# o1-mini benchmark scores

OpenAI · model · https://benchgap.net/model/o1-mini · data retrieved 2026-10-29

As of 2026-10-29, o1-mini (OpenAI) has measured scores on 7 benchmarks and estimated scores on 21 more.

| Benchmark | Score | Source |
|---|---|---|
| [AA-GPQA Diamond](https://benchgap.net/b/aa-gpqa-diamond/current.md) | 60.3% | measured |
| [AA-HLE](https://benchgap.net/b/aa-hle/current.md) | 3.6% | measured |
| [CritPt](https://benchgap.net/b/critpt/current.md) | 0.0% | estimated ± 0.3 pp, high confidence |
| [GPQA Diamond](https://benchgap.net/b/gpqa-diamond/current.md) | 60.3% | estimated ± 1.2 pp, high confidence |
| [HLE](https://benchgap.net/b/hle/current.md) | 4.7% | estimated ± 6.9 pp, low confidence |
| [MMLU-Pro](https://benchgap.net/b/mmlu-pro/current.md) | 72.9% | estimated ± 4.0 pp, high confidence |
| [AIME 2024](https://benchgap.net/b/aime2024/current.md) | 36.7% | estimated ± 8.2 pp, medium confidence |
| [Artificial Analysis Intelligence Index](https://benchgap.net/b/artificialanalysis/current.md) | 9.8% | measured |
| [BBH](https://benchgap.net/b/bbh/current.md) | 90.1% | estimated ± 2.4 pp, low confidence |
| [GPQA](https://benchgap.net/b/gpqa/current.md) | 60.0% | measured |
| [MMLU](https://benchgap.net/b/mmlu/current.md) | 85.2% | measured |
| [AA-Omniscience Accuracy](https://benchgap.net/b/omniscienceaccuracy/current.md) | 17.1% | estimated ± 1.5 pp, high confidence |
| [MATH-500](https://benchgap.net/b/math-500/current.md) | 90.0% | measured |
| [MMMLU](https://benchgap.net/b/mmmlu/current.md) | 78.3% | estimated ± 1.7 pp, high confidence |
| [AA MMLU-Pro](https://benchgap.net/b/aa-mmlu-pro/current.md) | 83.4% | estimated ± 1.0 pp, low confidence |
| [AIME 2025](https://benchgap.net/b/aime2025/current.md) | 34.7% | estimated ± 14.2 pp, low confidence |
| [ARC-AGI-1](https://benchgap.net/b/arcagi1/current.md) | 60.0% | estimated ± 8.1 pp, low confidence |
| [ARC-AGI-2](https://benchgap.net/b/arc-agi-2/current.md) | 30.7% | estimated ± 14.6 pp, low confidence |
| [Vals GPQA Diamond](https://benchgap.net/b/vals-gpqa-diamond/current.md) | 81.3% | estimated ± 5.3 pp, low confidence |
| [Vals MMLU-Pro](https://benchgap.net/b/vals-mmlu-pro/current.md) | 83.9% | estimated ± 2.1 pp, medium confidence |
| [HLE w/o tools](https://benchgap.net/b/hlenotools/current.md) | 29.0% | estimated ± 4.6 pp, medium confidence |
| [ARC-AGI-3](https://benchgap.net/b/arcagi3/current.md) | 1.4% | estimated ± 7.7 pp, low confidence |
| [C-Eval](https://benchgap.net/b/ceval/current.md) | 88.5% | estimated ± 1.0 pp, medium confidence |
| [MMLU-Redux](https://benchgap.net/b/mmluredux/current.md) | 90.3% | estimated ± 1.2 pp, medium confidence |
| [SuperGPQA](https://benchgap.net/b/supergpqa/current.md) | 42.5% | estimated ± 8.2 pp, low confidence |
| [HealthBench (length-adjusted)](https://benchgap.net/b/healthbenchlengthadjusted/current.md) | 53.9% | estimated ± 3.3 pp, medium confidence |
| [HealthBench Professional (raw)](https://benchgap.net/b/healthbenchprofessionalraw/current.md) | 50.5% | estimated ± 8.6 pp, low confidence |
| [SimpleQA](https://benchgap.net/b/simpleqa/current.md) | 7.6% | measured |