protologue

ARC-AGI

Also called ARC, Abstraction and Reasoning Corpus, ARC-AGI-2, ARC Prize.

ARC-AGI (the Abstraction and Reasoning Corpus) is a benchmark of visual grid puzzles in which a model must infer a transformation rule from a few examples and apply it to a new grid, designed to measure how efficiently a system acquires new skills.

Description

The puzzles are easy for most people but require reasoning that cannot be memorized, because each task is novel. François Chollet introduced it in 2019 alongside a definition of intelligence as skill-acquisition efficiency. Successive versions, such as ARC-AGI-2, were made harder as systems improved, and many results are reported with explicit compute costs.

Sources

  1. Chollet (2019). On the Measure of Intelligence.
  2. Chollet et al. (2025). ARC-AGI-2: A New Challenge for Frontier AI Reasoning Systems.

Cite this entry

Protologue. (2026). ARC-AGI. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.4.0, PTL-0192). https://protologue.com/t/arc-agi/

BibTeX
@misc{protologue_arc_agi,
  title = {ARC-AGI},
  author = {{Protologue}},
  year = {2026},
  howpublished = {Protologue: A Taxonomy of Prompting and LLM Techniques, v1.4.0},
  note = {Entry PTL-0192},
  url = {https://protologue.com/t/arc-agi/}
}

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