title: OSUniverse: Benchmark for Multimodal GUI-navigation AI Agents
summary: In this paper, we introduce OSUniverse: a benchmark of complex, multimodal
  desktop-oriented tasks for advanced GUI-navigation AI agents that focuses on
  ease of use, extensibility, comprehensive coverage of test cases, and automated
  validation. We divide the tasks in increasing levels of complexity, from basic
  precision clicking to multistep, multiapplication tests requiring dexterity,
  precision, and clear thinking from the agent. In version one of the benchmark,
  presented here, we have calibrated the complexity of the benchmark test cases
  to ensure that the SOTA (State of the Art) agents (at the time of publication)
  do not achieve results higher than 50%, while the average white collar worker
  can perform all these tasks with perfect accuracy. The benchmark can be scored
  manually, but we also introduce an automated validation mechanism that has an
  average error rate less than 2%. Therefore, this benchmark presents solid
  ground for fully automated measuring of progress, capabilities and the
  effectiveness of GUI-navigation AI agents over the short and medium-term
  horizon. The source code of the benchmark is available at
  https://github.com/agentsea/osuniverse.
paper_authors._id: 681b518bf497fd5e45b55eeb
paper_authors.name: Mariya Davydova
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-05-14T11:27:43.146Z
paper_authors._id: 62d16ec939e0332b574d0d95
paper_authors.avatarUrl: /avatars/52a69820fffb347b3ea495b121bb3ad9.svg
paper_authors.fullname: Mariya Davydova
paper_authors.type: user
paper_authors.user: mariyadavydova
paper_authors._id: 681b518bf497fd5e45b55eec
paper_authors.name: Daniel Jeffries
paper_authors._id: 681b518bf497fd5e45b55eed
paper_authors.name: Patrick Barker
paper_authors._id: 681b518bf497fd5e45b55eee
paper_authors.name: Arturo Márquez Flores
paper_authors._id: 681b518bf497fd5e45b55eef
paper_authors.name: Sinéad Ryan
paper_title: OSUniverse: Benchmark for Multimodal GUI-navigation AI Agents
paper_summary: In this paper, we introduce OSUniverse: a benchmark of complex, multimodal
  desktop-oriented tasks for advanced GUI-navigation AI agents that focuses on
  ease of use, extensibility, comprehensive coverage of test cases, and automated
  validation. We divide the tasks in increasing levels of complexity, from basic
  precision clicking to multistep, multiapplication tests requiring dexterity,
  precision, and clear thinking from the agent. In version one of the benchmark,
  presented here, we have calibrated the complexity of the benchmark test cases
  to ensure that the SOTA (State of the Art) agents (at the time of publication)
  do not achieve results higher than 50%, while the average white collar worker
  can perform all these tasks with perfect accuracy. The benchmark can be scored
  manually, but we also introduce an automated validation mechanism that has an
  average error rate less than 2%. Therefore, this benchmark presents solid
  ground for fully automated measuring of progress, capabilities and the
  effectiveness of GUI-navigation AI agents over the short and medium-term
  horizon. The source code of the benchmark is available at
  https://github.com/agentsea/osuniverse.
paper_ai_summary: OSUniverse benchmarks multimodal desktop tasks for GUI-navigation AI, offering automated validation and scoring mechanisms.
paper_ai_keywords: OSUniverse GUI-navigation AI benchmark multimodal tasks desktop-oriented automated validation accuracy complexity calibration