Global-MMLU

A comprehensive multilingual benchmark covering 42 languages that addresses cultural and linguistic biases in evaluation, with improved translation quality and culturally sensitive question subsets.

Gemma 3n E4B Instructed from Google currently leads the Global-MMLU leaderboard with a score of 0.603 across 4 evaluated AI models.

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Progress Over Time

Interactive timeline showing model performance evolution on Global-MMLU

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Global-MMLU Leaderboard

4 models
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FAQ

Common questions about Global-MMLU.

What is the Global-MMLU benchmark?

A comprehensive multilingual benchmark covering 42 languages that addresses cultural and linguistic biases in evaluation, with improved translation quality and culturally sensitive question subsets.

What is the Global-MMLU leaderboard?

The Global-MMLU leaderboard ranks 4 AI models based on their performance on this benchmark. Currently, Gemma 3n E4B Instructed by Google leads with a score of 0.603. The average score across all models is 0.577.

What is the highest Global-MMLU score?

The highest Global-MMLU score is 0.603, achieved by Gemma 3n E4B Instructed from Google.

How many models are evaluated on Global-MMLU?

4 models have been evaluated on the Global-MMLU benchmark, with 0 verified results and 4 self-reported results.

Where can I find the Global-MMLU paper?

The Global-MMLU paper is available at https://arxiv.org/abs/2412.03304. The paper details the methodology, dataset construction, and evaluation criteria.

What categories does Global-MMLU cover?

Global-MMLU is categorized under general, language, and reasoning. The benchmark evaluates text models with multilingual support.

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