AI2 ARC
Allen Institute for AIA benchmark of 7,787 genuine grade-school science questions assembled to study advanced question answering. The dataset is split into an Easy set and a Challenge set, and it remains one of the canonical multiple-choice reasoning benchmarks for language models.
AI2 Reasoning Challenge (ARC), Allen Institute for AI (Clark et al. 2018, arXiv:1803.05457). 7,787 grade-school science multiple-choice questions: ARC-Challenge (2,590) + ARC-Easy (5,197). Foundational LLM commonsense/reasoning benchmark, still a standard in 2026 model release reports. Verified live June 2026 on huggingface.co/datasets/allenai/ai2_arc.
Openness
5 high confidence- data
- open(7,787 questions, downloadable on HF)
- license
- CC-BY-SA-4.0(open data license, redistributable)
- datasheet
- yes(HF dataset card + arXiv paper)
- access
- public(train/val/test splits all released, not held-out)
Fully open under CC-BY-SA-4.0 with dataset card; the canonical open-data benchmark profile.
- https://huggingface.co/datasets/allenai/ai2_arc recorded 2026-06-04
CC-BY-SA-4.0, 7,787 questions, public splits, dataset card, ~479K downloads last month
Adoption
4 high confidence~479K HF downloads in the last month alone (so >1M cumulative) and one of the most-cited standard reasoning benchmarks routinely reported in frontier model release cards. Strong usage_volume signal as an entrenched evaluation standard.
- https://huggingface.co/datasets/allenai/ai2_arc recorded 2026-06-04
~479,090 downloads in the last month
Capability
not assessedCapability not a meaningful axis for an eval dataset.
Unchanged since 2026-06-09 (last edited, not re-checked)