A suite of 23 challenging tasks from the BIG-Bench collaborative benchmark where prior language models failed to exceed average human performance, even with chain-of-thought prompting.
Mirac Suzgun, Nathan Scales, Nathanael Schärli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc V. Le, Ed H. Chi, Denny Zhou, Jason Wei
Category
Reasoning
Version
2022
Direction
higher is better
Ranking use
Reference
Contamination risk
Unknown
A suite of 23 challenging tasks from the BIG-Bench collaborative benchmark where prior language models failed to exceed average human performance, even with chain-of-thought prompting. Results stay tied to the exact model variant and evaluation system. Multiple systems for the same model use the best published score on this page; overall Lumina scoring uses the median of ranking-eligible rows.
A suite of 23 challenging tasks from the BIG-Bench collaborative benchmark where prior language models failed to exceed average human performance, even with chain-of-thought prompting.
Which model scores highest on BIG-Bench Hard?
DeepSeek V4 Pro Base by DeepSeek currently leads with 87.5%.
How many models are evaluated on BIG-Bench Hard?
5 models in the LuminaBench cohort have a qualifying score on this benchmark.