math benchmark
HiddenMath
Google DeepMind's internal mathematical reasoning benchmark that introduces novel problems not encountered during model training to evaluate true mathematical reasoning capabilities rather than memorization
Updated Aug 11, 2026
Models13
Model coverage13
MetricScore
EvidenceB
HiddenMath Ranking
Higher score ranks better on this benchmark.
| 1 | GO | 63.0% | 100.0% | 13 | C | |
| 2 | GO | 60.3% | 91.7% | 13 | C | |
| 3 | GO | 55.3% | 83.3% | 13 | C | |
| 4 | GO | 54.5% | 75.0% | 13 | C | |
| 5 | GO | 52.0% | 66.7% | 13 | C | |
| 6 | GO | 47.2% | 58.3% | 13 | C | |
| 7 | GO | 43.0% | 50.0% | 13 | C | |
| 8 | GO | 37.7% | 41.7% | 13 | C | |
| 9 | GO | 37.7% | 33.3% | 13 | C | |
| 10 | GO | 32.8% | 25.0% | 13 | C | |
| 11 | GO | 27.7% | 16.7% | 13 | C | |
| 12 | GO | 27.7% | 8.3% | 13 | C | |
| 13 | GO | 15.8% | 0.0% | 13 | C |
HiddenMath Score Distribution
A closer view of the leading scores on this benchmark.
HiddenMath Highlights
The leading models and scores on this benchmark.
What is HiddenMath?
What HiddenMath measures and how its scores work.
Google DeepMind's internal mathematical reasoning benchmark that introduces novel problems not encountered during model training to evaluate true mathematical reasoning capabilities rather than memorization
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- HiddenMath
- Modality
- text
- Primary category
- math
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- hiddenmath|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about HiddenMath.
Which model scores highest on HiddenMath?
Gemini 2.0 Flash is currently ranked first with 63.0%.
What does HiddenMath measure?
Google DeepMind's internal mathematical reasoning benchmark that introduces novel problems not encountered during model training to evaluate true mathematical reasoning capabilities rather than memorization
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
13 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.