---
id: "sentence-transformers/multi-qa-mpnet-base-dot-v1"
also: ["sentence-transformers/multi-qa-mpnet-base-dot-v1-20251117", "sentence-transformers/multi-qa-mpnet-base-dot-v1"]
cheapest_list_usd_per_m: "0.005 in, 0.0 out, at deepinfra on openrouter"
context: 512
max_output: 460
input: ["text"]
output: ["embeddings"]
released: "2025-11-18"
api: ["/api/v1/embeddings"]
endpoints: 2
gateways: "openrouter (2)"
no_training: 1
trains: 0
retains_prompts: 0
---
# 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.