cua vs typesafe-computer-use
Computer-use infrastructure for agents: sandboxed Linux, macOS and Windows desktops locally or in the cloud, Cua Driver for native apps (CLI/MCP/SDK), Lume VMs, CUA-S1 models, Cua Bench. — versus — macOS computer-use loop at ~$0.0002/step: OCR + accessibility tree read the screen, a TypeSafe classifier picks the next action, code clicks; an LLM writes only free text.
Both are computer-use stacks for desktop tasks; cua runs frontier agents in sandboxed VMs, jev drives your real Mac with a cheap classifier.
| cua | typesafe-computer-use | |
|---|---|---|
| Stars | 32k | 1.3k |
| Forks | 2.4k | 123 |
| Language | Rust | Python |
| License | MIT | MIT |
| Last activity | yesterday | 1 months ago |
| Topics | agents, sandboxes | agents, decision-models |
| Curated connections | 5 | 6 |
cua — the curator's take
The broadest open stack for computer-use agents: one sandbox API that runs a desktop locally or on their cloud, Cua Driver that operates native apps on macOS, Windows and Linux in the background without taking your pointer (CLI, MCP or typed SDKs), Lume for macOS and Linux VMs on Apple Silicon, Cua Bench for tasks and trajectories, and CUA-S1, small decision models for forms. Use it when your agent has to touch software that has no API. The breadth is the cost: many components, a cloud product (Fleets) promoted throughout, and the installer signs you in. If your agent only needs the web, browser-use is far less; if it only needs to run code, a plain sandbox is enough.
typesafe-computer-use — the curator's take
Use it when per-step cost and latency matter more than raw capability: cheap, gated, replayable desktop automation with a confidence number per action. Skip it when tasks need real visual reasoning — anything the frontier model infers from pixels must be rebuilt as deterministic state — and remember it drives your real mouse, needs a paid TypeSafe key, and Windows is experimental.