Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35 billion total parameters and 3 billion active parameters per token. It uses a hybrid sparse mixture-of-experts architecture combining Gated...
Models
Every model in the catalog with source-linked pricing, context limits, provider availability, and published benchmark results.
The Qwen3.5 Series 35B-A3B is a native vision-language model designed with a hybrid architecture that integrates linear attention mechanisms and a sparse mixture-of-experts model, achieving higher inference efficiency. Its overall...
The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers...
Reasoning-first Gemini preview for agentic coding and complex problem solving
Gemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage across complex workflows. Building on the multimodal foundation...
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...
The Qwen3.5 122B-A10B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. In terms of...
Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI. It supports text and image inputs with text output, and is designed for agentic workflows, coding, and complex...
Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI. It supports text and image inputs with text output, and is designed for agentic workflows, coding, and complex...
Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architecture. It uses a unified vision-language design...
DeepSeek-V3.1 Terminus is an update to [DeepSeek V3.1](/deepseek/deepseek-chat-v3.1) that maintains the model's original capabilities while addressing issues reported by users, including language consistency and agent capabilities, further optimizing the model's...
Small GPT-5 for responsive agents, coding help, and everyday automation
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....
Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...
Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...
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...
NVIDIA Nemotron 3.5 Lightning is an open mixture-of-experts model from NVIDIA, with 3B active parameters out of 30B total. It is suited for high-throughput agentic workloads and specialized tasks that...
Multimodal reasoning model for visual analysis, planning, and tool use
gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for...
Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at...
Ling-2.6-flash is an instant (instruct) model from inclusionAI with 104B total parameters and 7.4B active parameters, designed for real-world agents that require fast responses, strong execution, and high token efficiency....
Devstral 2 is a state-of-the-art open-source model by Mistral AI specializing in agentic coding. It is a 123B-parameter dense transformer model supporting a 256K context window. Devstral 2 supports exploring...
Qwen3-Next-80B-A3B-Thinking is a reasoning-first chat model in the Qwen3-Next line that outputs structured “thinking” traces by default. It’s designed for hard multi-step problems; math proofs, code synthesis/debugging, logic, and agentic...
NVIDIA Nemotron 3 Nano 30B A3B is a small language MoE model with highest compute efficiency and accuracy for developers to build specialized agentic AI systems. The model is fully...
Mistral Medium 3.1 is an updated version of Mistral Medium 3, which is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances...
Mistral Medium 3.1 is an updated version of Mistral Medium 3, which is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances...
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...
NVIDIA Nemotron 3 Super is a 120B-parameter open hybrid MoE model, activating just 12B parameters for maximum compute efficiency and accuracy in complex multi-agent applications. Built on a hybrid Mamba-Transformer...
OpenAI o3-mini-high is the same model as [o3-mini](/openai/o3-mini) with reasoning_effort set to high. o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and...
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...
Low-latency Gemini model for high-volume multimodal and agent workloads
Reasoning model for deliberate analysis, multi-step problem solving, and tool use
Solar Pro 3 is Upstage's powerful Mixture-of-Experts (MoE) language model. With 102B total parameters and 12B active parameters per forward pass, it delivers exceptional performance while maintaining computational efficiency. Optimized...
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...
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...
gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for...
Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architecture. It uses a unified vision-language design...
North Mini Code is Cohere's first agentic coding model and the debut of its North family. A sparse mixture-of-experts model with 30B total parameters and 3B active, it is optimized...
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...
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.
Small omni GPT for cheap multimodal assistance and production-scale traffic
GPT-4o mini is OpenAI's newest model after [GPT-4 Omni](/models/openai/gpt-4o), supporting both text and image inputs with text outputs. As their most advanced small model, it is many multiples more affordable...
OpenAI o3-mini-high is the same model as [o3-mini](/openai/o3-mini) with reasoning_effort set to high. o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and...
Qwen3-14B is a dense 14.8B parameter causal language model from the Qwen3 series, designed for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for...
