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BGE-M3

BGE-M3 is a versatile embedding model from the Beijing Academy of Artificial Intelligence that supports dense retrieval, multi-vector retrieval, and sparse retrieval for text embeddings. It is designed to work in over 100 languages and can handle inputs ranging from short sentences to long documents of up to 8192 tokens.

Key Information

  • Category: Language Models
  • Source: Huggingface
  • Tags: sentence-similarity
  • Last updated: January 09, 2026

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Canonical source: https://huggingface.co/BAAI/bge-m3

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