Massive Text Embedding Benchmark (MTEB)

MTEB (Massive Text Embedding Benchmark) is a Python framework for evaluating embeddings and retrieval systems across diverse NLP tasks, including classification, clustering, retrieval, reranking, and semantic textual similarity. It supports over 1000 languages and various modalities like text and image, with continuous expansion. As of version 2.12.16, it aims to provide a standardized, comprehensive, and reproducible way to compare embedding models. The library maintains a frequent release cadence with minor updates often occurring weekly.