A macOS agent built around $0.0002 decisions
Many frontier-model desktop agents send a fresh screenshot to a large model for every action, then wait several seconds for a plan. Andrew Levin’s MIT-licensed open-source project, typesafe-computer-use, extracts screen state locally and asks a smaller decision model to select from bounded actions. Levin says he built the initial version in under 30 minutes.
The agent works toward a plain-English goal on macOS, reporting a cost of roughly $0.0002 per decision. Screenshot pixels remain on the machine. Model requests contain OCR text, accessibility metadata, the active application, the browser URL, and other structured state. Free-form text goes to a separate writer model only when a field or URL requires it.
- Platform: macOS 14 or later
- License: MIT
- Decision service: TypeSafe API
- Default writer: Claude Haiku
- Reported decision latency: 0.13–0.38 seconds
One screenshot, a 155× cost gap
The repository compares its TypeSafe configuration, labeled jev, with Claude Opus 5 on the same screenshot and goal. The Opus baseline receives a bare screenshot.
These figures come from the repository and have not been independently verified. They describe a narrow point comparison, with no task-completion rates, broad application suite, or recovery benchmark. Writer-model calls also add their own latency and cost. A production evaluation would need to measure successful completion, retries, writer usage, and failures across representative workflows.
TypeSafe, the project’s core dependency, accepts a Choice containing as many as 255 options and returns a probability distribution with a calibrated confidence score. According to the README, responses arrive within a few hundred milliseconds and incur no output-token charge. The open-source agent therefore depends on hosted inference rather than a locally runnable decision model.