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

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 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

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

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

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

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

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

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

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

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

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

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