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

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

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

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

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

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

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 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

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

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