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OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments

Tests whether agents can finish 369 tasks in real desktop applications, using executable checks of the final state. The original study found a wide gap between agent and human success rates.

Introduction

A convincing action sequence can still leave the wrong spreadsheet or browser state. Evaluating the resulting files and application state makes completion measurable without requiring an agent to follow one reference trajectory.

Key Findings
  • The 369-task Ubuntu suite spans desktop software, files, and multi-application workflows, testing more than browser navigation.
  • In the original experiments, the best agent reached 12.24% success versus 72.36% for humans; these are historical baselines.
  • Failures in screen grounding and application knowledge show why stronger text reasoning alone may not fix desktop control.
Who Should Read It

Great fit if you study computer-use agents and need reproducible, outcome-based evaluation. Look elsewhere if you need a lightweight text-only test: virtual machines and application-specific evaluators add setup costs, and the published benchmark focuses on Ubuntu.

Information

  • Websitearxiv.org
  • OrganizationsThe University of Hong Kong, Carnegie Mellon University, Salesforce Research, University of Waterloo
  • AuthorsTianbao Xie, Danyang Zhang, Jixuan Chen, Xiaochuan Li, Siheng Zhao, Ruisheng Cao, Toh Jing Hua, Zhoujun Cheng, Dongchan Shin, Fangyu Lei …
  • Published date2024/04/11

Categories

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