MMLU C

AI benchmark · Knowledge

Domains
Knowledge
Tier
C why
Snapshot

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.

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

  • Open Medical-LLM Leaderboard

    “A leaderboard that scores LLMs by accuracy on medical question-answering datasets including MedQA, MedMCQA, PubMedQA and medical MMLU subsets.”

Tier C

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.

@dextune ↗ · @dongxi_nlp ↗ · @chronollm ↗

How we got to tier C
  1. Adoption: 5 models scored. Tier C.
  2. 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.
  3. In curated RL directories: 2 points, a floor of C.
  4. 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

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Next: browse all benchmarks. Entry from the RL Research daily scrape of public sources, 2026-11-05 snapshot.