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BAAI: bge-large-en-v1.5

BAAI: bge-large-en-v1.5 is an embeddings model from Baai, with a 512-token context window, priced at $0.01 / 1M tokens. Fully Informed benchmarks and compares models like BAAI: bge-large-en-v1.5 across the whole OpenRouter catalogue.

Vendor BaaiType Embeddings512 contextPrice $0.01 / 1M tokens
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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...
Related embeddings models
BAAI: bge-base-en-v1.5$0.01 / 1M tokensBAAI: bge-m3$0.01 / 1M tokensGoogle: Gemini Embedding 001$0.15 / 1M tokensGoogle: Gemini Embedding 2$0.20 / 1M tokensGoogle: Gemini Embedding 2 Preview$0.20 / 1M tokensIntfloat: E5-Base-v2$0.01 / 1M tokens
FAQ
What is 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...
What is the context window of BAAI: bge-large-en-v1.5?
BAAI: bge-large-en-v1.5 supports a 512-token context window.
How much does BAAI: bge-large-en-v1.5 cost?
BAAI: bge-large-en-v1.5 is priced at $0.01 / 1M tokens via OpenRouter.
What are alternatives to BAAI: bge-large-en-v1.5?
Comparable embeddings models include BAAI: bge-base-en-v1.5, BAAI: bge-m3, Google: Gemini Embedding 001, Google: Gemini Embedding 2.
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