Models

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

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

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

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

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

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

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

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

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

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

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

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

Flagship Mistral model for advanced reasoning, coding, and multilingual work

Mistral's largest general model for enterprise agents, coding, and multilingual reasoning

Open multimodal Llama model for image understanding, captioning, and visual QA