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healthcare benchmark

HealthBench Consensus

HealthBench Consensus is a HealthBench subset focused on questions where physician-created rubric criteria have especially high agreement, measuring healthcare performance and safety on consensus-evaluable conversations.

Updated Aug 11, 2026

Models4
Model coverage4
MetricScore
EvidenceB

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  • Ranking
  • Distribution
  • Highlights
  • About
  • FAQ

HealthBench Consensus Ranking

Higher score ranks better on this benchmark.

4 rows
Columns

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1OPGPT-5.6 SolOpenAI95.5%100.0%4CAug 11, 2026
2OPGPT-5.6 LunaOpenAI95.1%66.7%4CAug 11, 2026
3OPGPT-5.6 TerraOpenAI95.1%33.3%4CAug 11, 2026
4OPGPT-5.5 InstantOpenAI94.7%0.0%4CAug 11, 2026

HealthBench Consensus Score Distribution

A closer view of the leading scores on this benchmark.

HealthBench Consensus

HealthBench Consensus Highlights

The leading models and scores on this benchmark.

Rank #1GPT-5.6 Sol95.5%Rank #2GPT-5.6 Luna95.1%Rank #3GPT-5.6 Terra95.1%Rank #4GPT-5.5 Instant94.7%

What is HealthBench Consensus?

What HealthBench Consensus measures and how its scores work.

HealthBench Consensus is a HealthBench subset focused on questions where physician-created rubric criteria have especially high agreement, measuring healthcare performance and safety on consensus-evaluable conversations.

Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.

Family
HealthBench Consensus
Modality
text
Primary category
healthcare
Score direction
higher
LLMBoard eligible
Yes
Evaluation key
healthbench-consensus|llm-stats-current

Benchmark scores retain their original unit. Overall score eligibility is shown separately.

FAQ

Common questions about HealthBench Consensus.

Which model scores highest on HealthBench Consensus?

GPT-5.6 Sol is currently ranked first with 95.5%.

What does HealthBench Consensus measure?

HealthBench Consensus is a HealthBench subset focused on questions where physician-created rubric criteria have especially high agreement, measuring healthcare performance and safety on consensus-evaluable conversations.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

4 model results are currently shown.

Does this benchmark affect the overall score?

Yes. This benchmark can contribute to the current LLMBoard capability score.

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