AI BriefingQwen3.6-35B-A3B: Agentic Coding Performance Unveiled for All Users
Key point
Qwen3.6-35B-A3B has been released, achieving large-model-class coding and multimodal performance with just 3 billion active parameters.
Details
Qwen3.6-35B-A3B is an open-source model that achieves both efficiency and performance using a sparse Mixture-of-Experts (MoE) architecture, where only 3 billion of its total 35 billion parameters are activated.
Compared to the previous generation, its agentic coding capabilities have been greatly improved, reaching a level competitive with large dense models such as Qwen3.5-27B and Gemma4-31B. It recorded high scores on major coding benchmarks including SWE-bench Verified (73.4), Terminal-Bench (51.5), and Claw-Eval (68.7).
Additionally, as a natively multimodal model, it achieved Claude Sonnet 4.5-level performance on vision-language tasks, and also demonstrated excellent performance in spatial intelligence and video understanding.
The model has been released via the Alibaba Cloud Model Studio API, Hugging Face, and ModelScope, and is supported with integration across various third-party coding tools such as OpenClaw, Claude Code, and Qwen Code. Notably, its preserve_thinking feature allows it to maintain reasoning traces suited for agentic tasks.
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