The trajectory export feature is smart. Evaluation and training data collection in the same tool.

I'm curious how the benchmarks handle non-determinism. Real GUIs have loading states, animations, popups that appear sometimes but not always. Does cuabench control for that, or is variance just part of the measurement?

Also interested in what "Windows Arena" tests specifically. Windows has so many edge cases - UAC prompts, driver install dialogs, random update notifications. Those feel like the hard mode for computer-use agents.

Thanks - trajectory export was key for us since most teams want both eval and training data.

On non-determinism: we actually handle this in two ways. For our simulated environments (HTML/JS apps like the Slack/CRM clones), we control the full render state so there's no variance from animations or loading states. For native OS environments, we use explicit state verification before scoring - the reward function waits for expected elements rather than racing against UI timing. Still not perfect, but it filters out most flaky failures.

Windows Arena specifically - we're focusing on common productivity flows (file management, browser tasks, Office workflows) rather than the edge cases you mentioned. UAC prompts and driver dialogs are exactly the hard mode scenarios that break most agents today. We're not claiming to solve those yet, but that's part of why we're open-sourcing this - want to build out more adversarial tasks with the community.