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

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

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

Qwen instruction model for multilingual chat, reasoning, and tool use

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

Hosted Qwen coder for software agents, repo edits, and long-context code