NVIDIA NeMo Retriever vs. Nomic Embed Comparison


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About NVIDIA NeMo Retriever is a collection of microservices for building multimodal extraction, reranking, and embedding pipelines with high accuracy and maximum data privacy. It delivers quick, context-aware responses for AI applications like advanced retrieval-augmented generation (RAG) and agentic AI workflows. As part of the NVIDIA NeMo platform and built with NVIDIA NIM, NeMo Retriever allows developers to flexibly leverage these microservices to connect AI applications to large enterprise datasets wherever they reside and fine-tune them to align with specific use cases. NeMo Retriever provides components for building data extraction and information retrieval pipelines. The pipeline extracts structured and unstructured data (e.g., text, charts, tables), converts it to text, and filters out duplicates. A NeMo Retriever embedding NIM converts the chunks into embeddings and stores them in a vector database, accelerated by NVIDIA cuVS, for enhanced performance and speed of indexing.	About Nomic Embed is a suite of open source, high-performance embedding models designed for various applications, including multilingual text, multimodal content, and code. The ecosystem includes models like Nomic Embed Text v2, which utilizes a Mixture-of-Experts (MoE) architecture to support over 100 languages with efficient inference using 305M active parameters. Nomic Embed Text v1.5 offers variable embedding dimensions (64 to 768) through Matryoshka Representation Learning, enabling developers to balance performance and storage needs. For multimodal applications, Nomic Embed Vision v1.5 aligns with the text models to provide a unified latent space for text and image data, facilitating seamless multimodal search. Additionally, Nomic Embed Code delivers state-of-the-art performance on code embedding tasks across multiple programming languages.
Platforms Supported Windows Mac Linux Cloud On-Premises iPhone iPad Android Chromebook	Platforms Supported Windows Mac Linux Cloud On-Premises iPhone iPad Android Chromebook
Audience Enterprise developers and data scientists searching for a tool to build scalable, high-accuracy AI applications	Audience Machine learning engineers and developers seeking a solution offering embedding models for multilingual text, multimodal content, and code applications
Support Phone Support 24/7 Live Support Online	Support Phone Support 24/7 Live Support Online
API Offers API	API Offers API
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing No information available. Free Version Free Trial	Pricing Free Free Version Free Trial
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software
Training Documentation Webinars Live Online In Person	Training Documentation Webinars Live Online In Person
Company Information NVIDIA Founded: 1993 United States developer.nvidia.com/nemo-retriever	Company Information Nomic United States www.nomic.ai/embed
Alternatives AI-Q NVIDIA Blueprint NVIDIA	Alternatives BGE
NVIDIA NeMo Guardrails NVIDIA	Mixedbread
BGE	Cohere Embed Cohere
NVIDIA NeMo NVIDIA	NVIDIA NeMo Retriever NVIDIA
Mixedbread View All	Gemini Embedding Google View All
Categories Embedding Models Reranking Models	Categories Embedding Models Reranking Models

Integrations Baseten Go Java JavaScript NVIDIA NIM NVIDIA NeMo PHP Python Ruby View All 2 Integrations	Integrations Baseten Go Java JavaScript NVIDIA NIM NVIDIA NeMo PHP Python Ruby View All 7 Integrations
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