Mobile-Agent-v3: Foundamental Agents for GUI Automation
Authors: name: Jiabo Ye; name: Xi Zhang; name: Haiyang Xu; name: Haowei Liu; name: Junyang Wang; name: Zhaoqing Zhu; name: Ziwei Zheng; name: Feiyu Gao; name: Junjie Cao; name: Zhengxi Lu; name: Jitong Liao; name: Qi Zheng; name: Fei Huang; name: Jingren Zhou; name: Ming Yan
Published: 2025-08-21 00:39:12

Abstract: This paper introduces GUI-Owl, a foundational GUI agent model that achieves
state-of-the-art performance among open-source end-to-end models on ten GUI
benchmarks across desktop and mobile environments, covering grounding, question
answering, planning, decision-making, and procedural knowledge. GUI-Owl-7B
achieves 66.4 on AndroidWorld and 29.4 on OSWorld. Building on this, we propose
Mobile-Agent-v3, a general-purpose GUI agent framework that further improves
performance to 73.3 on AndroidWorld and 37.7 on OSWorld, setting a new
state-of-the-art for open-source GUI agent frameworks. GUI-Owl incorporates
three key innovations: (1) Large-scale Environment Infrastructure: a
cloud-based virtual environment spanning Android, Ubuntu, macOS, and Windows,
enabling our Self-Evolving GUI Trajectory Production framework. This generates
high-quality interaction data via automated query generation and correctness
validation, leveraging GUI-Owl to refine trajectories iteratively, forming a
self-improving loop. It supports diverse data pipelines and reduces manual
annotation. (2) Diverse Foundational Agent Capabilities: by integrating UI
grounding, planning, action semantics, and reasoning patterns, GUI-Owl supports
end-to-end decision-making and can act as a modular component in multi-agent
systems. (3) Scalable Environment RL: we develop a scalable reinforcement
learning framework with fully asynchronous training for real-world alignment.
We also introduce Trajectory-aware Relative Policy Optimization (TRPO) for
online RL, achieving 34.9 on OSWorld. GUI-Owl and Mobile-Agent-v3 are
open-sourced at https://github.com/X-PLUG/MobileAgent.