language benchmark
CommonSenseQA is a multiple-choice question answering dataset that requires different types of commonsense knowledge to predict correct answers. It contains 12,102 questions with one correct answer and four distractors, designed to test semantic reasoning and conceptual relationships. Questions are created based on ConceptNet concepts and require prior world knowledge for accurate reasoning.
Updated Aug 11, 2026
Higher score ranks better on this benchmark.
| 01 | MA | 70.4% | 100.0% | 1 | C |
The leading models and scores on this benchmark.
What CommonSenseQA measures and how its scores work.
CommonSenseQA is a multiple-choice question answering dataset that requires different types of commonsense knowledge to predict correct answers. It contains 12,102 questions with one correct answer and four distractors, designed to test semantic reasoning and conceptual relationships. Questions are created based on ConceptNet concepts and require prior world knowledge for accurate reasoning.
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 CommonSenseQA.
Mistral NeMo Instruct is currently ranked first with 70.4%.
CommonSenseQA is a multiple-choice question answering dataset that requires different types of commonsense knowledge to predict correct answers. It contains 12,102 questions with one correct answer and four distractors, designed to test semantic reasoning and conceptual relationships. Questions are created based on ConceptNet concepts and require prior world knowledge for accurate reasoning.
Yes. Higher values rank better for this benchmark.
1 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.