HyperAI
a day ago

MMBench-GUI: Hierarchical Multi-Platform Evaluation Framework for GUI Agents

Xuehui Wang, Zhenyu Wu, JingJing Xie, Zichen Ding, Bowen Yang, Zehao Li, Zhaoyang Liu, Qingyun Li, Xuan Dong, Zhe Chen, Weiyun Wang, Xiangyu Zhao, Jixuan Chen, Haodong Duan, Tianbao Xie, Chenyu Yang, Shiqian Su, Yue Yu, Yuan Huang, Yiqian Liu, Xiao Zhang, Yanting Zhang, Xiangyu Yue, Weijie Su, Xizhou Zhu, Wei Shen, Jifeng Dai, Wenhai Wang
MMBench-GUI: Hierarchical Multi-Platform Evaluation Framework for GUI
  Agents
Abstract

We introduce MMBench-GUI, a hierarchical benchmark for evaluating GUIautomation agents across Windows, macOS, Linux, iOS, Android, and Webplatforms. It comprises four levels: GUI Content Understanding, ElementGrounding, Task Automation, and Task Collaboration, covering essential skillsfor GUI agents. In addition, we propose a novel Efficiency-Quality Area (EQA)metric to assess GUI agent execution efficiency in online automation scenarios.Through MMBench-GUI, we identify accurate visual grounding as a criticaldeterminant of overall task success, emphasizing the substantial benefits ofmodular frameworks that integrate specialized grounding modules. Furthermore,to achieve reliable GUI automation, an agent requires strong task planning andcross-platform generalization abilities, with long-context memory, a broadaction space, and long-term reasoning playing a critical role. More important,task efficiency remains a critically underexplored dimension, and all modelssuffer from substantial inefficiencies, with excessive redundant steps evenwhen tasks are ultimately completed. The integration of precise localization,effective planning, and early stopping strategies is indispensable to enabletruly efficient and scalable GUI automation. Our benchmark code, evaluationdata, and running environment will be publicly available athttps://github.com/open-compass/MMBench-GUI.