Give AI agents computers they can use.
Cua provides open-source desktop automation, isolated cloud desktops,
local macOS VMs, specialist decision models, and benchmarks for evaluating computer-use agents.
Try Cua Fleets now at run.cua.ai
Choose your path
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CUA-S1: Explore small, specialized models for computer-use decisions. - Cua Driver: [Operate Calculator and verify its
result](https://cua.ai/docs/tutorials/drive-your-first-app). - Lume: [Create a Tahoe VM and connect over
SSH](https://cua.ai/docs/tutorials/create-your-first-lume-vm). - Cua Bench: [Create and verify a simulated
task](https://cua.ai/docs/tutorials/your-first-cua-bench-task).
Bring your own agent and model, or explore CUA-S1 for specialized decisions. Cua provides the computer and automation tools. [Computer-Use
2.0](https://cua.ai/docs/concepts/what-is-computer-use) describes an agent moving between code, APIs, and graphical interfaces within the same task.
See Cua Driver in action
Two Cua Driver sessions select cells in LibreOffice Calc and objects in Inkscape on an Omarchy desktop while a terminal stays in the foreground. Watch
the 50-second demo, then explore Omarchy on Fleet.
https://github.com/user-attachments/assets/b4e5517c-d2db-4758-b4cf-07131b0753b2
Cua Fleets
Provision isolated cloud desktops at
run.cua.ai. A Fleet maintains
sandbox capacity; your code claims a desktop from a pool and uses the Sandbox SDK to run commands, capture screenshots, and interact with apps inside
it.
Your first result: provision a Linux desktop, run uname -a, save a screenshot, and delete the cloud resources. The tutorial covers Fleet
credentials, dependencies, and cleanup. Pools can retain paid capacity after a claim ends, so follow its cleanup steps.
Local sandboxes and Fleets share the Sandbox SDK, but credentials, images, operations, and runtime requirements differ. Use the [runtime support
reference](https://cua.ai/docs/reference/sandbox-sdk/runtime-support) to choose an environment. For your own hardware, see [Manage local sandbox
lifecycle](https://cua.ai/docs/how-to-guides/sandbox/manage-local-lifecycle).
Your first Cloud Fleet | Fleet overview |
Cua Driver
Give your agent tools to inspect and operate native desktop apps and browsers on macOS, Windows, and Linux. Connect through the CLI, MCP, or typed
SDKs. Background delivery lets agents work without moving your pointer or taking focus when the app and platform support it; see [platform
support](https://cua.ai/docs/reference/cua-driver/platform-support) for the boundaries.
macOS / Linux
/bin/bash -c "$(curl -fsSL https://cua.ai/driver/install.sh)"
Windows (PowerShell)
irm https://cua.ai/driver/install.ps1 | iex
Your first result: connect your agent, ask it to compute 6 × 7 in Calculator, and have it verify that the app displays 42. The tutorial covers platform setup, permissions, and agent connection.
Drive your first app | Installation
Using Claude Code, Codex, Cursor, OpenClaw, or another agent? Find your integration.
Source documentation and architecture notes live in libs/cua-driver/README.md.
CUA-S1
CUA-S1 is our family of small, specialized System 1 models for computer use. We use "System 1" as an engineering analogy for fast, bounded decisions,
such as choosing which value belongs in a field or whether to leave an element alone. It is not a strict classification of model architectures or a
replacement for a general-purpose agent's planning and reasoning.
The first research profile focuses on forms: scoring decisions from structured interface elements and document values rather than generating a
response token by token. Application code orders the actions, and the optional Cua Driver integration handles execution with explicit action
boundaries.
The project includes Python model code, synthetic-data generation, training, and evaluation. The GitHub component is an early, source-only research
release; model weights are hosted separately on Hugging Face. The source is MIT-licensed. Check each model and dataset card for its scope,
limitations, and artifact-specific license.
Explore CUA-S1 | Model card | Safety and deployment guidance
CUA-S1-FORMS on Hugging Face: Model weights | Dataset
Lume
Create and manage local macOS and Linux VMs on Apple Silicon using Apple's Virtualization.Framework.
/bin/bash -c "$(curl -fsSL https://cua.ai/lume/install.sh)"
Your first result: create a vanilla macOS Tahoe VM from an Apple restore image, start it, and connect over SSH. The tutorial uses the Lume CLI directly and explains the unattended setup defaults.
Cua Bench
Build computer-use tasks, evaluate agents, and export trajectories for training. Start with a simulated task that requires no VM, Docker, or model API key.
With Python 3.12 or 3.13 and uv installed:
uv tool install 'cua-bench[browser]'
uv tool run --from 'cua-bench[browser]' playwright install chromium
Your first result: create a small task, run its reference solution, and verify that its evaluator reports a reward of 1.0. Then try the same task yourself.
Build your first task | **[What is
Cua-Bench?](https://cua.ai/docs/concepts/what-is-cua-bench) | CLI reference** |
Resources
- Documentation — Guides, examples, and API reference - Blog — Tutorials, updates, and research -
Discord — Community support and discussions - GitHub Issues — Bug
reports and feature requests - Security — Private vulnerability reporting
Citation
If Cua supports your research, please cite the software:
@software{cua2025,
author = {{Cua AI, Inc.}},
title = {Cua},
year = {2025},
url = {https://github.com/trycua/cua},
license = {MIT}
}
For reproducibility, include the Cua release or commit used in your experiments. Citation metadata is also available in CITATION.cff.
Contributing
We welcome contributions! See our Contributing Guidelines for details.
License
MIT License — see LICENSE for details.
Third-party components have their own licenses:
- Kasm (MIT)
- OmniParser (CC-BY-4.0)
- Optional
cua-agent[omni]includes ultralytics (AGPL-3.0)
Trademarks
Apple, macOS, Ubuntu, Canonical, and Microsoft are trademarks of their respective owners. This project is not affiliated with or endorsed by these companies.
Sponsors
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