BAAI /

bge-m3

5 DZD in / 1M tokens

bge-m3 is a state-of-the-art multi-lingual, multi-functionality, and multi-granularity text embedding model developed by the Beijing Academy of Artificial Intelligence (BAAI). Built on a 567-million parameter XLM-RoBERTa architecture, it supports over 100 languages and processes input sequences up to 8,192 tokens. It is uniquely engineered to output dense embeddings, lexical/sparse weights (similar to SPLADE), and multi-vector representations (ColBERT-style) simultaneously within a single forward pass, making it a foundational engine for versatile hybrid search and RAG systems.