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.
NVIDIA Nemotron 3 Ultra is an open frontier-reasoning and orchestration model from NVIDIA, with 55B active parameters out of 550B total (MoE). Built on a hybrid Transformer-Mamba mixture-of-experts architecture, it...
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
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,...
Google's proven reasoning model for coding, math, and multimodal analysis
Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy...
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...
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...
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...
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...
Coding-optimized GPT model for repository edits, reviews, and agentic software work
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.
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.
Reasoning-optimized 398B MoE agent model with extended thinking for long-horizon and multi-turn tool use
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...
Long-lived GPT workhorse for coding, instruction following, and production apps
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 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...
DeepSeek chat model for instruction following, coding, and analysis
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 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...
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....
Deliberate o-series reasoner for hard math, coding, and multi-step analysis
Low-latency Gemini model for high-volume multimodal and agent workloads
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...
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.
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'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-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,...
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 |
|---|---|---|---|---|---|---|---|---|
| Nemotron 3 Ultra 550B A55Bnvidia/nemotron-3-ultra-550b-a55b | 1155.0 | 1M | $0.5 | $2.5 | 2026-06-04 | |||
| NVIDIA: Nemotron 3 Ultra (free)nvidia/nemotron-3-ultra-550b-a55b:free | 1155.0 | 1M | Free | Free | — | |||
| OpenAI: GPT-5 Mini (batch)openai/gpt-5-mini:batch | 1152.0 | 400K | $0.125 | $1 | — | |||
| GPT-5 Miniopenai/gpt-5-mini | 1152.0 | 400K | $0.25 | $2 | 2025-08-07 | |||
| MiniMax: MiniMax M2minimax/minimax-m2 | 1141.0 | 204.8K | $0.255 | $1.02 | — | |||
| Gemini 2.5 Progoogle/gemini-2.5-pro | 1134.0 | 1.04858M | $1.25 | $10 | 2025-06-17 | |||
| Google: Gemini 2.5 Pro (batch)google/gemini-2.5-pro:batch | 1134.0 | 1.04858M | $0.625 | $5 | — | |||
| Qwen: Qwen3.5 Plus 2026-02-15qwen/qwen3.5-plus-02-15 | 1128.0 | 1M | $0.26 | $1.56 | — | |||
| Qwen: Qwen3 Coder 480B A35Bqwen/qwen3-coder | 1122.0 | 262.144K | $0.3 | $1 | — | |||
| Anthropic: Claude Haiku 4.5anthropic/claude-haiku-4.5 | 1120.0 | 200K | $1 | $5 | — | |||
| Anthropic: Claude Haiku 4.5 (batch)anthropic/claude-haiku-4.5:batch | 1120.0 | 200K | $0.5 | $2.5 | — | |||
| Qwen: Qwen3 Maxqwen/qwen3-max | 1117.0 | 262.144K | $0.78 | $3.9 | — | |||
| GPT-5.1 Codex miniopenai/gpt-5.1-codex-mini | 1115.0 | 400K | $0.22 | $1.8 | 2025-11-13 | |||
| Mistral: Mistral Large 3 2512mistralai/mistral-large-2512 | 1103.0 | 262.144K | $0.5 | $1.5 | — | |||
| Mistral: Mistral Large 3 2512 (batch)mistralai/mistral-large-2512:batch | 1103.0 | 262.144K | $0.25 | $0.75 | — | |||
| Trinity Large Thinkingarcee-ai/trinity-large-thinking | 1102.0 | 524.288K | $0.25 | $0.9 | 2026-04-01 | |||
| OpenAI: GPT-4.1 (batch)openai/gpt-4.1:batch | 1102.0 | 1.04758M | $1 | $4 | — | |||
| GPT-4.1openai/gpt-4.1 | 1102.0 | 1.04758M | $2 | $8 | 2025-04-14 | |||
| GPT-4.1 miniopenai/gpt-4.1-mini | 1093.0 | 1.04758M | $0.4 | $1.6 | 2025-04-14 | |||
| OpenAI: GPT-4.1 Mini (batch)openai/gpt-4.1-mini:batch | 1093.0 | 1.04758M | $0.2 | $0.8 | — | |||
| Gemini 2.5 Flashgoogle/gemini-2.5-flash | 1088.0 | 1.04858M | $0.3 | $2.5 | 2025-06-17 | |||
| Google: Gemini 2.5 Flash (batch)google/gemini-2.5-flash:batch | 1088.0 | 1.04858M | $0.15 | $1.25 | — | |||
| DeepSeek Chatdeepseek/deepseek-chat | 1076.0 | 1M | $0.147 | $0.295 | 2025-12-01 | |||
| GPT-5 Nanoopenai/gpt-5-nano | 1068.0 | 400K | $0.05 | $0.4 | 2025-08-07 | |||
| OpenAI: GPT-5 Nano (batch)openai/gpt-5-nano:batch | 1068.0 | 400K | $0.025 | $0.2 | — | |||
| Mistral: Ministral 3 14B 2512mistralai/ministral-14b-2512 | 1061.0 | 262.144K | $0.2 | $0.2 | — | |||
| OpenAI: o3 (batch)openai/o3:batch | 1057.0 | 200K | $1 | $4 | — | |||
| o3openai/o3 | 1057.0 | 200K | $2 | $8 | 2025-04-16 | |||
| Gemini 3.1 Flash Lite Previewgoogle/gemini-3.1-flash-lite-preview | 1052.0 | 1.04858M | $0.25 | $1.5 | 2026-03-03 | |||
| o4-miniopenai/o4-mini | 1026.0 | 200K | $1.1 | $4.4 | 2025-04-16 | |||
| OpenAI: o4 Mini (batch)openai/o4-mini:batch | 1026.0 | 200K | $0.55 | $2.2 | — | |||
| Mistral: Ministral 3 8B 2512mistralai/ministral-8b-2512 | 1013.0 | 262.144K | $0.15 | $0.15 | — | |||
| Mistral: Ministral 3 8B 2512 (batch)mistralai/ministral-8b-2512:batch | 1013.0 | 262.144K | $0.075 | $0.075 | — | |||
| GPT-4.1 nanoopenai/gpt-4.1-nano | 993.0 | 1.04758M | $0.1 | $0.4 | 2025-04-14 | |||
| OpenAI: GPT-4.1 Nano (batch)openai/gpt-4.1-nano:batch | 993.0 | 1.04758M | $0.05 | $0.2 | — | |||
| Mistral: Codestral 2508mistralai/codestral-2508 | 990.0 | 256K | $0.3 | $0.9 | — | |||
| Mistral: Codestral 2508 (batch)mistralai/codestral-2508:batch | 990.0 | 256K | $0.15 | $0.45 | — | |||
| Qwen: Qwen3 235B A22B Instruct 2507qwen/qwen3-235b-a22b-2507 | 974.0 | 262.144K | $0.087 | $0.35 | — | |||
| Meta: Llama 4 Scoutmeta-llama/llama-4-scout | 796.0 | 327.68K | $0.1 | $0.3 | — |