Models

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

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

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

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

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

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

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

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

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