Qwen3-30B-A3B-Thinking-2507 is a 30B parameter Mixture-of-Experts reasoning model optimized for complex tasks requiring extended multi-step thinking. The model is designed specifically for “thinking mode,” where internal reasoning traces are separated...
| Model | Creator | Score | Inputs | Context | Input | Output | Released | Compare |
|---|---|---|---|---|---|---|---|---|
| Qwen: Qwen3.6 35B A3Bqwen/qwen3.6-35b-a3b | 13.1 | 262.144K | $0.1 | $0.95 | — | |||
| Qwen: Qwen3.5-35B-A3Bqwen/qwen3.5-35b-a3b | 11.8 | 262.144K | $0.14 | $1 | — | |||
| Qwen: Qwen3.5 397B A17Bqwen/qwen3.5-397b-a17b | 8.3 | 262.144K | $0.5 | $3.6 | — | |||
| Gemini 3.1 Pro Previewgoogle/gemini-3.1-pro-preview | 8.2 | 1.04858M | $2 | $12 | 2026-02-19 | |||
| Google: Gemini 3.1 Pro Preview (batch)google/gemini-3.1-pro-preview:batch | 8.2 | 1.04858M | $1 | $6 | — | |||
| Anthropic: Claude Haiku 4.5anthropic/claude-haiku-4.5 | 8.0 | 200K | $1 | $5 | — | |||
| Anthropic: Claude Haiku 4.5 (batch)anthropic/claude-haiku-4.5:batch | 8.0 | 200K | $0.5 | $2.5 | — | |||
| Qwen: Qwen3.5-122B-A10Bqwen/qwen3.5-122b-a10b | 7.6 | 262.144K | $0.4 | $3.2 | — | |||
| Mistral: Mistral Medium 3.5mistralai/mistral-medium-3-5 | 7.0 | 262.144K | $1.5 | $7.5 | — | |||
| Mistral: Mistral Medium 3.5 (batch)mistralai/mistral-medium-3-5:batch | 7.0 | 262.144K | $0.75 | $3.75 | — | |||
| Qwen: Qwen3.5-9B (batch)qwen/qwen3.5-9b:batch | 7.0 | 262.144K | $0.17 | $0.25 | — | |||
| DeepSeek: DeepSeek V3.1 Terminusdeepseek/deepseek-v3.1-terminus | 6.8 | 163.84K | $0.27 | $1 | — | |||
| GPT-5 Miniopenai/gpt-5-mini | 6.8 | 400K | $0.25 | $2 | 2025-08-07 | |||
| OpenAI: GPT-5 Mini (batch)openai/gpt-5-mini:batch | 6.8 | 400K | $0.125 | $1 | — | |||
| Google: Gemma 4 31B (batch)google/gemma-4-31b-it:batch | 6.7 | 262.144K | $0.39 | $0.97 | — | |||
| Google: Gemma 4 31B (free)google/gemma-4-31b-it:free | 4.2 | 262.144K | Free | Free | — | |||
| OpenAI: gpt-oss-120b (batch)openai/gpt-oss-120b:batch | 3.7 | 131.072K | $0.03 | $0.136 | — | |||
| NVIDIA: Nemotron 3.5 Lightning (free)nvidia/nemotron-3.5-lightning:free | 3.5 | 1M | Free | Free | — | |||
| Nova 2 Liteamazon/nova-2-lite-v1 | 3.1 | 1M | $0.3 | $2.5 | 2025-12-02 | |||
| OpenAI: gpt-oss-20b (free)openai/gpt-oss-20b:free | 3.1 | 131.072K | Free | Free | — | |||
| Google: Gemma 4 26B A4B (free)google/gemma-4-26b-a4b-it:free | 2.9 | 262.144K | Free | Free | — | |||
| inclusionAI: Ling-2.6-flashinclusionai/ling-2.6-flash | 2.3 | 262.144K | $0.01 | $0.03 | — | |||
| Mistral: Devstral 2 2512mistralai/devstral-2512 | 2.3 | 262.144K | $0.4 | $2 | — | |||
