Applies to:
- Plan - Any
- Deployment - Any
- How to run prompts or evaluations on large datasets. Guidance on running via SDK and expected performance.
Summary
For large datasets, reduce the Playground sample rate for faster iteration, or run an experiment through the SDK from your own environment, with results recorded in Braintrust.What is happening
Each dataset row runs the configured tasks and scorers, so larger datasets take more work to process. Completion time depends on model response times, input size, concurrency, and provider rate limits. The SDK achieved higher throughput in tests, but this does not guarantee faster execution for every workload. For a fair comparison, use the same dataset, model, scorers, and concurrency settings in both SDK and Playground runs.Fix or suggestion
Use the SDK to run an evaluation against a dataset and saved prompt stored in Braintrust, with results recorded as an experiment. This approach lets you manage bulk workloads from your own environment.- Increase
maxConcurrency(TypeScript) ormax_concurrency(Python) to speed processing. Monitor your model provider for rate limits. - Reduce input size and sample rate to improve throughput.
- Check that your account has the required permissions to run experiments and write dataset rows.
How to confirm it worked
- Open the resulting experiment and verify that it contains one evaluation result for each dataset row included in the run.
- Check for task errors or missing outputs. A matching result count alone does not confirm that every case succeeded.