Mercury 2 is an extremely fast reasoning LLM, and the first reasoning diffusion LLM (dLLM). Instead of generating tokens sequentially, Mercury 2 produces and refines multiple tokens in parallel, achieving...
Models
Every model in the catalog with source-linked pricing, context limits, provider availability, and published benchmark results.
Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It is optimized for...
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...
Tiny GPT-4.1 option for classification, routing, and very high-volume tasks
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)
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 smallest model in the Ministral 3 family, Ministral 3 3B is a powerful, efficient tiny language model with vision capabilities.
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...
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, 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...
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...
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 |
|---|---|---|---|---|---|---|---|---|
| Inception: Mercury 2inception/mercury-2 | 1003.0 | 128K | $0.25 | $0.75 | — | |||
| MoonshotAI: Kimi K2 0711moonshotai/kimi-k2 | 997.0 | 131.072K | $0.57 | $2.3 | — | |||
| OpenAI: GPT-4.1 Nano (batch)openai/gpt-4.1-nano:batch | 993.0 | 1.04758M | $0.05 | $0.2 | — | |||
| GPT-4.1 nanoopenai/gpt-4.1-nano | 993.0 | 1.04758M | $0.1 | $0.4 | 2025-04-14 | |||
| Mistral: Codestral 2508 (batch)mistralai/codestral-2508:batch | 990.0 | 256K | $0.15 | $0.45 | — | |||
| Mistral: Codestral 2508mistralai/codestral-2508 | 990.0 | 256K | $0.3 | $0.9 | — | |||
| Qwen: Qwen3 235B A22B Thinking 2507qwen/qwen3-235b-a22b-thinking-2507 | 980.0 | 131.072K | $0.23 | $2.3 | — | |||
| Qwen: Qwen3 235B A22B Instruct 2507qwen/qwen3-235b-a22b-2507 | 974.0 | 262.144K | $0.087 | $0.35 | — | |||
| Mistral: Ministral 3 3B 2512mistralai/ministral-3b-2512 | 971.0 | 131.072K | $0.1 | $0.1 | — | |||
| Qwen: Qwen3 235B A22Bqwen/qwen3-235b-a22b | 950.0 | 131.072K | $0.455 | $1.82 | — | |||
| GPT-4oopenai/gpt-4o | 929.0 | 128K | $2.5 | $10 | 2024-05-13 | |||
| OpenAI: GPT-4o (batch)openai/gpt-4o:batch | 929.0 | 128K | $1.25 | $5 | — | |||
| Qwen: Qwen3 30B A3Bqwen/qwen3-30b-a3b | 921.0 | 40.96K | $0.12 | $0.5 | — | |||
| Mistral: Mistral Small 3.2 24Bmistralai/mistral-small-3.2-24b-instruct | 911.0 | 128K | $0.075 | $0.2 | — | |||
| Meta: Llama 4 Maverickmeta-llama/llama-4-maverick | 860.0 | 128K | $0.2 | $0.696 | — | |||
| Meta: Llama 4 Scoutmeta-llama/llama-4-scout | 796.0 | 327.68K | $0.1 | $0.3 | — |