MMLU C
AI benchmark · Knowledge
What is MMLU?
MMLU measures a text model's multitask accuracy across 57 multiple-choice subjects, testing world knowledge and problem solving from elementary to professional level.
“The test covers 57 tasks including elementary mathematics, US history, computer science, law, and more.”
arxiv.org/abs/2009.03300 ↗“they still have near-random accuracy on some socially important subjects such as morality and law.”
arxiv.org/abs/2009.03300 ↗“The test covers 57 tasks including elementary mathematics, US history, computer science, law, and more.”
arxiv.org/abs/2009.03300 ↗General capability
“To attain high accuracy on this test, models must possess extensive world knowledge and problem solving ability.”
arxiv.org/abs/2009.03300 ↗
Paper: arxiv.org/abs/2009.03300 ↗
Lineage
Benchmarks this one is built on and built from: versions, subsets, extensions and the indexes that combine them.
Derived benchmarks
Edge LLM Leaderboard: Raspberry Pi 5 extension
“Benchmarks throughput, memory/model size, and MMLU accuracy of quantized LLMs running locally on a Raspberry Pi 5 (8GB) edge device.”
HELM MMLU extension
“HELM's MMLU leaderboard scores language models by exact-match accuracy on the Massive Multitask Language Understanding multiple-choice knowledge exam, within Stanford CRFM's holistic evaluation framework.”
MMLU Medical Genetics subset
MMLU Professional Medicine subset
MMLU-Pro extension
MMLU-ProX extension
MMLU-Redux extension
MMLU-STEM subset
MMMLU extension
“MMMLU measures multilingual general knowledge by testing models on the MMLU test set professionally translated into 14 languages.”
Open Italian LLM Leaderboard extension
“A leaderboard that scores open LLMs on Italian-language benchmarks translated into Italian, such as MMLU, ARC Challenge and HellaSwag.”
Open Multilingual LLM Evaluation Leaderboard extension
“A leaderboard ranking LLMs across 29 mostly non-English languages on machine-translated ARC, HellaSwag, MMLU and TruthfulQA.”
Included in
“A leaderboard that scores LLMs by accuracy on medical question-answering datasets including MedQA, MedMCQA, PubMedQA and medical MMLU subsets.”
Tier C
Niche: a handful of models scored, or built by an RL vendor.
How much stands behind a tier: usage, who backs it, a confirmed line from its own site or paper, and a clear read on X. High with three of the four, medium with two, low otherwise.
- 5 models scored
- in curated RL directories (2 pts)
On X · mixed, moderate buzz, from 10 posts about MMLU in the last month
MMLU still appears routinely in model release scorecards, mostly as MMLU-Pro, but is widely described as saturated, contamination-prone, and sensitive to how it is run.
How we got to tier C
- Adoption: 5 models scored. Tier C.
- On X: mixed, moderate buzz. “MMLU still appears routinely in model release scorecards, mostly as MMLU-Pro, but is widely described as saturated, contamination-prone, and sensitive to how it is run.” No move.
- In curated RL directories: 2 points, a floor of C.
- Confirmed: a line from its own site or paper places it.
A clear view on X moves a tier one step up or down; most entries don't move. How tiers work.
Where MMLU sits
Its domain on the map, live. Hover a logo for its name; click to open it. Open it on the full map
Next: browse all benchmarks. Entry from the RL Research daily scrape of public sources, 2026-11-05 snapshot.