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arXiv · 2505.11831

ARC-AGI-2: A New Challenge for Frontier AI Reasoning Systems

Francois Chollet·Mike Knoop·Gregory Kamradt·Bryan Landers·Henry Pinkard
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Abstract

The Abstraction and Reasoning Corpus for Artificial General Intelligence (ARC-AGI), introduced in 2019, established a challenging benchmark for evaluating the general fluid intelligence of artificial systems via a set of unique, novel tasks only requiring minimal prior knowledge. While ARC-AGI has spurred significant research activity over the past five years, recent AI progress calls for benchmarks capable of finer-grained evaluation at higher levels of cognitive complexity. We introduce ARC-AGI-2, an upgraded version of the benchmark. ARC-AGI-2 preserves the input-output pair task format of its predecessor, ensuring continuity for researchers. It incorporates a newly curated and expanded set of tasks specifically designed to provide a more granular signal to assess abstract reasoning and problem-solving abilities at higher levels of fluid intelligence. To contextualize the difficulty and characteristics of ARC-AGI-2, we present extensive results from human testing, providing a robust baseline that highlights the benchmark's accessibility to human intelligence, yet difficulty for current AI systems. ARC-AGI-2 aims to serve as a next-generation tool for rigorously measuring progress towards more general and human-like AI capabilities.

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Francois Chollet, Mike Knoop, Gregory Kamradt, Bryan Landers, Henry Pinkard. 2025-05-17. ARC-AGI-2: A New Challenge for Frontier AI Reasoning Systems. https://arxiv.org/abs/2505.11831

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