Skip to content
  12.  
    13. © 2023 – 2025 OpenRouter, Inc

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

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

    Created Nov 18, 2025512 context
    $0.005/M input tokens$0/M output tokens

    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.

    Sample code and API for multi-qa-mpnet-base-dot-v1

    OpenRouter normalizes requests and responses across providers for you.

    OpenRouter provides an OpenAI-compatible embeddings API that you can call directly, or using the OpenAI SDK.

    In the examples below, the OpenRouter-specific headers are optional. Setting them allows your app to appear on the OpenRouter leaderboards.

    Using third-party SDKs

    For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.

    See the Request docs for all possible fields, and Parameters for explanations of specific sampling parameters.