OSWorld Style Synthetic Benchmarks for Computer Use Agents

Why OSWorld matters for AI teams

OSWorld is a benchmark suite that runs agents in simulated desktop environments and evaluates their ability to complete real-world tasks. It generates synthetic trajectories of mouse movements, clicks, keyboard inputs, and screen observations. This approach lets you test models at scale without risking production systems. Teams using OSWorld-style benchmarks report up to 10x more diverse test coverage compared with manual test cases.

What you get from synthetic benchmarks

• Control over task difficulty, environment states, and success criteria
• Reproducible evaluation across thousands of tasks
• No dependency on real user data or external services
• Ability to generate edge cases and rare scenarios that rarely occur in production
• Faster iteration cycles for model training and evaluation

The tradeoff: realism vs. controllability

Synthetic benchmarks are controllable and scalable, but they can diverge from the real world. A perfect simulation may miss latency, UI glitches, or unexpected user behavior. Real-world data is messy but authentic. The best teams combine synthetic benchmarks with a small amount of high-quality real data to balance coverage and realism.

How Coasty fits

Coasty runs computer use agents on real desktops and browsers, capturing realistic interaction data that reflects actual user behavior. This approach lets you produce custom synthetic datasets for your specific workflows. Coasty’s offering is a custom, contact-led service where you talk to the Coasty data team about your needs and they build datasets tailored to your agents and evaluation targets.