ARC-AGI Methodology — Methodology

How it works

• Each task: 3–5 input/output grid pairs demonstrating a rule, then a test input.
• Model must produce the correct output grid.
• Tasks are private and rotated to prevent training contamination.

Strengths

• Strong contamination resistance
• Tests generalization, not recall

Limitations

• Small eval set
• Grid format is unusual for LLMs

Best use cases

• AGI-progress measurement
• Reasoning-model stress test

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