Models

2026-09-02 upgraded snapshot of Qwen3.8 Max with stronger coding, collaborative agents, and multimodal document understanding

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

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

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

Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows

2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows

Lightweight multimodal Qwen model for high-throughput text, image, and video tasks

Multimodal Qwen workhorse for long-context agents, visual inputs, and coding

Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks

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

Earlier Qwen multimodal workhorse for million-token agent and document tasks

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

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

Open-weight Qwen coding model for agents, repository edits, and multi-turn tool use

Flagship Qwen3 model for coding agents, complex reasoning, and tool use

Efficient Qwen thinking model for local reasoning, math, and coding agents