A translated / multilingual version of the MMLU (Measuring Massive Multitask Language Understanding) benchmark adapted for multilingual evaluation. MMLU is a 57-task, multiple-choice benchmark covering subjects across humanities, social sciences, and STEM requiring broad world knowledge and problem-solving. The "okapi MMLU (translated)" assets on Hugging Face provide MMLU questions and answers translated into multiple languages (examples on HF include many languages such as id, vi, ar, bn, de, es, fr, etc.). The translated MMLU variants are commonly used for multilingual few-shot evaluation (the Okapi paper reports using translated MMLU in 5-shot evaluations). License on the HF repos is listed as CC-BY-NC-4.0. Source references: the original MMLU paper (Hendrycks et al., arXiv:2009.03300) and the Okapi project (Okapi: instruction-tuned LLMs; arXiv:2307.16039) and the Hugging Face dataset pages (e.g., jon-tow/okapi_mmlu and SEACrowd/okapi_m_mmlu).
Accuracy is the reported evaluation metric for okapi MMLU (translated). Codesota tracks published model scores on this metric so readers can compare state-of-the-art results across sources and model families.
Higher is better
| Rank | Model | Trust | Score | Year | Source |
|---|---|---|---|---|---|
| 01 | Qwen2.5-72B-Instruct | paper | 79.97 | N/A | Source ↗ |