Models Model details

Sentence Transformers

Sentence Transformers: multi-qa-mpnet-base-dot-v1

sentence-transformers/multi-qa-mpnet-base-dot-v1

The multi-qa-mpnet-base-dot-v1 embedding model transforms sentences and short paragraphs into a 768-dimensional dense vector space, generating high-quality semantic embeddings optimized for question-and-answer retrieval, semantic search, and similarity-scoring across diverse content.

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

Created

Nov 18, 2025

Hugging Face

sentence-transformers/multi-qa-mpnet-base-dot-v1

Publication status

Hugging Face: verifiedLicense: not publishedParameter count: published

Modalities

Input · TextOutput · Embeddings