Co-Design Bench揭示编程智能体短板
AI 总结
阿里巴巴与亚洲多所大学研究人员基于真实代码修改请求构建了Co-Design Bench，任务输入可包含图片、音频、视频和文档。论文称，GPT-6 Astra在十个受测模型中领先，平均满足约70%的任务要求，但仅26.4%的任务完全正确；成绩也会随智能体运行环境而变化。
深度见解
该基准以真实Web应用修改任务更严格地检验编程智能体，显示领先模型仍需人工收尾，也表明评估时必须同时考虑模型与运行环境。
AI coding agents still need human cleanup on nearly three out of four tasks in a real-world test
Jonathan Kemper View the LinkedIn Profile of Jonathan Kemper
Nov 8, 2026
ChatGPT-5.6 prompted by THE DECODER
Researchers from Alibaba and several Asian universities built a coding-agent benchmark from real user change requests. Even the best model fully completes only about one in four tasks, putting the near-perfect scores of older tests into perspective.
#Co-Design Bench#Alibaba#GPT-6 Astra#Claude Opus 5#Qwen3.8-Max#Qwen3.8-27B#Grok 4.6#GLM-5.2#WebCompass-edit#SWE-bench Verified