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...
Models
Every model in the catalog with source-linked pricing, context limits, provider availability, and published benchmark results.
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...
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...
Ring-2.6-1T is a 1T-parameter-scale thinking model with 63B active parameters, built for real-world agent workflows that require both strong capability and operational efficiency. It is optimized for coding agents, tool...
Grok 4.3 is a reasoning model from SpaceXAI. It accepts text and image inputs with text output, and is suited for agentic workflows, instruction-following tasks, and applications requiring high factual...
Grok 4.3 is a reasoning model from SpaceXAI. It accepts text and image inputs with text output, and is suited for agentic workflows, instruction-following tasks, and applications requiring high factual...
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...
O-series reasoning model for hard analysis, math, coding, and planning
The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learning to reason...
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...
Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows
GPT-5 is OpenAI’s most advanced model, offering major improvements in reasoning, code quality, and user experience. It is optimized for complex tasks that require step-by-step reasoning, instruction following, and accuracy...
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...
Claude Sonnet 4 significantly enhances the capabilities of its predecessor, Sonnet 3.7, excelling in both coding and reasoning tasks with improved precision and controllability. Achieving state-of-the-art performance on SWE-bench (72.7%),...
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...
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...
Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per...
Low-latency Gemini model for high-volume multimodal and agent workloads
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...
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...
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...
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...
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...
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...
Mistral Small 4 is the next major release in the Mistral Small family, unifying the capabilities of several flagship Mistral models into a single system. It combines strong reasoning from...
Mistral Small 4 is the next major release in the Mistral Small family, unifying the capabilities of several flagship Mistral models into a single system. It combines strong reasoning from...
Ling 3.0 Tiny is a mixture-of-experts model from InclusionAI, with 1.3B active parameters out of 7.9B total. It is designed for responsive agents, instruction following, and multi-turn conversations, with switchable...
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....
GPT model for general reasoning, writing, coding, and tool-assisted tasks
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...
Multimodal reasoning model for visual analysis, planning, and tool use
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...
Compact GPT model for low-latency assistance and high-volume workloads
The latest GPT-4 Turbo model with vision capabilities. Vision requests can now use JSON mode and function calling. Training data: up to December 2023.
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...
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...
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...
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.
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...
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...
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...
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...
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...
Small GPT-5 for responsive agents, coding help, and everyday automation
| Model | Creator | Score | Inputs | Context | Input | Output | Released | Compare |
|---|---|---|---|---|---|---|---|---|
| Google: Gemma 4 31B (batch)google/gemma-4-31b-it:batch | 43.4 | 262.144K | $0.39 | $0.97 | — | |||
| Google: Gemma 4 31B (free)google/gemma-4-31b-it:free | 43.4 | 262.144K | Free | Free | — | |||
