CoAct-1: Computer-using Agents with Coding as Actions
Authors: name: Linxin Song; name: Yutong Dai; name: Viraj Prabhu; name: Jieyu Zhang; name: Taiwei Shi; name: Li Li; name: Junnan Li; name: Silvio Savarese; name: Zeyuan Chen; name: Jieyu Zhao; name: Ran Xu; name: Caiming Xiong
Published: 2025-08-05 21:33:36

Abstract: Autonomous agents that operate computers via Graphical User Interfaces (GUIs)
often struggle with efficiency and reliability on complex, long-horizon tasks.
While augmenting these agents with planners can improve task decomposition,
they remain constrained by the inherent limitations of performing all actions
through GUI manipulation, leading to brittleness and inefficiency. In this
work, we introduce a more robust and flexible paradigm: enabling agents to use
coding as a enhanced action. We present CoAct-1, a novel multi-agent system
that synergistically combines GUI-based control with direct programmatic
execution. CoAct-1 features an Orchestrator that dynamically delegates subtasks
to either a conventional GUI Operator or a specialized Programmer agent, which
can write and execute Python or Bash scripts. This hybrid approach allows the
agent to bypass inefficient GUI action sequences for tasks like file management
and data processing, while still leveraging visual interaction when necessary.
We evaluate our system on the challenging OSWorld benchmark, where CoAct-1
achieves a new state-of-the-art success rate of 60.76%, significantly
outperforming prior methods. Furthermore, our approach dramatically improves
efficiency, reducing the average number of steps required to complete a task to
just 10.15, compared to 15 for leading GUI agents. Our results demonstrate that
integrating coding as a core action provides a more powerful, efficient, and
scalable path toward generalized computer automation.