Models Model details

Sentence Transformers

Sentence Transformers: all-mpnet-base-v2

sentence-transformers/all-mpnet-base-v2

The all-mpnet-base-v2 embedding model encodes sentences and short paragraphs into a 768-dimensional dense vector space, providing high-fidelity semantic embeddings well suited for tasks like information retrieval, clustering, similarity scoring, and text ranking.

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

109,486,978

Model facts

Author

Sentence Transformers

Tokenizer

Other

Modality

Text -> Embeddings

License

Apache-2.0

Created

Nov 17, 2025

Hugging Face

sentence-transformers/all-mpnet-base-v2

Publication status

Hugging Face: verifiedLicense: publishedParameter count: published

Modalities

Input · TextOutput · Embeddings