math benchmark
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
Higher score ranks better on this benchmark.
| 01 | GO | 63.0% | 100.0% | 13 | C | |
| 02 | GO | 60.3% | 91.7% | 13 | C | |
| 03 | GO | 55.3% | 83.3% | 13 | C | |
| 04 | GO | 54.5% | 75.0% | 13 | C | |
| 05 | GO | 52.0% | 66.7% | 13 | C | |
| 06 | GO | 47.2% | 58.3% | 13 | C | |
| 07 | GO | 43.0% | 50.0% | 13 | C | |
| 08 | GO | 37.7% | 41.7% | 13 | C | |
| 09 | 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 |
A closer view of the leading scores on this benchmark.
The leading models and scores on this benchmark.
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.
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about HiddenMath.
Gemini 2.0 Flash is currently ranked first with 63.0%.
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
Yes. Higher values rank better for this benchmark.
13 model results are currently shown.
Yes. This benchmark can contribute to the current LLMBoard capability score.