | $0.652 | — | |||
| GPT OSS 120Bopenai/gpt-oss-120b | 898.0 | 131.072K | $0.03 | $0.17 | 2025-08-05 | |||
| OpenAI: gpt-oss-120b (batch)openai/gpt-oss-120b:batch | 898.0 | 131.072K | $0.03 | $0.136 | — | |||
| GPT-4oopenai/gpt-4o | 866.0 | 128K | $2.5 | $10 | 2024-05-13 | |||
| OpenAI: GPT-4o (batch)openai/gpt-4o:batch | 866.0 | 128K | $1.25 | $5 | — | |||
| Qwen: Qwen3 235B A22Bqwen/qwen3-235b-a22b | 864.0 | 131.072K | $0.455 | $1.82 | — | |||
| o4-miniopenai/o4-mini | 851.0 | 200K | $1.1 | $4.4 | 2025-04-16 | |||
| OpenAI: o4 Mini (batch)openai/o4-mini:batch | 851.0 | 200K | $0.55 | $2.2 | — | |||
| GPT-4.1openai/gpt-4.1 | 847.0 | 1.04758M | $2 | $8 | 2025-04-14 | |||
| OpenAI: GPT-4.1 (batch)openai/gpt-4.1:batch | 847.0 | 1.04758M | $1 | $4 | — | |||
| GPT-4.1 miniopenai/gpt-4.1-mini | 834.0 | 1.04758M | $0.4 | $1.6 | 2025-04-14 | |||
| OpenAI: GPT-4.1 Mini (batch)openai/gpt-4.1-mini:batch | 834.0 | 1.04758M | $0.2 | $0.8 | — |