Qwen3.5

In plain words

Qwen3.5 is an open-weight vision-language model designed for agentic tasks that require reasoning over long sequences. It combines linear attention with mixture-of-experts architecture to provide the reasoning capabilities of a 397-billion-parameter model while maintaining inference speeds comparable to a 17-billion-parameter model. The system handles both text and images natively, making it suitable for developers building autonomous AI agents.

written from the facts on this page · September 2026

From the sources

An open-weight, native vision-language model built for long-horizon agentic tasks. Its hybrid architecture (linear attention + MoE) delivers the capabilities of a 397B giant with the inference speed of a 17B model.

Qwen Studio offers comprehensive functionality spanning chatbot, image and video understanding, image generation, document processing, web search integration, tool utilization, and artifacts.

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  Qwen3.5 SmallMar 2026 · huggingface.co · ▲355

  0.8B-9B native multimodal w/ more intelligence, less compute

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  Qwen3.6-35B-A3BApr 2026 · qwen.ai · ▲124

  The open sparse MoE model for agentic coding

• 
  Qwen3-235B-A22B-Thinking-25072025 · huggingface.co · ▲262

  Qwen's most advanced reasoning model yet

• 
  Qwen3.6-27BApr 2026 · qwen.ai · ▲120

  The sweet-spot open dense model for coding agents

• 
  Qwen3-Coder2025 · qwenlm.github.io · ▲248

  A powerful open model for agentic coding tasks

• 
  Qwen3.6-PlusApr 2026 · qwen.ai · ▲139

  Multimodal AI optimized for real-world coding agents

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