LLM Reference
activeSafety

ToxiGen

Metric: Toxicity Classification Accuracy (higher is better)Introduced: 2022

274,000 machine-generated toxic and benign statements about 13 minority groups, using adversarial classifier-in-the-loop decoding for implicit hate speech evaluation.

Models ranked

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need ≥2 snapshots

Leaderboard

Tracked models ranked by Toxicity Classification Accuracy (higher is better).

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How to read this benchmark

This benchmark scores models where higher is better. Use scores for directional filtering and shortlisting, not universal quality ranking; then validate pricing, context window, provider availability, and fit for your workload.

Trust this score when

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

Be cautious when

  • There is only one benchmark snapshot or the dataset appears stale.
  • The 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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Last reviewed: Apr 15, 2026