| Qwen: Qwen3 Next 80B A3B Thinkingqwen/qwen3-next-80b-a3b-thinking | 2.1 | 262.144K | $0.15 | $1.2 | — | |||
| NVIDIA: Nemotron 3 Nano 30B A3B (free)nvidia/nemotron-3-nano-30b-a3b:free | 2.0 | 256K | Free | Free | — | |||
| Mistral: Mistral Medium 3.1mistralai/mistral-medium-3.1 | 1.9 | 131.072K | $0.4 | $2 | — | |||
| Mistral: Mistral Medium 3.1 (batch)mistralai/mistral-medium-3.1:batch | 1.9 | 131.072K | $0.2 | $1 | — | |||
| GPT-4.1 miniopenai/gpt-4.1-mini | 1.8 | 1.04758M | $0.4 | $1.6 | 2025-04-14 | |||
| OpenAI: GPT-4.1 Mini (batch)openai/gpt-4.1-mini:batch | 1.8 | 1.04758M | $0.2 | $0.8 | — | |||
| NVIDIA: Nemotron 3 Super (free)nvidia/nemotron-3-super-120b-a12b:free | 1.7 | 262.144K | Free | Free | — | |||
| OpenAI: o3 Mini High (batch)openai/o3-mini-high:batch | 1.7 | 200K | $0.55 | $2.2 | — | |||
| Gemini 2.5 Progoogle/gemini-2.5-pro | 1.6 | 1.04858M | $1.25 | $10 | 2025-06-17 | |||
| Google: Gemini 2.5 Pro (batch)google/gemini-2.5-pro:batch | 1.6 | 1.04858M | $0.625 | $5 | — | |||
| Gemini 3.1 Flash Lite Previewgoogle/gemini-3.1-flash-lite-preview | 1.6 | 1.04858M | $0.25 | $1.5 | 2026-03-03 | |||
| Mercury 2inception/mercury-2 | 1.6 | 128K | $0.25 | $0.75 | 2026-02-24 | |||
| Upstage: Solar Pro 3upstage/solar-pro-3 | 1.4 | 131.072K | $0.15 | $0.6 | — | |||
| Qwen: Qwen3 235B A22B Thinking 2507qwen/qwen3-235b-a22b-thinking-2507 | 1.3 | 128K | $0.45 | $3.5 | — | |||
| GPT-4.1 nanoopenai/gpt-4.1-nano | 1.2 | 1.04758M | $0.1 | $0.4 | 2025-04-14 | |||
| OpenAI: GPT-4.1 Nano (batch)openai/gpt-4.1-nano:batch | 1.2 | 1.04758M | $0.05 | $0.2 | — | |||
| OpenAI: gpt-oss-20b (batch)openai/gpt-oss-20b:batch | 1.2 | 131.072K | $0.024 | $0.112 | — | |||
| Qwen: Qwen3.5-9Bqwen/qwen3.5-9b | 1.2 | 262.144K | $0.17 | $0.25 | — | |||
| Cohere: North Mini Code (free)cohere/north-mini-code:free | 1.1 | 256K | Free | Free | — | |||
| Mistral: Ministral 3 14B 2512mistralai/ministral-14b-2512 | 1.1 | 262.144K | $0.2 | $0.2 | — | |||
| Mistral: Mistral Large 3 2512mistralai/mistral-large-2512 | 1.0 | 262.144K | $0.5 | $1.5 | — | |||
| Mistral: Mistral Large 3 2512 (batch)mistralai/mistral-large-2512:batch | 1.0 | 262.144K | $0.25 | $0.75 | — | |||
| GPT-4o miniopenai/gpt-4o-mini | 1.0 | 128K | $0.15 | $0.6 | 2024-07-18 | |||
| OpenAI: GPT-4o-mini (batch)openai/gpt-4o-mini:batch | 1.0 | 128K | $0.075 | $0.3 | — | |||
| OpenAI: o3 Mini Highopenai/o3-mini-high | 0.9 | 200K | $1.1 | $4.4 | — | |||
| Qwen: Qwen3 14Bqwen/qwen3-14b | 0.9 | 40.96K | $0.12 | $0.24 | — | |||
| Qwen: Qwen3 30B A3B Thinking 2507qwen/qwen3-30b-a3b-thinking-2507 | 0.9 | 81.92K | $0.2 | $2.4 | — |