# MobiAgent: A Systematic Framework for Customizable Mobile Agents

## TL;DR

MobiAgent is a comprehensive framework that enhances mobile agents with improved accuracy and efficiency through specialized models, acceleration techniques, benchmarking, and an AI-assisted data collection pipeline, achieving state-of-the-art results.

## Contribution

The paper introduces MobiAgent, a systematic and customizable mobile agent system with novel components and an efficient data collection pipeline, advancing real-world mobile agent performance.

## Key findings

- Achieves state-of-the-art performance in real-world scenarios.
- Reduces manual annotation costs significantly.
- Outperforms general-purpose LLMs and specialized GUI agents.

## Abstract

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.