MobiAgent: A Systematic Framework for Customizable Mobile Agents

Zhang, Cheng, Feng, Erhu, Zhao, Xi, Zhao, Yisheng, Gong, Wangbo, Sun, Jiahui, Du, Dong, Hua, Zhichao, Xia, Yubin, Chen, Haibo

arXiv.org Artificial Intelligence 

With the rapid advancement of Vision-Language Models (VLMs), GUI-based mobile agents have emerged as a key development direction for intelligent mobile systems. However, existing agent models continue to face significant challenges in real-world task execution, particularly in terms of accuracy and efficiency. To address these limitations, we propose MobiAgent, a comprehensive mobile agent system comprising three core components: the MobiMind-series agent models, the AgentRR acceleration framework, and the MobiFlow benchmarking suite. Furthermore, recognizing that the capabilities of current mobile agents are still limited by the availability of high-quality data, we have developed an AI-assisted agile data collection pipeline that significantly reduces the cost of manual annotation. Compared to both general-purpose LLMs and specialized GUI agent models, MobiAgent achieves state-of-the-art performance in real-world mobile scenarios.