HealthBench
OpenAI benchmark of 5,000 realistic health conversations graded against physician-written rubrics. LLMReference tracks the length-adjusted score when available to reduce verbosity bias.
Models ranked
3
tracked on this benchmark
Score band
57.0 – 55.8
best → lowest tracked
Snapshot trend
—
need ≥2 snapshots
Leaderboard
Tracked models ranked by Length-adjusted score (higher is better).
Notes: Official GPT-5.6 preview system-card row. Raw score is recorded only in the version label so rankings use the comparable length-adjusted metric.
Notes: Official GPT-5.6 preview system-card row. Raw score is recorded only in the version label so rankings use the comparable length-adjusted metric.
Notes: Official GPT-5.6 preview system-card row. Raw score is recorded only in the version label so rankings use the comparable length-adjusted metric.
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: Jun 26, 2026