OmniGUI/OmniGUI
OmniGUI: Benchmarking GUI Agents in Omni-Modal Smartphone Environments [π Project Page] [π arXiv Paper] [π Dataset] [π» GitHub] [π Leaderboard] OmniGUI is a step-level GUI agent benchmark designed for omni-modal smartphone interaction. At each action step, the agent receives interleaved multimodal observations, including static screenshots, synchronous audio cues, short video clips, and action history, and must predict the next GUI action such as TAP or TYPE. Theβ¦ See the full description on the dataset page: https://huggingface.co/datasets/OmniGUI/OmniGUI.
OmniGUI: Benchmarking GUI Agents in Omni-Modal Smartphone Environments
<font size=4><div align='center' > [π Project Page] [π arXiv Paper] [π Dataset] [π» GitHub] [π Leaderboard] </div></font>
OmniGUI is a step-level GUI agent benchmark designed for omni-modal smartphone interaction. At each action step, the agent receives interleaved multimodal observations, including static screenshots, synchronous audio cues, short video clips, and action history, and must predict the next GUI action such as TAP or TYPE.
The benchmark contains 708 expert-demonstrated episodes and 2,572 action steps across 29 real smartphone applications in both Chinese and English. OmniGUI evaluates five core capabilities: Localization, Semantic Understanding, Cross-modal Discrimination, Temporal Reasoning, and Instant Response.
π Quick Start
Download the dataset
You can download the dataset using the huggingface-cli:
huggingface-cli download XIAOCHENLIN00zz/OmniGUI \
--repo-type dataset \
--local-dir dataAfter downloading, your local data directory should contain:
data/merged_sorted.jsondata/benchmark/
π οΈ APP STATISTICS
π Chinese Applications (ZH)
π English Applications (EN)
π FINAL SUMMARY (TOTAL)
Citation
Feel free to cite the following article if you find OmniGUI helpful:
@article{henry2026omnigui,
title={OmniGUI: Benchmarking GUI Agents in Omni-Modal Smartphone Environments},
author={Henry, Felix and Lin, Xiaochen and Zhu, Jiangyou and Zhang, Bingqian and Chen, Min and Huang, Shiyu and others},
journal={arXiv preprint arXiv:2605.18758},
year={2026}
}