BAAI /

bge-large-en-v1.5

5 DZD in / 1M tokens

bge-large-en-v1.5 is a high-performance open-source text embedding model developed by the Beijing Academy of Artificial Intelligence (BAAI). Built on a 335-million parameter BERT-large encoder architecture, it maps text into a dense 1024-dimensional vector space optimized for semantic search, retrieval-augmented generation (RAG), and zero-shot ranking. Version 1.5 improves similarity score distribution and delivers top-tier performance across the Massive Text Embedding Benchmark (MTEB) while balancing embedding accuracy with practical inference latency.