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Intfloat: E5-Large-v2

intfloat/e5-large-v2

Created Nov 18, 2025512 context
$0.01/M input tokens$0/M output tokens

The e5-large-v2 embedding model maps English sentences, paragraphs, and documents into a 1024-dimensional dense vector space, delivering high-accuracy semantic embeddings optimized for retrieval, semantic search, reranking, and similarity-scoring tasks.

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Recent activity on E5-Large-v2

Total usage per day on OpenRouter

Prompt
42K
Completion
0
Reasoning
0

Prompt tokens measure input size. Reasoning tokens show internal thinking before a response. Completion tokens reflect total output length.