MMLU-Pro: Next-Gen AI Evaluation Benchmark

MMLU-Pro, introduced in 2024, is an advanced benchmark for Measuring massive multitask language Understanding in AI models. It features over 12,000 questions and 10-option multiple choice, providing better model differentiation. This benchmark significantly impacts how we evaluate AI performance, showing larger gaps between top models.

Prashant Pathak1 Aug, 2026

MMLU-Pro represents a crucial advancement in evaluating Artificial Intelligence models. Introduced in 2024, it helps assess broad knowledge across many subjects. This benchmark offers a robust method for Measuring massive multitask language Understanding, pushing the boundaries of AI assessment. It plays a key role in understanding and ranking advanced AI systems today.

MMLU-Pro vs. Original MMLU

The MMLU-Pro benchmark significantly upgrades AI evaluation compared to the original MMLU. It uses over 12,000 questions with a 10-option multiple-choice format. This expanded answer base profoundly impacts model performance evaluation. Model accuracy on MMLU-Pro typically drops by 16% to 33% from original MMLU scores. This larger drop provides better differentiation among top-performing models. For instance, GPT-4o and GPT-4-Turbo showed a 1% gap on standard MMLU. On MMLU-Pro, this spread widens to 9%, clearly showing distinct performance levels.

Improved Evaluation and Reasoning

MMLU-Pro's design enhances evaluation by reducing prompt sensitivity. Previously, MMLU showed about 4% to 5% sensitivity to prompt variations. MMLU-Pro lowers this to an estimated 2%. This makes evaluations more reliable. The benchmark also strengthens reasoning assessment. Reasoning methods, like chain-of-thought, yield much better performance on MMLU-Pro. These methods outperform direct answer strategies, highlighting the benchmark's ability to test deeper AI understanding.

Leading Model Performance

As of early 2026, top model performance on MMLU-Pro shows tight clustering. The leading 15 models all score above 87%. Google’s Gemini-3.1-Pro leads with 91.2%. Gemini-3-Pro (Thinking) follows at 90.1%, and GPT-o1 at 89.3%. Models using thinking strategies rank higher, surpassing their standard counterparts. These standard models generally cluster in the 87% to 88% range. The overall difference between the top-ranked and 15th-ranked model is just over 4 percentage points. This illustrates intense competition in broad knowledge tasks among frontier AI models.

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MMLU-Pro FAQs

What is MMLU-Pro?

MMLU-Pro is an advanced benchmark for evaluating AI models' general knowledge and reasoning skills. It was introduced in 2024.

How does MMLU-Pro differ from the original MMLU?

MMLU-Pro features over 12,000 questions and 10 multiple-choice options. This design leads to a 16%–33% drop in model accuracy compared to the original MMLU.