WorldGUI
Desktop GUI agents do 611 tasks that start from varied initial states, such as the target app not being open. Tasks come with instructional videos and project files.
127 GitHub stars at November 1st, 2026.
- Made by
- Show Lab, National University of Singapore
- Released
- February 2025
- Kind
- Desktop apps
- Level
- Everyday
- Scored
- Checked automatically
- Answers
- Agent task
- Tasks
- All public
- Strongest model tested
- GPT-5.1 #65 on the capability index
- Last model added
- November 2025
- Scores refreshed
- November 12th, 2026
In the authors’ words
Recent progress in GUI agents has substantially improved visual grounding, yet robust planning remains challenging, particularly when the environment deviates from a canonical initial state. In real applications, users often invoke assistance mid-workflow, where software may be partially configured, steps may have been executed in different orders, or the interface may differ from its default setup. Such task-state variability is pervasive but insufficiently evaluated in existing GUI benchmarks. To address this gap, we introduce WorldGUI, a benchmark covering ten widely used desktop and web applications with tasks instantiated under diverse, systematically constructed initial states. These variations capture realistic human-computer interaction settings and enable diagnostic evaluation of an agent's ability to recover, adapt plans, and handle non-default contexts. We further present WorldGUI-Agent, a simple and model-agnostic framework that organizes planning and execution around three critique stages, improving reliability in dynamic environments. Experiments demonstrate that state-of-the-art GUI agents exhibit substantial performance degradation under non-default initial conditions, revealing limited robustness and fragile planning behaviors. Our benchmark and framework provide a foundation for developing more adaptable and reliable GUI agents. The code and data are available at https://github.com/showlab/WorldGUI.
GPT-5.1 leads with 45.8%
Best score per entry from the benchmark's own leaderboard, read on November 12th, 2026. Where a model ran with several settings or harnesses, we keep its best. Names in gray aren't in our model list: fine-tunes, agent systems, products and older models. They don't count toward leaders.
- 1 GPT-5.1 45.8%
- 2 Claude-3.5-Sonnet (snapshot unspecified) 36%
- 3 Agent S2 (backbone unspecified) 34.2%
- 4 GPT-4o (snapshot unspecified) 26%
- 5 Gemini-2.0 (model unspecified) 19.1%
- 6 UI-TARS-1.5 (size unspecified) 12.3%
Source: Official WorldGUI leaderboard
| # | Entry | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-5.1 | 45.8% | WorldGUI-Agent | Nov 2025 | Official leaderboard |
| 2 | Claude-3.5-Sonnet (snapshot unspecified) | 36% | WorldGUI-Agent | Official leaderboard | |
| 3 | Agent S2 (backbone unspecified) | 34.2% | Official leaderboard | ||
| 4 | GPT-4o (snapshot unspecified) | 26% | WorldGUI-Agent | Official leaderboard | |
| 5 | Gemini-2.0 (model unspecified) | 19.1% | WorldGUI-Agent | Official leaderboard | |
| 6 | UI-TARS-1.5 (size unspecified) | 12.3% | Official leaderboard |
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Official WorldGUI leaderboard
No lab model card reports it yet
We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark.
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