MTEB is a Python framework for evaluating embeddings and retrieval systems for both text and image.
MTEB covers more than 1000 languages and diverse tasks, from classics like classification and clustering to use-case specialized tasks such as legal, code, or healthcare retrieval.
Code, datasets, and results for "The Embedder's Dilemma: LLMs Are Better, but at What Cost?" (COLM 2026). MTEB(LLM) benchmarks 10 LLMs and 26 embedding models on 37 tasks with full cost and through…
Code, datasets, and results for "The Embedder's Dilemma: LLMs Are Better, but at What Cost?" (COLM 2026). MTEB(LLM) benchmarks 10 LLMs and 26 embedding models on 37 tasks with full cost and throughput accounting.
embeddings-benchmark/embedders-dilemma's past year of commit activity
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