Intfloat
Intfloat: E5-Large-v2
intfloat/e5-large-v2
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.
Input
$0.01
/ 1M tokens · Token reference
Output
$0
/ 1M tokens · Token reference
Context window
512
tokens
Embeddings output · Token reference fields do not establish an output-unit price.
Limits
Context
512
tokens
Max output
460
90% of the context window
Parameters
335,142,400
Model facts
Author
Intfloat
Tokenizer
Other
Modality
Text -> Embeddings
License
MIT
Created
Nov 18, 2025
Hugging Face
intfloat/e5-large-v2
Publication status
Hugging Face: verifiedLicense: publishedParameter count: published
Modalities
Input · TextOutput · Embeddings