healthcare benchmark
A challenging variation of HealthBench that evaluates large language models' performance and safety in healthcare through 5,000 multi-turn conversations with particularly rigorous evaluation criteria validated by 262 physicians from 60 countries
Updated Aug 7, 2026
Sorted by the source-provided rank. Higher score is better according to the registry.
| 1 | ME | 42.8% | 100.0% | 9 | C | |
| 2 | OP | 33.1% | 87.5% | 9 | C | |
| 3 | OP | 32.7% | 75.0% | 9 | C | |
| 4 | OP | 32.0% | 62.5% | 9 | C | |
| 5 | OP | 30.0% | 50.0% | 9 | C | |
| 6 | OP | 25.9% | 37.5% | 9 | C | |
| 7 | OP | 22.9% | 25.0% | 9 | C | |
| 8 | OP | 10.8% | 12.5% | 9 | C | |
| 9 | OP | 1.6% | 0.0% | 9 | C |
Top published rows on the benchmark's original scale.
The top published results on this benchmark's own scale.
Definition and scoring fields from the benchmark registry.
A challenging variation of HealthBench that evaluates large language models' performance and safety in healthcare through 5,000 multi-turn conversations with particularly rigorous evaluation criteria validated by 262 physicians from 60 countries
Scores are shown in ratio. The current registry marks this benchmark as not independently verified with evidence level C.
Source-native results are preserved. Eligibility for the overall LLMBoard score is a separate policy decision.
Common questions about HealthBench Hard.
Muse Spark is currently ranked first with 42.8%.
A challenging variation of HealthBench that evaluates large language models' performance and safety in healthcare through 5,000 multi-turn conversations with particularly rigorous evaluation criteria validated by 262 physicians from 60 countries
Yes. Higher values rank better for this benchmark.
9 unique published model results are currently shown.
This benchmark is preserved as source-native evidence but is not eligible for the current overall score.