BIG-Bench Extra Hard
BIG-Bench Extra Hard (BBEH) is a challenging benchmark that replaces each task in BIG-Bench Hard with a novel task that probes similar reasoning capabilities but exhibits significantly increased difficulty. The benchmark contains 23 tasks testing diverse reasoning skills including many-hop reasoning, causal understanding, spatial reasoning, temporal arithmetic, geometric reasoning, linguistic reasoning, logic puzzles, and humor understanding. Designed to address saturation on existing benchmarks where state-of-the-art models achieve near-perfect scores, BBEH shows substantial room for improvement with best models achieving only 9.8-44.8% average accuracy.
Gemma 4 31B from Google currently leads the BIG-Bench Extra Hard leaderboard with a score of 0.744 across 9 evaluated AI models.
Gemma 4 31B leads with 74.4%, followed by Gemma 4 26B-A4B at 64.8% and Gemma 4 E4B at 33.1%.
Progress Over Time
Interactive timeline showing model performance evolution on BIG-Bench Extra Hard
BIG-Bench Extra Hard Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 | Google | 31B | 262K | $0.14 / $0.40 | ||
| 2 | Google | 25B | 262K | $0.13 / $0.40 | ||
| 3 | Google | 8B | — | — | ||
| 4 | Google | 5B | — | — | ||
| 5 | Google | 27B | — | — | ||
| 6 | Google | 12B | — | — | ||
| 7 | Google | — | — | — | ||
| 8 | Google | 4B | — | — | ||
| 9 | Google | 1B | — | — |
FAQ
Common questions about BIG-Bench Extra Hard.
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