cua vs OpenSandbox
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 — CNCF-landscape sandbox platform for AI agents: multi-language SDKs, unified API, CLI and MCP over Docker/Kubernetes runtimes — coding agents, GUI agents, evals and RL training.
Both provide sandboxes for GUI agents; OpenSandbox spans coding, GUI and eval workloads over Docker and Kubernetes, Cua centres on full desktops with input, video and a native-app driver.
| cua | OpenSandbox | |
|---|---|---|
| Stars | 28k | 16k |
| Forks | 1.9k | 1.4k |
| Language | Rust | Python |
| License | MIT | Apache-2.0 |
| Last activity | today | 3 days ago |
| Topics | agents, sandboxes | sandboxes, agents, local |
| Curated connections | 4 | 8 |
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.
OpenSandbox — the curator's take
The platform play in agent sandboxing: one API over Docker and Kubernetes runtimes, SDKs in multiple languages, an MCP server, and OpenSSF/CNCF hygiene — built for the org that needs sandboxes as shared infrastructure across coding agents, GUI agents, eval harnesses and RL training, not a per-project tool. NOT the isolation ceiling: container runtimes trade the hard KVM boundary microVM sandboxes give you for operational familiarity — if untrusted code is the threat model, weigh a Firecracker-class runtime instead; if platform ergonomics on your existing K8s is the goal, this is the mature option.