BoolQ
BoolQ is a reading comprehension dataset for yes/no questions containing 15,942 naturally occurring examples. Each example consists of a question, passage, and boolean answer, where questions are generated in unprompted and unconstrained settings. The dataset challenges models with complex, non-factoid information requiring entailment-like inference to solve.
Hermes 3 70B from Nous Research currently leads the BoolQ leaderboard with a score of 0.880 across 10 evaluated AI models.
Hermes 3 70B leads with 88.0%, followed by 
Gemma 2 27B at 84.8% and 
Phi-3.5-MoE-instruct at 84.6%.
Progress Over Time
Interactive timeline showing model performance evolution on BoolQ
BoolQ Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 | Nous Research | 70B | — | — | ||
| 2 | Google | 27B | — | — | ||
| 3 | Microsoft | 60B | — | — | ||
| 4 | Google | 9B | — | — | ||
| 5 | 2B | — | — | |||
| 5 | Google | 8B | — | — | ||
| 7 | Microsoft | 4B | — | — | ||
| 8 | Microsoft | 4B | — | — | ||
| 9 | 2B | — | — | |||
| 9 | Google | 8B | — | — |
FAQ
Common questions about BoolQ.
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