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