Models Model details

Intfloat

Intfloat: E5-Base-v2

intfloat/e5-base-v2

The e5-base-v2 embedding model encodes English sentences and paragraphs into a 768-dimensional dense vector space, producing efficient and high-quality semantic embeddings optimized for tasks such as semantic search, similarity scoring, retrieval and clustering.

Input
$0.005

/ 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

109,482,752

Model facts

Author

Intfloat

Tokenizer

Other

Modality

Text -> Embeddings

License

MIT

Created

Nov 18, 2025

Hugging Face

intfloat/e5-base-v2

Publication status

Hugging Face: verifiedLicense: publishedParameter count: published

Modalities

Input · TextOutput · Embeddings