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.
What MMLU Chat measures
MMLU Chat is a text benchmark that evaluates large language models on language, legal, math, reasoning, finance, general, and healthcare tasks. LLM Stats tracks 1 model on this benchmark, with a maximum possible score of 1. Current average across reported models is 0.8, with the leader reaching 0.8.
Compare leaders on the best AI for language, best AI for legal, best AI for math, best AI for reasoning, best AI for finance, best AI for general and best AI for healthcare leaderboards.
Publication
- Paper
- Measuring Massive Multitask Language Understanding
- Authors
- Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, and 3 others
- Published
- arXiv
- 2009.03300
Abstract
We propose a new test to measure a text model's multitask accuracy. The test covers 57 tasks including elementary mathematics, US history, computer science, law, and more. To attain high accuracy on this test, models must possess extensive world knowledge and problem solving ability. We find that while most recent models have near random-chance accuracy, the very largest GPT-3 model improves over random chance by almost 20 percentage points on average. However, on every one of the 57 tasks, the best models still need substantial improvements before they can reach expert-level accuracy. Models also have lopsided performance and frequently do not know when they are wrong. Worse, they still have near-random accuracy on some socially important subjects such as morality and law. By comprehensively evaluating the breadth and depth of a model's academic and professional understanding, our test can be used to analyze models across many tasks and to identify important shortcomings.
Llama 3.1 Nemotron 70B Instruct leads with 80.6%.
Progress Over Time
Interactive timeline showing model performance evolution on MMLU Chat
MMLU Chat Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 | 70B | — | — |
FAQ
Common questions about MMLU Chat.
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