physics benchmark
Global PIQA is a multilingual commonsense reasoning benchmark that evaluates physical interaction knowledge across 100 languages and cultures. It tests AI systems' understanding of physical world knowledge in diverse cultural contexts through multiple choice questions about everyday situations requiring physical commonsense.
Updated Aug 11, 2026
Higher score ranks better on this benchmark.
| 01 | GO | 93.4% | 100.0% | 13 | C | |
| 02 | GO | 92.8% | 91.7% | 13 | C | |
| 03 | AC | 91.4% | 83.3% | 13 | C | |
| 04 | AC | 90.3% | 75.0% | 13 | C | |
| 05 | AC | 89.8% | 66.7% | 13 | C | |
| 06 | AC | 89.8% | 58.3% | 13 | C | |
| 07 | AC | 88.4% | 50.0% | 13 | C | |
| 08 | AC | 87.5% | 41.7% | 13 | C | |
| 09 | AC | 86.6% | 33.3% | 13 | C | |
| 10 | AC | 83.2% | 25.0% | 13 | C | |
| 11 | AC | 78.9% | 16.7% | 13 | C | |
| 12 | AC | 69.3% | 8.3% | 13 | C | |
| 13 | AC | 59.4% | 0.0% | 13 | C |
A closer view of the leading scores on this benchmark.
The leading models and scores on this benchmark.
What Global PIQA measures and how its scores work.
Global PIQA is a multilingual commonsense reasoning benchmark that evaluates physical interaction knowledge across 100 languages and cultures. It tests AI systems' understanding of physical world knowledge in diverse cultural contexts through multiple choice questions about everyday situations requiring physical commonsense.
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 Global PIQA.
Gemini 3 Pro is currently ranked first with 93.4%.
Global PIQA is a multilingual commonsense reasoning benchmark that evaluates physical interaction knowledge across 100 languages and cultures. It tests AI systems' understanding of physical world knowledge in diverse cultural contexts through multiple choice questions about everyday situations requiring physical commonsense.
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.