healthcare benchmark
HealthBench (raw) is the HealthBench score before length adjustment.
Updated Oct 23, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAN | Score69.40% | Percentile100.00% | Participants1 | EvidenceC | Evaluated |
The leading models and scores on this benchmark.
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis healthbench (raw) AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
Selection summary
Claude Sonnet 5.5 currently leads HealthBench (raw) with 69.40%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price, and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.
What HealthBench (raw) measures and how its scores work.
HealthBench (raw) is a healthcare benchmark metric distinct from the length-adjusted HealthBench catalog metric.
It measures Score, reported as a ratio, before length adjustment.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about HealthBench (raw).
Claude Sonnet 5.5 is currently ranked first with 69.40%.
The current leaders are Claude Sonnet 5.5 (69.40%).
Claude Sonnet 5.5 has the lowest matched official input price at $2.0 input / $10 output per 1M tokens.
The fastest matched records are Claude Sonnet 5.5 (42.00 tok/s via Anthropic).
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.
It measures Score, reported as a ratio, before length adjustment.
Yes. Higher values rank better for this benchmark.
1 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.