Even the latest AI models make three systematic reasoning errors, ARC-AGI-3 analysis shows

THE DECODER / 5/2/2026

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The ARC Prize Foundation evaluated 160 game runs of OpenAI’s GPT-5.5 and Anthropic’s Opus 4.7 on the ARC-AGI-3 benchmark.
The analysis found that both models remain below 1% accuracy on tasks that humans can solve easily.
It identified three systematic reasoning error patterns that account for much of the models’ poor performance.
The findings suggest that even state-of-the-art AI still has consistent gaps in core reasoning/understanding required for ARC-AGI-3-style problems.

The ARC Prize Foundation analyzed 160 game runs of OpenAI's GPT-5.5 and Anthropic's Opus 4.7 on the ARC-AGI-3 benchmark. Three systematic error patterns explain why both models stay below 1 percent on tasks that humans can solve without much trouble.

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