The bge-large-en-v1.5 embedding model maps English sentences, paragraphs, and documents into a 1024-dimensional dense vector space, delivering high-fidelity semantic embeddings optimized for semantic search, document retrieval, and downstream NLP tasks in English.
Recent activity on bge-large-en-v1.5
Total usage per day on OpenRouter
Prompt
342M
Completion
0
Prompt tokens measure input size. Reasoning tokens show internal thinking before a response. Completion tokens reflect total output length.