bge-large-en-v1.5 and bge-base-en-v1.5 are both feature-extraction models. See each entry for specifics.
BGE-Large-EN-v1.5 is BAAI's highest-capacity English embedding model in the v1.5 series, producing 1024-dimensional vectors. It achieves top MTEB retrieval scores among its generation of English-only embedding models, at the cost of higher compute and storage than BGE-small or BGE-base. MIT licensed with ONNX export support.
BGE-Base-EN-v1.5 is BAAI's mid-tier English embedding model in the v1.5 series, producing 768-dimensional vectors. It balances accuracy and compute cost between the small (384d) and large (1024d) variants, making it a practical default for English retrieval tasks where storage and inference overhead of the large model are undesirable. MIT licensed with ONNX export.
Pick based on your compute budget and specific task requirements.