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  • Retrieval Augmented Generation
  • NVIDIA
    Deprecation in 9dDownloadable

    llama-3.2-nemoretriever-1b-vlm-embed-v1

    Multimodal question-answer retrieval representing user queries as text and documents as images.
    Model
    nemo retriever
    200K
    9mo
    NVIDIA
    Downloadable

    llama-3.2-nemoretriever-500m-rerank-v2

    GPU-accelerated model optimized for providing a probability score that a given passage contains the information to answer a question.
    Model
    nemo retriever
    6.87K
    9mo
    NVIDIA
    Free Endpoint

    llama-3_2-nemoretriever-300m-embed-v1

    Multilingual, cross-lingual embedding model for long-document QA retrieval, supporting 26 languages.
    Model
    Text-to-Embedding
    272K
    8mo
    NVIDIA
    Downloadable

    llama-3_2-nemoretriever-300m-embed-v2

    Multilingual, cross-lingual embedding model for long-document QA retrieval, supporting 26 languages.
    Model
    Text-to-Embedding
    146
    6mo
    NVIDIA
    Downloadable

    llama-nemotron-embed-1b-v2

    Multilingual, cross-lingual embedding model for long-document QA retrieval, supporting 26 languages.
    Model
    Text-to-Embedding
    1.37M
    1mo
    NVIDIA
    Downloadable

    llama-nemotron-rerank-1b-v2

    GPU-accelerated model optimized for providing a probability score that a given passage contains the information to answer a question.
    Model
    nemo retriever
    111K
    1mo
    NVIDIA
    Downloadable

    llama-nemotron-embed-vl-1b-v2

    Multimodal question-answer retrieval representing user queries as text and documents as images.
    Model
    nemo retriever
    8.28M
    2mo
    NVIDIA
    Downloadable

    llama-nemotron-rerank-vl-1b-v2

    GPU-accelerated model optimized for providing a probability score that a given passage contains the information to answer a question.
    Model
    nemo retriever
    659
    2w
    NVIDIA
    Downloadable

    llama-3.2-nv-embedqa-1b-v2

    Multilingual and cross-lingual text question-answering retrieval with long context support and optimized data storage efficiency.
    Model
    nemo retriever
    2.4M
    8mo
    NVIDIA
    Downloadable

    llama-3.2-nv-rerankqa-1b-v2

    Fine-tuned reranking model for multilingual, cross-lingual text question-answering retrieval, with long context support.
    Model
    nemo retriever
    175K
    8mo
    NVIDIA
    Free Endpoint

    nv-embedcode-7b-v1

    The NV-EmbedCode model is a 7B Mistral-based embedding model optimized for code retrieval, supporting text, code, and hybrid queries.
    Model
    nemo retriever
    201K
    10mo
    Cyborg
    Launchable

    Cyborg Enterprise RAG

    Securely extract, embed, and index multimodal data with encryption in-use for fast, accurate semantic search.
    Blueprint
    NIM
    1mo
    NVIDIA
    Launchable

    Multi-Agent Intelligent Warehouse

    An AI-powered, multi-agent system designed to optimize warehouse operations through intelligent automation, real-time monitoring, and natural language interaction.
    Blueprint
    NVIDIA AI
    1mo
    NVIDIA
    Downloadable

    nv-embedqa-e5-v5

    English text embedding model for question-answering retrieval.
    Model
    Embedding
    12.37M
    8mo
    NVIDIA
    Launchable

    Retail Shopping Assistant

    Elevate Shopping Experiences Online and In Stores.
    Blueprint
    NVIDIA AI
    1mo
    NVIDIA
    LaunchableEnterprise

    Build an Enterprise RAG Pipeline Blueprint

    Power fast, accurate semantic search across multimodal enterprise data with NVIDIA’s RAG Blueprint—built on NeMo Retriever and Nemotron models—to connect your agents to trusted, authoritative sources of knowledge.
    Blueprint
    NVIDIA AI
    1mo
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