Cua
Cua is an open-source infrastructure project designed to scale computer-use agents, providing drivers, sandboxes, SDKs, and benchmarks that enable training, evaluation, and data generation for AI agents capable of controlling full desktop environments. It supports multiple operating systems including macOS, Linux, and Windows, allowing developers to run agents across heterogeneous fleets. The project offers cross-OS drivers for interacting with desktop UIs, sandboxed execution environments, and standardized evaluation benchmarks. Cua aims to advance computer-use 2.0 by offering the community open-source tooling for building and assessing agents that can perform complex GUI tasks, automate workflows, and generate interaction datasets at scale.
- Category
- AI Agents
- Pricing
- Open Source
Problem solved
Cua addresses the lack of unified, cross-platform infrastructure for developing and evaluating computer-use AI agents, enabling reproducible training, testing, and data collection in sandboxed desktop environments.
Use cases
- Training computer-use agents on desktop automation tasks
- Evaluating agents on cross-OS benchmarks
- Generating synthetic interaction data for model fine-tuning
- Running agents in sandboxed desktop environments
- Developing custom computer-control SDKs
- Benchmarking agent performance on real-world GUI tasks
Audience
- Developers
- ML Engineers
- Data Scientists
- Researchers
Pros
- Cross-platform support for macOS, Linux, and Windows
- Provides sandboxed environments for safe agent execution
- Includes benchmarks for standardized evaluation
- Open-source and community-driven
- Facilitates large-scale data generation
Cons
- Requires technical expertise to set up and use
- No managed cloud service
- Limited documentation for beginners
- May require significant computational resources
Official website: https://github.com/trycua/cua
Canonical LambdaBase page: https://www.lambdabase.com/tools/cua