What is the MTEB benchmark and what does it measure?

The Massive Text Embedding Benchmark, or MTEB, is a public leaderboard that evaluates embedding models across more than 50 tasks in eight categories including retrieval, classification, clustering, and semantic similarity. It was introduced by Muennighoff and colleagues in 2022 and is hosted on Hugging Face. MTEB lets practitioners compare models using a single composite score, but high ranking does not guarantee strong performance on a specific domain. Treat MTEB as a starting filter, not a final answer for production model selection.