LLM Reference
GPQAactiveReasoning

GPQA: Google-Proof Q&A

Metric: Accuracy (higher is better)Introduced: 2023

About

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.Compare model scores alongside pricing, API availability, and release date — high benchmark score alone doesn't make a model the right pick.

How to read this benchmark

This benchmark uses a scoring system where higher is better. Scores are useful for directional filtering and model shortlisting, not for universal quality ranking.

Interpretation checklist: prefer benchmarks that are closest to your workload style, then validate against the linked model pages for pricing, context window, and provider availability.

Trust when:

  • There is a fresh timestamped snapshot (or multiple snapshots) for this benchmark.
  • Model list covers the same version family you can actually deploy today.
  • Top candidates overlap with your required routing and feature requirements.

Don't trust when:

  • There is only one benchmark snapshot or the dataset appears stale.
  • Benchmark metric direction is opposite of your decision objective.
  • The score difference between options is narrow and likely within implementation variance.

Current modeled score band for tracked entries is roughly 94.6 – 93.6.

Window

May 28 to Jun 3

last 3 snapshots

Mean delta

-14.80

score points

Coverage

1

models in latest snapshot

Leaderboard preview (top 5)

  1. 1. Claude Mythos Preview94.6
  2. 2. Gemini 3.1 Pro Preview94.3
  3. 3. Claude Opus 4.794.2
  4. 4. GPT-5.593.6
  5. 5. GPT-5.5 Pro93.6