BAAI /

bge-base-en-v1.5

3 DZD in / 1M tokens

bge-base-en-v1.5 is an open-source text embedding model developed by the Beijing Academy of Artificial Intelligence (BAAI). Built upon a 109-million parameter BERT-base encoder architecture, it maps text into a dense 768-dimensional vector space optimized for semantic search, dense retrieval, and Retrieval-Augmented Generation (RAG) pipelines. Version 1.5 refines similarity score distributions and delivers top-tier performance on the Massive Text Embedding Benchmark (MTEB) while maintaining extremely low latency and hardware requirements.