bge-small-en-v1.5

bge-small-en-v1.5 is a lightweight English embedding model from BAAI designed for semantic search, retrieval, similarity scoring, ranking, and RAG workflows. It converts text into 384-dimensional dense embeddings that capture semantic meaning, making it well suited for finding related documents, matching queries to content, clustering text, and powering vector search. Its compact size makes it a strong choice for high-volume embedding workloads where latency and cost matter.