| Qwen: Qwen3.5-122B-A10Bqwen/qwen3.5-122b-a10b | 43.3 | 262.144K | $0.4 | $3.2 | — | |||
| inclusionAI: Ring-2.6-1Tinclusionai/ring-2.6-1t | 42.8 | 262.144K | $0.075 | $0.625 | — | |||
| SpaceXAI: Grok 4.3x-ai/grok-4.3 | 42.2 | 1M | $1.25 | $2.5 | — | |||
| SpaceXAI: Grok 4.3 (batch)x-ai/grok-4.3:batch | 42.2 | 1M | $1 | $2 | — | |||
| Qwen: Qwen3.6 35B A3Bqwen/qwen3.6-35b-a3b | 41.9 | 262.144K | $0.1 | $0.95 | — | |||
| o1openai/o1 | 39.7 | 200K | $15 | $60 | 2024-12-05 | |||
| OpenAI: o1 (batch)openai/o1:batch | 39.7 | 200K | $7.5 | $30 | — | |||
| Google: Gemma 4 26B A4B (free)google/gemma-4-26b-a4b-it:free | 39.3 | 262.144K | Free | Free | — | |||
| GPT-5openai/gpt-5 | 37.8 | 400K | $1.25 | $10 | 2025-08-07 | |||
| OpenAI: GPT-5 (batch)openai/gpt-5:batch | 37.8 | 400K | $0.625 | $5 | — | |||
| NVIDIA: Nemotron 3 Super (free)nvidia/nemotron-3-super-120b-a12b:free | 37.7 | 262.144K | Free | Free | — | |||
| Anthropic: Claude Sonnet 4anthropic/claude-sonnet-4 | 37.6 | 200K | $3 | $15 | — | |||
| Qwen: Qwen3.5-35B-A3Bqwen/qwen3.5-35b-a3b | 37.0 | 262.144K | $0.14 | $1 | — | |||
| Cohere: North Mini Code (free)cohere/north-mini-code:free | 36.5 | 256K | Free | Free | — | |||
| Qwen: Qwen3 Coder Nextqwen/qwen3-coder-next | 36.2 | 262.144K | $0.12 | $0.8 | — | |||
| Gemini 3.1 Flash Lite Previewgoogle/gemini-3.1-flash-lite-preview | 34.7 | 1.04858M | $0.25 | $1.5 | 2026-03-03 | |||
| Gemini 2.5 Progoogle/gemini-2.5-pro | 33.3 | 1.04858M | $1.25 | $10 | 2025-06-17 | |||
| Google: Gemini 2.5 Pro (batch)google/gemini-2.5-pro:batch | 33.3 | 1.04858M | $0.625 | $5 | — | |||
| Mistral: Devstral 2 2512mistralai/devstral-2512 | 31.3 | 262.144K | $0.4 | $2 | — | |||
| Mercury 2inception/mercury-2 | 31.1 | 128K | $0.25 | $0.75 | 2026-02-24 | |||
| OpenAI: gpt-oss-120b (batch)openai/gpt-oss-120b:batch | 30.4 | 131.072K | $0.03 | $0.136 | — | |||
| OpenAI: gpt-oss-120b (free)openai/gpt-oss-120b:free | 30.4 | 131.072K | Free | Free | — | |||
| Qwen: Qwen3.5-9B (batch)qwen/qwen3.5-9b:batch | 28.7 | 262.144K | $0.17 | $0.25 | — | |||
| NVIDIA: Nemotron 3.5 Lightning (free)nvidia/nemotron-3.5-lightning:free | 26.8 | 1M | Free | Free | — | |||
| Mistral: Mistral Small 4mistralai/mistral-small-2603 | 26.6 | 262.144K | $0.15 | $0.6 | — | |||
| Mistral: Mistral Small 4 (batch)mistralai/mistral-small-2603:batch | 26.6 | 262.144K | $0.075 | $0.3 | — | |||
| inclusionAI: Ling 3.0 Tiny (free)inclusionai/ling-3.0-tiny:free | 26.5 | 262.144K | Free | Free | — | |||
| inclusionAI: Ling-2.6-flashinclusionai/ling-2.6-flash | 25.3 | 262.144K | $0.01 | $0.03 | — | |||
| GPT-4o (2024-05-13)openai/gpt-4o-2024-05-13 | 24.2 | 128K | $5 | $15 | 2024-05-13 | |||
| Qwen: Qwen3.5-9Bqwen/qwen3.5-9b | 23.5 | 262.144K | $0.17 | $0.25 | — | |||
| Nova 2 Liteamazon/nova-2-lite-v1 | 23.0 | 1M | $0.3 | $2.5 | 2025-12-02 | |||
| Qwen: Qwen3 235B A22B Thinking 2507qwen/qwen3-235b-a22b-thinking-2507 | 22.1 | 128K | $0.45 | $3.5 | — | |||
| GPT-4 Turboopenai/gpt-4-turbo | 21.5 | 128K | $10 | $30 | 2023-11-06 | |||
| OpenAI: GPT-4 Turbo (batch)openai/gpt-4-turbo:batch | 21.5 | 128K | $5 | $15 | — | |||
| OpenAI: gpt-oss-20b (batch)openai/gpt-oss-20b:batch | 20.7 | 131.072K | $0.024 | $0.112 | — | |||
| OpenAI: gpt-oss-20b (free)openai/gpt-oss-20b:free | 20.7 | 131.072K | Free | Free | — | |||
| Mistral: Mistral Medium 3.1mistralai/mistral-medium-3.1 | 20.5 | 131.072K | $0.4 | $2 | — | |||
| Mistral: Mistral Medium 3.1 (batch)mistralai/mistral-medium-3.1:batch | 20.5 | 131.072K | $0.2 | $1 | — | |||
| GPT-4.1 miniopenai/gpt-4.1-mini | 20.2 | 1.04758M | $0.4 | $1.6 | 2025-04-14 | |||
| OpenAI: GPT-4.1 Mini (batch)openai/gpt-4.1-mini:batch | 20.2 | 1.04758M | $0.2 | $0.8 | — | |||
| Mistral: Mistral Large 3 2512mistralai/mistral-large-2512 | 20.1 | 262.144K | $0.5 | $1.5 | — | |||
| Mistral: Mistral Large 3 2512 (batch)mistralai/mistral-large-2512:batch | 20.1 | 262.144K | $0.25 | $0.75 | — | |||
| Qwen: Qwen3 Next 80B A3B Thinkingqwen/qwen3-next-80b-a3b-thinking | 17.4 | 262.144K | $0.15 | $1.2 | — | |||
| Meta: Llama 4 Maverickmeta-llama/llama-4-maverick | 16.3 | 128K | $0.188 | $0.652 | — | |||
| OpenAI: o3 Mini Highopenai/o3-mini-high | 16.3 | 200K | $1.1 | $4.4 | — | |||
| OpenAI: o3 Mini High (batch)openai/o3-mini-high:batch | 16.3 | 200K | $0.55 | $2.2 | — | |||
| Upstage: Solar Pro 3upstage/solar-pro-3 | 16.2 | 131.072K | $0.15 | $0.6 | — | |||
| GPT-5 Miniopenai/gpt-5-mini | 15.6 | 400K | $0.25 | $2 | 2025-08-07 |