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.

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.

CUA-S1-FORMS on Hugging Face:

Cua Platform Overview

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.

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.

Lume: Create and manage local macOS and Linux VMs on Apple Silicon using Apple’s Virtualization.Framework.

Cua Bench: Build computer-use tasks, evaluate agents, and export trajectories for training.

Computer-Use 2.0 describes an agent moving between code, APIs, and graphical interfaces within the same task.

The repository has 24,796+ GitHub stars as of September 2026.