physics benchmark
GPQA Physics is the physics subset of GPQA, containing challenging multiple-choice questions written by domain experts in physics.
Updated Sep 5, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelOP | Score92.80% | 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 gpqa physics 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
o1 currently leads GPQA Physics with 92.80%. 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 GPQA Physics measures and how its scores work.
A benchmark consisting of challenging multiple-choice physics questions written by domain experts and requiring graduate-level knowledge and reasoning.
It measures Score, reported as a ratio.
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 GPQA Physics.
o1 is currently ranked first with 92.80%.
The current leaders are o1 (92.80%).
o1 has the lowest matched official input price at $15 input / $60 output per 1M tokens.
The fastest matched records are o1 (66.00 tok/s via OpenAI).
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.
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.