VM-free OS(World), at scale.
To eval or train a computer-use agent, you need real desktops — a lot of them. OSWorld gives you a faithful one — LibreOffice, Chrome, VS Code, files and windows — but it ships as a heavy virtual machine. We propose a series of lightweight, VM-free sandboxes with standardized interfaces, where we reproduce benchmarks (e.g. OSWorld) and generate verifiable tasks to train any agent, on a fraction of the hardware resources.
OSWorld's VM tax: How we cut it with Lite.OSWorld
OSWorld's faithful desktop is a full VM per task. It needs /dev/kvm,
nested virtualization, and heavy resources — which cloud instances, CI runners, and
nested containers rarely provide, so it doesn't scale.
Lite.OSWorld (ours) keeps OSWorld's desktop and drops the VM. The same tasks and evaluators
run on a GNOME desktop in a plain Docker container. No /dev/kvm, so it runs
anywhere Docker does, at under a quarter of the memory and cpu.
| OSWorld | Lite.OSWorld | |
|---|---|---|
| Runtime | QEMU/KVM VM | Docker container |
| Host requirement | /dev/kvm, nested virt | Any Docker host |
| Memory | 4.1 GB | 0.9 GB |
| Cold start | 29.9 s | 23.8 s |
| Parallelism | baseline | ~4.6× more instances |
| Task suite | OSWorld | Identical |
Across 13 models, Lite.OSWorld's scores match the OSWorld VM's. The same model runs the same task the same way in the container as in the VM, judged by the same evaluators, so a score or training signal earned in the container carries straight back to the real benchmark.
Beyond OSWorld: Scalable Training Sandboxes
The VM-free container isn't just for OSWorld — it's a base for a family of scalable CUA-Lite sandboxes with verifiable tasks. The same base already runs more: browser and desktop tasks, real science desktops (GMAT flying spacecraft, PyMOL turning proteins). Efficient sandboxes to train and benchmark any agent, at scale.
Computer-use agents, without the heavy VM. Try it, or bring your own sandboxes: GitHub · Hugging Face · Email.