Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy
Models
Every model in the catalog with source-linked pricing, context limits, provider availability, and published benchmark results.
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.
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...
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.
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...
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....
Small GPT-5 for responsive agents, coding help, and everyday automation
Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work
Tencent Hy reasoning model for coding, instruction following, and agent tasks
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...
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-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-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...
Reasoning-optimized 398B MoE agent model with extended thinking for long-horizon and multi-turn tool use
Coding-optimized GPT model for repository edits, reviews, and agentic software work
DeepSeek chat model for instruction following, coding, and analysis
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,...
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...
Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs
Low-latency Gemini model for high-volume multimodal and agent workloads
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)
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...
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...
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
| Model | Creator | Score | Inputs | Context | Input | Output | Released | Compare |
|---|---|---|---|---|---|---|---|---|
| Nemotron 3 Ultra 550B A55Bnvidia/nemotron-3-ultra-550b-a55b | 1156.0 | 1M | $0.5 | $2.5 | 2026-06-04 | |||
| MiniMax: MiniMax M2minimax/minimax-m2 | 1156.0 | 204.8K | $0.255 | $1.02 | — | |||
| Mistral: Mistral Large 3 2512mistralai/mistral-large-2512 | 1152.0 | 262.144K | $0.5 | $1.5 | — | |||
| Qwen: Qwen3.5 Plus 2026-02-15qwen/qwen3.5-plus-02-15 | 1152.0 | 1M | $0.26 | $1.56 | — | |||
| Mistral: Mistral Large 3 2512 (batch)mistralai/mistral-large-2512:batch | 1152.0 | 262.144K | $0.25 | $0.75 | — | |||
| Gemini 2.5 Flashgoogle/gemini-2.5-flash | 1149.0 | 1.04858M | $0.3 | $2.5 | 2025-06-17 | |||
| Google: Gemini 2.5 Flash (batch)google/gemini-2.5-flash:batch | 1149.0 | 1.04858M | $0.15 | $1.25 | — | |||
| OpenAI: GPT-5 Mini (batch)openai/gpt-5-mini:batch | 1146.0 | 400K | $0.125 | $1 | — | |||
| GPT-5 Miniopenai/gpt-5-mini | 1146.0 | 400K | $0.25 | $2 | 2025-08-07 | |||
| DeepSeek V4 Flashdeepseek/deepseek-v4-flash | 1142.0 | 1M | $0.15 | $0.6 | 2026-04-24 | |||
| Hy3tencent/hy3 | 1141.0 | 256K | $0.066 | $0.26 | 2026-07-06 | |||
| Anthropic: Claude Haiku 4.5anthropic/claude-haiku-4.5 | 1140.0 | 200K | $1 | $5 | — | |||
| Anthropic: Claude Haiku 4.5 (batch)anthropic/claude-haiku-4.5:batch | 1140.0 | 200K | $0.5 | $2.5 | — | |||
| GPT-4.1openai/gpt-4.1 | 1118.0 | 1.04758M | $2 | $8 | 2025-04-14 | |||
| OpenAI: GPT-4.1 (batch)openai/gpt-4.1:batch | 1118.0 | 1.04758M | $1 | $4 | — | |||
| Qwen: Qwen3 Coder 480B A35B (free)qwen/qwen3-coder:free | 1116.0 | 262K | Free | Free | — | |||
| Qwen: Qwen3 Maxqwen/qwen3-max | 1116.0 | 262.144K | $0.78 | $3.9 | — | |||
| Trinity Large Thinkingarcee-ai/trinity-large-thinking | 1114.0 | 524.288K | $0.25 | $0.9 | 2026-04-01 | |||
| GPT-5.1 Codex miniopenai/gpt-5.1-codex-mini | 1113.0 | 400K | $0.22 | $1.8 | 2025-11-13 | |||
| DeepSeek Chatdeepseek/deepseek-chat | 1104.0 | 1M | $0.147 | $0.295 | 2025-12-01 | |||
| Qwen: Qwen3 Coder 30B A3B Instructqwen/qwen3-coder-30b-a3b-instruct | 1098.0 | 262.144K | $0.07 | $0.28 | — | |||
| Qwen: Qwen3 Coder 480B A35Bqwen/qwen3-coder | 1097.0 | 262.144K | $0.3 | $1 | — | |||
| Qwen: Qwen3 235B A22B Instruct 2507qwen/qwen3-235b-a22b-2507 | 1085.0 | 262.144K | $0.087 | $0.35 | — | |||
| OpenAI: GPT-5 Nano (batch)openai/gpt-5-nano:batch | 1071.0 | 400K | $0.025 | $0.2 | — | |||
| GPT-5 Nanoopenai/gpt-5-nano | 1071.0 | 400K | $0.05 | $0.4 | 2025-08-07 | |||
| Gemini 3.1 Flash Lite Previewgoogle/gemini-3.1-flash-lite-preview | 1061.0 | 1.04858M | $0.25 | $1.5 | 2026-03-03 | |||
| GPT-4.1 miniopenai/gpt-4.1-mini | 1048.0 | 1.04758M | $0.4 | $1.6 | 2025-04-14 | |||
| OpenAI: GPT-4.1 Mini (batch)openai/gpt-4.1-mini:batch | 1048.0 | 1.04758M | $0.2 | $0.8 | — | |||
| Mistral: Codestral 2508 (batch)mistralai/codestral-2508:batch | 1033.0 | 256K | $0.15 | $0.45 | — | |||
| Mistral: Codestral 2508mistralai/codestral-2508 | 1033.0 | 256K | $0.3 | $0.9 | — | |||
| o4-miniopenai/o4-mini | 1006.0 | 200K | $1.1 | $4.4 | 2025-04-16 | |||
| OpenAI: o4 Mini (batch)openai/o4-mini:batch | 1006.0 | 200K | $0.55 | $2.2 | — | |||
| Meta: Llama 4 Scoutmeta-llama/llama-4-scout | 909.0 | 327.68K | $0.1 | $0.3 | — | |||
| OpenAI: GPT-4.1 Nano (batch)openai/gpt-4.1-nano:batch | 906.0 | 1.04758M | $0.05 | $0.2 | — | |||
| GPT-4.1 nanoopenai/gpt-4.1-nano | 906.0 | 1.04758M | $0.1 | $0.4 | 2025-04-14 |