by BAAI
BAAI/bge-large-en-v1.5 is a large English text embedding model and part of the BGE (BAAI General Embedding) series. It achieves excellent performance on the MTEB benchmark, with an average score of 64.23 across 56 datasets, excelling in tasks such as retrieval, clustering, and text pair classification. The model supports a maximum input length of 512 tokens and is suitable for various natural language processing tasks, such as text retrieval and semantic similarity computation.
BAAI/bge-large-en-v1.5 is a large English text embedding model and part of the BGE (BAAI General Embedding) series. It achieves excellent performance on the MTEB benchmark, with an average score of 64.23 across 56 datasets, excelling in tasks such as retrieval, clustering, and text pair classification. The model supports a maximum input length of 512 tokens and is suitable for various natural language processing tasks, such as text retrieval and semantic similarity computation.
On AIHubMix, BAAI/bge-large-en-v1.5 costs $0.03 per million input tokens and $0.03 per million output tokens.
BAAI/bge-large-en-v1.5 accepts text and image input.
BAAI/bge-large-en-v1.5 supports tool calling, function calling and structured outputs. Per-protocol parameter support is listed in the capability table on this page.
BAAI/bge-large-en-v1.5 is available through the AIHubMix unified API. The API is OpenAI-compatible: point your OpenAI SDK at https://aihubmix.com/v1, use your AIHubMix API key, and set the model name to BAAI/bge-large-en-v1.5 — no other code changes needed.
BAAI/bge-large-en-v1.5 is developed by BAAI. AIHubMix aggregates it alongside models from other providers behind one API and one bill.
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Use BAAI/bge-large-en-v1.5 via the AIHubMix unified API — one interface for every major LLM.