MobiAgent: A Systematic Framework for Customizable Mobile Agents
Authors: name: Cheng Zhang, name: Erhu Feng, name: Xi Zhao, name: Yisheng Zhao, name: Wangbo Gong, name: Jiahui Sun, name: Dong Du, name: Zhichao Hua, name: Yubin Xia, name: Haibo Chen

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.