BAAI: bge-large-en-v1.5

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.

• Context window: 8,192 tokens
• Input: text
• Output: embeddings
• Pricing: $0.01/M input tokens

View on OpenRouter. Model data sourced from OpenRouter.