Try NVIDIA NIM APIs

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

Multimodal question-answer retrieval representing user queries as text and documents as images.

269K

8mo

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.

1.27K

8mo

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

Multilingual, cross-lingual embedding model for long-document QA retrieval, supporting 26 languages.

Retrieval Augmented Generation

86.67K

7mo

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

Multilingual, cross-lingual embedding model for long-document QA retrieval, supporting 26 languages.

Retrieval Augmented Generation

129K

5mo

llama-nemotron-embed-1b-v2

Multilingual, cross-lingual embedding model for long-document QA retrieval, supporting 26 languages.

Retrieval Augmented Generation

282K

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

Multimodal question-answer retrieval representing user queries as text and documents as images.

769K

1mo

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.

1.09K

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

Multilingual and cross-lingual text question-answering retrieval with long context support and optimized data storage efficiency.

6.82M

7mo

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

Fine-tuned reranking model for multilingual, cross-lingual text question-answering retrieval, with long context support.

165K

7mo

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.

255K

9mo

Cyborg

Launchable

Cyborg Enterprise RAG

Securely extract, embed, and index multimodal data with encryption in-use for fast, accurate semantic search.

NIM

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.

nv-embedqa-e5-v5

English text embedding model for question-answering retrieval.

Embedding

3.21M

7mo

Launchable

Retail Shopping Assistant

Elevate Shopping Experiences Online and In Stores.

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.

NIM

LaunchableEnterprise

Build an AI Agent for Enterprise Research

Build a custom enterprise research assistant powered by state-of-the-art models that process and synthesize multimodal data, enabling reasoning, planning, and refinement to generate comprehensive reports.