MMLU-Base

Base version of the Massive Multitask Language Understanding benchmark, evaluating language models across 57 tasks including elementary mathematics, US history, computer science, law, and other professional and academic subjects. Designed to comprehensively measure the breadth and depth of a model's academic and professional understanding.

Qwen2.5-Coder 7B Instruct from Alibaba Cloud / Qwen Team currently leads the MMLU-Base leaderboard with a score of 0.680 across 1 evaluated AI models.

Paper

Alibaba Cloud / Qwen TeamQwen2.5-Coder 7B Instruct leads with 68.0%.

Progress Over Time

Interactive timeline showing model performance evolution on MMLU-Base

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MMLU-Base Leaderboard

1 models
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1
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
7B
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FAQ

Common questions about MMLU-Base.

What is the MMLU-Base benchmark?

Base version of the Massive Multitask Language Understanding benchmark, evaluating language models across 57 tasks including elementary mathematics, US history, computer science, law, and other professional and academic subjects. Designed to comprehensively measure the breadth and depth of a model's academic and professional understanding.

What is the MMLU-Base leaderboard?

The MMLU-Base leaderboard ranks 1 AI models based on their performance on this benchmark. Currently, Qwen2.5-Coder 7B Instruct by Alibaba Cloud / Qwen Team leads with a score of 0.680. The average score across all models is 0.680.

What is the highest MMLU-Base score?

The highest MMLU-Base score is 0.680, achieved by Qwen2.5-Coder 7B Instruct from Alibaba Cloud / Qwen Team.

How many models are evaluated on MMLU-Base?

1 models have been evaluated on the MMLU-Base benchmark, with 0 verified results and 1 self-reported results.

Where can I find the MMLU-Base paper?

The MMLU-Base paper is available at https://arxiv.org/abs/2009.03300. The paper details the methodology, dataset construction, and evaluation criteria.

What categories does MMLU-Base cover?

MMLU-Base is categorized under finance, general, healthcare, language, legal, math, and reasoning. The benchmark evaluates text models.

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