Qwen3.6-27B 在多数编程基准测试中击败了规模大得多的前代模型
阅读原文· the-decoder.com阿里巴巴新发布的开源模型 Qwen3.6-27B 在多项编程基准测试中超越了其前代模型。该模型仅拥有 270 亿参数，而其前代模型的参数量是其 15 倍。这一结果表明，模型在代码能力上实现了显著的效率提升，以更小的规模取得了更优的性能。
Qwen3.6-27B beats much larger predecessor on most coding benchmarks
Alibaba has released Qwen3.6-27B, a new dense open-source model with 27 billion parameters. According to Alibaba, the model outperforms its much larger predecessor, Qwen3.5-397B-A17B (397 billion parameters) on nearly every coding benchmark tested. It scored 77.2 on SWE-bench Verified compared to 76.2, and 59.3 on Terminal-Bench 2.0 compared to 52.5.
The model handles both text and multimodal reasoning. As a "dense" model, it's easier to run than the more complex MoE (Mixture of Experts) architectures, which activate different sub-models depending on the task.
Qwen3.6-27B is available through Qwen Studio, the Alibaba Cloud Model Studio API, and as open weights on Hugging Face and ModelScope. It's aimed at developers who want strong coding performance without dealing with a massive model.