LLM Reference
CrowS-PairsactiveSafety

CrowS-Pairs

Metric: Bias Score (higher is better)Introduced: 2020

About

1,508 crowdsourced sentence pairs measuring stereotypical bias in masked language models across 9 categories including race, gender, and religion.Compare model scores alongside pricing, API availability, and release date — high benchmark score alone doesn't make a model the right pick.

How to read this benchmark

This benchmark uses a scoring system where higher is better. Scores are useful for directional filtering and model shortlisting, not for universal quality ranking.

Interpretation checklist: prefer benchmarks that are closest to your workload style, then validate against the linked model pages for pricing, context window, and provider availability.

Trust when:

  • There is a fresh timestamped snapshot (or multiple snapshots) for this benchmark.
  • Model list covers the same version family you can actually deploy today.
  • Top candidates overlap with your required routing and feature requirements.

Don't trust when:

  • There is only one benchmark snapshot or the dataset appears stale.
  • Benchmark metric direction is opposite of your decision objective.
  • The score difference between options is narrow and likely within implementation variance.

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