Browserbase provides reliable, verifiable evaluations and benchmarking for computer use models
Most evaluation frameworks test computer use models against cloned websites or synthetic environments. The real web is nothing like that. Cookie popups, CAPTCHAs, iframes, rate limits, and layouts that change overnight all make live evaluation unreliable at best and misleading at worst.
Browserbase runs your evaluations against real websites on deterministic browser infrastructure. Every task runs in a consistent, isolated environment that eliminates variability from anti-bot checks, random page states, and network noise. And every result is human-verified, not just scored by an LLM judge.
Avoid false positives. Improve your eval's accuracy.
LLM judging is inconsistent. Different judge models, thresholds, and prompts produce different pass rates on the same tasks. Browserbase pairs automated scoring with human verification. Evaluators review screenshots, full web trajectories, and final task states to confirm whether a task was actually completed.
Test against the web your models will actually face.
Run WebVoyager, OnlineMind2Web, and custom Stagehand evals on live websites instead of static clones. Browserbase captures every run with full session recordings, logs, and metrics so your team can debug failures and track progress across model versions.
Every trace. Every score. Published.
Without Browserbase, it would not have been possible to seamlessly train our model with reliable access to real-world websites.
Browserbase provides reliable, verifiable evaluations and benchmarking for computer use models
Most evaluation frameworks test computer use models against cloned websites or synthetic environments. The real web is nothing like that. Cookie popups, CAPTCHAs, iframes, rate limits, and layouts that change overnight all make live evaluation unreliable at best and misleading at worst.
Browserbase runs your evaluations against real websites on deterministic browser infrastructure. Every task runs in a consistent, isolated environment that eliminates variability from anti-bot checks, random page states, and network noise. And every result is human-verified, not just scored by an LLM judge.
Avoid false positives. Improve your eval's accuracy.
LLM judging is inconsistent. Different judge models, thresholds, and prompts produce different pass rates on the same tasks. Browserbase pairs automated scoring with human verification. Evaluators review screenshots, full web trajectories, and final task states to confirm whether a task was actually completed.
Test against the web your models will actually face.
Run WebVoyager, OnlineMind2Web, and custom Stagehand evals on live websites instead of static clones. Browserbase captures every run with full session recordings, logs, and metrics so your team can debug failures and track progress across model versions.
Every trace. Every score. Published.
Without Browserbase, it would not have been possible to seamlessly train our model with reliable access to real-world websites.
Browserbase publishes complete evaluation data for every run. No cherry-picked results, no quietly pruned benchmarks. Your team and the broader research community get the same data, making results reproducible and comparisons fair.
Condense 18 browser hours into 20 minutes.
Google DeepMind used Browserbase's concurrent browser infrastructure to run thousands of evaluation tasks in parallel, turning what used to take 18 browser hours into 20 minutes of total runtime. Instant browser provisioning and high concurrency mean total time is limited only by how long a single task takes to complete.
Same environment. Every run. No surprises.
Each browser session runs in an isolated, SOC-2 Type II compliant environment. No variability from rate limits, random states, or anti-bot interference. Your evaluations produce consistent, comparable results across runs and across teams.
See exactly what your model did and where it went wrong.
Full session recordings, step-by-step logs, and live view let your team watch evaluations as they happen or replay them later. Debug failures faster and give your research team the context they need to improve model performance.
Browserbase publishes complete evaluation data for every run. No cherry-picked results, no quietly pruned benchmarks. Your team and the broader research community get the same data, making results reproducible and comparisons fair.
Condense 18 browser hours into 20 minutes.
Google DeepMind used Browserbase's concurrent browser infrastructure to run thousands of evaluation tasks in parallel, turning what used to take 18 browser hours into 20 minutes of total runtime. Instant browser provisioning and high concurrency mean total time is limited only by how long a single task takes to complete.
Same environment. Every run. No surprises.
Each browser session runs in an isolated, SOC-2 Type II compliant environment. No variability from rate limits, random states, or anti-bot interference. Your evaluations produce consistent, comparable results across runs and across teams.
See exactly what your model did and where it went wrong.
Full session recordings, step-by-step logs, and live view let your team watch evaluations as they happen or replay them later. Debug failures faster and give your research team the context they need to improve model performance.
