Guide

Open Llama with long-context vision for efficient multimodal agents

Open multimodal Llama model for long-context analysis and efficient agents

Open multimodal Llama model for strong reasoning and fast responses

Open multimodal Llama model for strong reasoning and fast responses

Open multimodal Llama model for long-context analysis and efficient agents

Qwen3 235B A22B Instruct 2507 TEE from Chutes - text input, 262,144 token context

Dense open Qwen model for self-hosted chat, reasoning, and coding

Mistral-7B-Instruct-v0.3 from AWS Bedrock - text input, 127,000 token context

Mixtral-8x7B-Instruct-v0.1 from AWS Bedrock - text input, 32,000 token context

Dense open Qwen model for self-hosted chat, reasoning, and coding

Dense open Qwen model for self-hosted chat, reasoning, and coding

Smaller Qwen coder for efficient local agents and repo-level fixes

Dense open Qwen model for self-hosted chat, reasoning, and coding

Large open Qwen MoE for multilingual reasoning, coding, and tool use

Dense open Qwen model for self-hosted chat, reasoning, and coding

Open Qwen coding heavyweight for repository reasoning and agentic engineering

Smaller Qwen coder for efficient local agents and repo-level fixes

Large open Qwen MoE for multilingual reasoning, coding, and tool use

Qwen vision-language model for visual reasoning, documents, and agent tasks

Qwen vision-language model for visual reasoning, documents, and agent tasks

Qwen instruction model for multilingual chat, reasoning, and tool use

Qwen instruction model for multilingual chat, reasoning, and tool use

Qwen vision-language model for visual reasoning, documents, and agent tasks

DeepSeek chat model for instruction following, coding, and analysis

Open Gemma instruction model for efficient chat and self-hosted deployments

Qwen vision-language model for visual reasoning, documents, and agent tasks

Qwen2.5-VL-32B is a multimodal vision-language model fine-tuned through reinforcement learning for enhanced mathematical reasoning, structured outputs, and visual problem-solving capabilities. It excels at visual analysis tasks, including object recognition, textual...

DeepSeek V3, a 685B-parameter, mixture-of-experts model, is the latest iteration of the flagship chat model family from the DeepSeek team. It succeeds the [DeepSeek V3](/deepseek/deepseek-chat-v3) model and performs really well...

Deepseek V3 03-24 from Fireworks AI - text input, 160,000 token context

March 2025 checkpoint of DeepSeek-V3 with improved reasoning and coding

DeepSeek chat model for instruction following, coding, and analysis

The o1 series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o1-pro model uses more compute to think harder and provide...

The o1 series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o1-pro model uses more compute to think harder and provide...

O-series reasoning model for hard analysis, math, coding, and planning

Venice Medium from Venice AI - text, image input, 128,000 token context

Venice Uncensored 1.1 from Venice AI - text input, 32,000 token context

Mistral Small 3.1 24B Instruct is an upgraded variant of Mistral Small 3 (2501), featuring 24 billion parameters with advanced multimodal capabilities. It provides state-of-the-art performance in text-based reasoning and vision tasks, including image analysis, programming, mathematical reasoning, and multilingual support across dozens of languages. Equipped with an extensive 128k token context window and optimized for efficient local inference, it supports use cases such as conversational agents, function calling, long-document comprehension, and privacy-sensitive deployments. The updated version is [Mistral Small 3.2](mistralai/mistral-small-3.2-24b-instruct)

Mistral Small 3.1 24B Instruct is an upgraded variant of Mistral Small 3 (2501), featuring 24 billion parameters with advanced multimodal capabilities. It provides state-of-the-art performance in text-based reasoning and...

Mistral reasoning model for transparent analysis, math, and complex decisions

Mistral reasoning model for transparent analysis, math, and complex decisions

OLMo-2 32B Instruct is a supervised instruction-finetuned variant of the OLMo-2 32B March 2025 base model. It excels in complex reasoning and instruction-following tasks across diverse benchmarks such as GSM8K,...

Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities,...

Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities,...

Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities,...

Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities,...

Command A is an open-weights 111B parameter model with a 256k context window focused on delivering great performance across agentic, multilingual, and coding use cases. Compared to other leading proprietary...

Gemma 3 4B from Google - text, image input, 32,768 token context

Gemma 3 12B from Google - text, image input, 32,768 token context

Claude Sonnet 3.7 (Latest) from DeepInfra - text, image input, 200,000 token context

Cohere command model for multilingual enterprise agents, tools, and chat

Cohere command model for multilingual enterprise agents, tools, and chat