MMLU Chat

Chat-format variant 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. This version uses conversational prompting format for model evaluation.

Llama 3.1 Nemotron 70B Instruct from NVIDIA currently leads the MMLU Chat leaderboard with a score of 0.806 across 1 evaluated AI models.

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Progress Over Time

Interactive timeline showing model performance evolution on MMLU Chat

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MMLU Chat Leaderboard

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FAQ

Common questions about MMLU Chat.

What is the MMLU Chat benchmark?

Chat-format variant 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. This version uses conversational prompting format for model evaluation.

What is the MMLU Chat leaderboard?

The MMLU Chat leaderboard ranks 1 AI models based on their performance on this benchmark. Currently, Llama 3.1 Nemotron 70B Instruct by NVIDIA leads with a score of 0.806. The average score across all models is 0.806.

What is the highest MMLU Chat score?

The highest MMLU Chat score is 0.806, achieved by Llama 3.1 Nemotron 70B Instruct from NVIDIA.

How many models are evaluated on MMLU Chat?

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

Where can I find the MMLU Chat paper?

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

What categories does MMLU Chat cover?

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

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