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ModelTerms

Comparison

ARC-AGI vs MMLU

ARC-AGI and MMLU are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.

When you would reach for ARC-AGI

ARC-AGI comes up when the question is fundamentally about evaluation.

A grid puzzle where you must learn a transformation from 3 examples and apply it to a new grid.

When you would reach for MMLU

MMLU comes up when the question is fundamentally about evaluation.

GPT-4: 86.4% MMLU (5-shot, original release).

Frequently asked

What is the difference between ARC-AGI and MMLU?

ARC-AGI: ARC-AGI (Abstraction and Reasoning Corpus) is a benchmark of grid-puzzle tasks designed to require fluid reasoning rather than memorization. Humans score 85%; models stayed below 5% for years. MMLU: MMLU is a benchmark of ~16K multiple-choice questions across 57 subjects from elementary to professional. It is one of the most widely cited LLM benchmarks.

When should I use ARC-AGI vs MMLU?

ARC-AGI is the right concept when you are focused on evaluation. MMLU applies when you are focused on evaluation.

Are ARC-AGI and MMLU the same thing?

No. ARC-AGI is evaluation; MMLU is evaluation. They are related but address different parts of the AI stack.