GPQA Diamond
GPQA Diamond - Google-Proof Q&A benchmark for graduate-level scientific reasoning.
Category
STEM & Reasoning
Score type
percent
Scale
100%
higher is better
Models tested
57
What is GPQA Diamond?
GPQA Diamond is the 'diamond' subset of the Google-Proof Q&A benchmark — the hardest and cleanest part. The questions are written and checked by PhD scientists and are designed so that a skilled non-expert with full internet access can still barely get them right. The model has to answer graduate-level science questions with four multiple-choice options.
What does it test?
GPQA Diamond measures hard reasoning in science, technology, engineering and math. In detail, it checks:
- expert-level physics, chemistry and biology knowledge
- real reasoning instead of memorised question patterns
- resistance to plausible distractors
- reliability without web access (the questions are not Googleable)
How to read the score
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.
Frequently asked questions
What is the GPQA Diamond benchmark?
GPQA Diamond is the 'diamond' subset of the Google-Proof Q&A benchmark — the hardest and cleanest part. The questions are written and checked by PhD scientists and are designed so that a skilled non-expert with full internet access can still barely get them right. The model has to answer graduate-level science questions with four multiple-choice options.
What does GPQA Diamond test?
GPQA Diamond mainly measures hard reasoning in science, technology, engineering and math. Concretely, it checks: expert-level physics, chemistry and biology knowledge; real reasoning instead of memorised question patterns; resistance to plausible distractors.
How is the GPQA Diamond score calculated?
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better. The declared maximum score of this benchmark is 100.0.
Where do I get GPQA Diamond data and scores?
The official source is https://huggingface.co/datasets/Idavidrein/gpqa. The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/gpqa-diamond/scores) or pull it directly from the Open LLM Radar API with any HTTP client.
Benchmark data & downloads
Where to get, inspect and reuse the data behind this benchmark.
Official benchmark page / paper
The benchmark maintainer's website, paper or leaderboard
Benchmark dataset
The question/task data itself — download and evaluate locally
Benchmark metadata (JSON)
This page's benchmark record from the Open LLM Radar API
All model scores (JSON download)
Full score table as JSON; paginate with limit/offset params
Open LLM Radar API docs
Swagger UI to explore and reuse all radar API endpoints
Model scores 57 models tested
| # | Model | Score | Date | Source | Verified |
|---|---|---|---|---|---|
| 51 |
LFM2.5-8B-A1B
LiquidAI
|
51.3%
|
— | Report | Verified |
| 52 |
Clef-Flash
Cloudflare
|
51%
|
— | Report | Verified |
| 53 |
Clef
Cloudflare
|
48%
|
— | Report | Verified |
| 54 |
Qwen3.5-2B
Qwen Team (Alibaba Cloud)
|
45.6%
|
— | Report | Verified |
| 55 |
Gemma4-E2B
Google
|
43.4%
|
02.07.2026 | Report | Verified |
| 56 |
Gemma3-27B
Google
|
42.4%
|
02.07.2026 | Report | Unverified |
| 57 |
Gemma 3 27B IT
Google DeepMind
|
41.41%
|
27.02.2025 | Report | Verified |