腾讯混元联合 LMArena 推出 WebCraftBench 基准

该基准覆盖口语化描述、指令不完整、需求范围不一等真实使用场景，让智能体实际操作生成的应用并进行评分。基准对 17 个模型排名，与 Code Arena 排行榜的相关性达 0.

89。在 197 组人工验证样本上，其评分与人类偏好一致率为 85.

3%。

Real-world app requests don’t come as perfect specs. Congrats to the @TencentHunyuan team on WebCraftBench! Built from 369 requests collected from their internal replica of Code Arena, it embraces the messy details of real human usage: informal language, incomplete instructions, different project scopes, and diverse preferences. Their benchmark tests how AI-built apps look, work, and deliver on those requests. Across 17 models, its rankings strongly correlate with our Code Arena leaderboard (0.89). What could you uncover from real human-AI conversations and Arena’s leaderboard history? Explore our open datasets at huggingface.co/lmarena-ai/dat… ! Tencent Hy @TencentHunyuan The AI says the site is done. Then the homepage errors, the buttons overlap, and it added a login flow you never asked for. 🙃 Introduces WebCraftBench: agents actually use the live app, coverage-guided exploration finds what never got reached, then we score aesthetics, usability, and whether the original request was met. On 197 human-validated pairs, it matches human preference 85.3% of the time. Paper: arxiv.org/abs/2609.15387 Z 🔗 View Quoted Tweet

本条情报归属 AITOP「论文」核心栏目，重点聚焦中国 AI 产业与国产大模型生态。在跨区域产业观察坐标中，该动态直接关联「AI 开发者工具链、Coding Agent 与工程化实践」「中美大模型技术代差与商业化对照」研究主线，反映出当前技术演进与商业落地的最新风向。涉及核心实体与技术议题包括：WebCraftBench、Tencent Hunyuan、LMArena、编程助手，读者可通过下方标签进入对应专题页查阅历史脉络与关联对比。

信源核验说明：本文原始线索采编自「lmarena.ai」（@lmarena_ai），经 AITOP 多维评分管线结构化提炼。截至目前，全网已有 2 家独立信源对该事件进行交叉印证与跟进报道（含 Hunyuan 等），属于近期高关注度行业信号。