← All models
baai
BAAI: bge-m3
The bge-m3 embedding model encodes sentences, paragraphs, and long documents into a 1024-dimensional dense vector space, delivering high-quality semantic embeddings optimized for multilingual retrieval, semantic search, and large-context applications.
8,194 context
Modalities:text->embeddings
Released:11/17/2025
The bge-m3 embedding model encodes sentences, paragraphs, and long documents into a 1024-dimensional dense vector space, delivering high-quality semantic embeddings optimized for multilingual retrieval, semantic search, and large-context applications.
Weekly tokens
26.6B
Tokens generated this week (network-wide)
Usage by period
Today1.2K tokens
This week15.7M tokens
This month16.8M tokens
Trending15.7M tokens