GPQA: Google-Proof Q&A
PhD-level multiple-choice questions in biology, physics, and chemistry designed so that even experts with internet access score below 67%. The Diamond subset (198 questions) is the hardest variant used in most frontier model evaluations.
Models ranked
160
tracked on this benchmark
Score band
94.6 – 25.2
best → lowest tracked
Snapshot trend
-0.90
Aug 12 → Aug 26 · 1 models
Leaderboard
Tracked models ranked by Accuracy (higher is better).
Notes: Confidence: medium. DAT-3780 weekly best-of refresh: multiple secondary trackers agree on 94.6%; pending an Anthropic primary score.
Notes: Official GPT-5.6 GA launch benchmark row. Uses the repo canonical gpqa slug for the GPQA Diamond variant.
Notes: Uses the repo canonical gpqa slug for the GPQA Diamond variant; do not create a duplicate gpqa-diamond benchmark.
Notes: Official Anthropic launch benchmark using the repo canonical gpqa slug for GPQA Diamond.
Notes: Model variant: Kimi K3 (max reasoning effort). Benchmark variant: GPQA-Diamond. Harness/evaluator not disclosed by Moonshot. Source posture: Moonshot/Kimi self-reported launch table; confidence: medium because the value is vendor-reported and not independently reproduced. Recommended seed value: 93.5.
Notes: Confidence: medium. DAT-3780 weekly best-of refresh: secondary sources report about 89.5%; pending a Meta primary score.
How to read this benchmark
This benchmark scores models where higher is better. Use scores for directional filtering and shortlisting, not universal quality ranking; then validate pricing, context window, provider availability, and fit for your workload.
Trust this score when
- There is a fresh timestamped snapshot (or multiple snapshots) for this benchmark.
- The model list covers the same version family you can actually deploy today.
- Top candidates overlap with your required routing and feature requirements.
Be cautious when
- There is only one benchmark snapshot or the dataset appears stale.
- The benchmark metric direction is opposite of your decision objective.
- The score difference between options is narrow and likely within implementation variance.
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Last reviewed: Apr 15, 2026