NVIDIA
NVIDIA
NVIDIA Retrieval QA Llama 3.2 300m Embedding v1
Container
NVIDIA
NVIDIA
NVIDIA Retrieval QA Llama 3.2 300m Embedding v1

The NVIDIA Retrieval QA Llama3.2 300m Embedding NIM is an embedding NIM optimized for multilingual and crosslingual text question-answering retrieval.

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Text Embedding NIM

NeMo Retriever Text Embedding NIM (Text Embedding NIM) brings the power of state-of-the-art text embedding models to your applications, offering unparalleled natural language processing and understanding capabilities. You can use Text Retriever NIM for semantic search, Retrieval Augmented Generation (RAG) pipelines, or any application that uses text embeddings. Text Embedding NIM is built on the NVIDIA software platform, incorporating CUDA, TensorRT, and Triton to offer out-of-the-box GPU acceleration.

Getting started with the NIM

Deploying and integrating the NIM is straightforward thanks to our industry standard APIs. Visit the NIM Container page for release documentation, deployment guides and more.

Security Vulnerabilities in Open Source Packages

Please review the Security Scanning tab on NGC to view the latest security scan results.

For certain open-source vulnerabilities listed in the scan results, NVIDIA provides a response in the form of a Vulnerability Exploitability eXchange (VEX) document. The VEX information can be reviewed and downloaded from the Security Scanning tab.

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Governing Terms

The NIM container is governed by NVIDIA Agreements | Enterprise Software | NVIDIA Software License Agreement and NVIDIA Agreements | Enterprise Software | Product Specific Terms for AI Product; and the use of this model is governed by the ai-foundation-models-community-license.pdf.

Additional information: Llama 3.2 community license.

You are responsible for ensuring that your use of NVIDIA AI Foundation Models complies with all applicable laws.

Publisher
NVIDIA
NVIDIA
Latest Tag1
UpdatedJuly 17, 2025 UTC
Compressed Size3.29 GB
Multinode SupportNo
Multi-Arch SupportYes