ARC Prize

ARC Prize is among the most credible and closely watched benchmarks in AI research, and it earns that reputation by design rather than hype. Francois Chollet built the underlying ARC-AGI corpus specifically to resist the shortcut that undermines most other benchmarks: memorization from massive training data. The novel visual-grid puzzles are deliberately easy for humans and hard for models that lack genuine skill-acquisition and abstraction ability, which is why frontier labs treat their scores here as meaningful signals rather than marketing checkboxes, OpenAI's o3 announcement leaned directly on its ARC-AGI result. The leaderboards plotting model performance against compute cost across ARC-AGI-1, -2, and the newer agentic ARC-AGI-3 give researchers and practitioners an unusually honest lens on real reasoning progress versus brute-force scaling. Running the competition through Kaggle with over $2 million in prizes and a mandatory open-source requirement for winners is a smart way to keep the field's best ideas public rather than locked inside a single lab. Everything here, datasets, leaderboards, and competition materials, is free and open, funded by donations rather than a product to sell. For anyone tracking genuine AI reasoning capability rather than benchmark gaming, this is close to essential.