What is HealthBench Professional?
HealthBench Professional is a benchmark published by OpenAI in April 2026 that measures how well language models handle the work clinicians actually bring to them. It contains 525 physician-authored tasks selected from 15,079 real clinician conversations, each graded against a physician-written rubric. It narrows the scope of the original HealthBench, which covered general health conversations, to professional clinical use. The paper is at arxiv.org/abs/2604.27470.
The three use cases
Tasks fall into three categories of clinician work. Care consult: differential diagnosis, management decisions, and treatment questions. Writing and documentation: notes, summaries, letters, and coding. Medical research: synthesizing evidence and answering questions against the literature. A model that is strong in one category can be ordinary in another, which is part of what the benchmark is built to expose.
How the task set was built
| Source pool | 15,079 real conversations that clinicians brought to ChatGPT at work, not synthetic prompts written for the benchmark. |
|---|---|
| Selection | 525 tasks chosen by physicians, with difficult examples deliberately overweighted, roughly 3.5 times their natural rate. |
| Adversarial share | About one third of the set is red-teaming material: tasks written to invite a confident wrong answer. |
| Rubrics | Each task carries its own physician-written rubric. Criteria went through a three-stage construction and adjudication process, with three or more physicians per criterion. |
| Contributors | 190 physicians across 50 countries, 26 specialties, and 52 professional languages. |
How grading works
A model grader (GPT-5.4, low reasoning effort) reads the candidate response and judges each rubric criterion as met or not met. The score is earned points divided by possible points, clipped to 0 to 1, with a length adjustment so a longer answer cannot buy credit by covering everything. Rubrics include negative criteria: a response loses points for harmful or fabricated content regardless of what else it gets right.
Two reference points anchor the scale. Physician-written responses score 0.437 on the same rubrics, and the current model leader scores 0.660. Nothing is near 1.0, and that is by construction: the task set was enriched for difficulty until frontier models fail routinely.
The HealthBench family
| HealthBench May 2025 | 5,000 multi-turn health conversations with laypeople and professionals, graded on 48,562 physician-written rubric criteria from 262 physicians in 60 countries. |
|---|---|
| HealthBench Hard May 2025 | The 1,000 examples frontier models found hardest at release, with top scores around 0.32 at the time. |
| HealthBench Consensus May 2025 | 3,671 examples scored on 34 behavioral criteria validated by physician consensus, built as a near-zero-error baseline. |
| HealthBench Professional April 2026 | 525 tasks narrowed to what clinicians actually bring to a model at work, drawn from real clinician conversations. The benchmark this site tracks. |
The current ranking of 9 models is on the leaderboard. How the numbers on this site are produced is on the methodology page. Current results for the wider field of healthcare benchmarks are indexed at clinicalbenchmarks.ai.