Models

DeepSeek V4.1 Flash model for reasoning and agentic coding

Open-weight experimental preview of the Qwen4 architecture: hybrid-attention MoE (125B total, 6B active) with vision encoder for coding, agent tasks, and image and video understanding

Native multimodal GLM model for efficient coding and long-horizon agent tasks

Mixture-of-experts coding-reasoning model for agentic software tasks, tool use, and image understanding

Dense 27B vision-language model for coding, agent tasks, and image and video understanding

Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.

Multimodal MoE reasoning model (276B total, 12B active) for text, image, and audio

Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work

Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio

Large coding-reasoning model for agentic software tasks and RL search

Open coding-reasoning model for repository tasks and self-improving agents

Open coding-reasoning model for repository tasks and self-improving agents

Large coding-reasoning model for agentic software tasks and RL search

Lower-latency Kimi Code variant for interactive edits and coding-agent loops

Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking

Safety model for policy screening, moderation, and risk-aware routing workflows

MiniMax multimodal model for long-context coding, perception, and agent planning

Newer StepFun flash model for faster agents, coding, and multimodal prompts

Cohere's stronger command model for multilingual agents and enterprise workflows

Balanced Mistral model for enterprise assistants, multilingual work, and tools

Balanced Mistral model for enterprise assistants, multilingual work, and tools

Open Nemotron omni model combining reasoning with text, vision, and audio

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

Open MiMo model for multimodal coding agents and long-context automation

Multimodal Kimi workhorse for agent loops, coding tasks, and visual context

Open multimodal Qwen MoE for local agents that need vision, audio, and code

Largest Gemma 4 instruction model for open, self-hosted chat and reasoning

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

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

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

Reranking model for improving retrieval quality in search and recommendation systems

Efficient Mistral model for fast chat, extraction, and production assistants

Fast Mistral production model for chat, extraction, and cost-sensitive agents

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

Turkish-language multimodal instruct model built on Gemma 3 12B for e-commerce text, chat, and image-text tasks

Large open Qwen multimodal MoE for visual agents and long technical tasks

Earlier Kimi frontier model for long-context agents, coding, and multimodal work

GLM vision model for visual reasoning, documents, and multimodal agents

Lightweight GLM vision model for visual reasoning, documents, and multimodal agents

Nemotron multimodal model for visual reasoning and agentic AI workflows

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

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

Cohere vision model for multilingual document analysis, OCR, and image understanding

Efficient Mistral model for fast chat, extraction, and production assistants

Open multimodal Llama for strong reasoning with efficient everyday serving

Open Llama with long-context vision for efficient multimodal agents

Efficient multimodal model for instruction following, coding, reasoning, and function calling