打造真实用户场景的电脑助手评测基准，测试个性化任务完成能力。
MyPCBench: A Benchmark for Personally Intelligent Computer-Use Agents
- 构建包含17个模拟网页应用的个人化桌面环境，以真人角色为原型。
- 6款模型中最强者（Claude Opus 4.6）仅解决55.4%的任务，长流程任务易失败。
- 适合评估需跨应用、依赖历史数据的智能助理，推动真实场景落地。
现有电脑助手评测多在非个性化环境中进行，难以反映真实使用场景中助手需处理用户上下文、历史数据及登录账户的需求，尤其在网页任务上，无法对需登录或个人信息的网站进行实时测试。为此，我们提出MyPCBench，一个基于Linux桌面的评测基准，包含17个模拟真实世界的网页应用和完整桌面栈，所有设置围绕单一用户角色——《办公室》中的迈克尔·斯科特。定义了184项任务，均源自OpenClaw社区的真实请求。在统一的计算机+bash工具界面下，评测六款闭源与开源模型。结果显示，最佳模型Claude Opus 4.6仅成功完成55.4%的任务，是唯一超过50%的模型。失败集中于跨多应用、长轨迹的任务，凸显个性化带来的挑战。环境、任务集与代理框架已公开：https://mypcbench.com。
原文摘要 · Abstract (English)
Current benchmarks for computer-use agents evaluate models in impersonal environments. This leaves a gap between evaluation and deployment where personal assistants are expected to work across a user's whole digital life, including their context, historical data, and logged-in accounts. This gap is widest on web tasks, where live web evaluations cannot exercise sites that require logging in or personal information, the kind of site a real personal assistant has to drive. We introduce MyPCBench, which tests computer-use agents as personal assistants on a Linux desktop populated with 17 simulated real-world web applications and a full desktop stack, all seeded for one canonical persona, Michael Scott from The Office. We define 184 tasks in this environment, each inspired by a real request drawn from the OpenClaw community, and benchmark six closed and open-weight models with a uniform computer+bash tool surface. We find that the best model, Claude Opus 4.6, fully solves 55.4\% of the tasks, the only model above 50\%. Model failures cluster on tasks that span many applications and on long trajectories, where personalization stresses an assistant the most. We release the environment, task set, and agent harness at https://mypcbench.com.
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