Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Gemini Enterprise Agent Platform Reviews & Ratings
    1,161 Ratings
    Company Website
  • LM-Kit.NET Reviews & Ratings
    29 Ratings
    Company Website
  • LTX Reviews & Ratings
    182 Ratings
    Company Website
  • Runpod Reviews & Ratings
    230 Ratings
    Company Website
  • Bright Data Reviews & Ratings
    1,430 Ratings
    Company Website
  • IONOS Cloud GPU Servers Reviews & Ratings
    45,340 Ratings
    Company Website
  • LogicalDOC Reviews & Ratings
    150 Ratings
    Company Website
  • SearchUnify Reviews & Ratings
    150 Ratings
    Company Website
  • Intellimas Reviews & Ratings
    30 Ratings
    Company Website
  • Adaptive Security Reviews & Ratings
    152 Ratings
    Company Website

What is NVIDIA NeMo Retriever?

NVIDIA NeMo Retriever comprises a collection of microservices tailored for the development of high-precision multimodal extraction, reranking, and embedding workflows, all while prioritizing data privacy. It facilitates quick and context-aware responses for various AI applications, including advanced retrieval-augmented generation (RAG) and agentic AI functions. Within the NVIDIA NeMo ecosystem and leveraging NVIDIA NIM, NeMo Retriever equips developers with the ability to effortlessly integrate these microservices, linking AI applications to vast enterprise datasets, no matter their storage location, and providing options for specific customizations to suit distinct requirements. This comprehensive toolkit offers vital elements for building data extraction and information retrieval pipelines, proficiently gathering both structured and unstructured data—ranging from text to charts and tables—transforming them into text formats, and efficiently eliminating duplicates. Additionally, the embedding NIM within NeMo Retriever processes these data segments into embeddings, storing them in a highly efficient vector database, which is optimized by NVIDIA cuVS, thus ensuring superior performance and indexing capabilities. As a result, the overall user experience and operational efficiency are significantly enhanced, enabling organizations to fully leverage their data assets while upholding a strong commitment to privacy and accuracy in their processes. By employing this innovative solution, businesses can navigate the complexities of data management with greater ease and effectiveness.

What is Mistral NeMo?

We are excited to unveil Mistral NeMo, our latest and most sophisticated small model, boasting an impressive 12 billion parameters and a vast context length of 128,000 tokens, all available under the Apache 2.0 license. In collaboration with NVIDIA, Mistral NeMo stands out in its category for its exceptional reasoning capabilities, extensive world knowledge, and coding skills. Its architecture adheres to established industry standards, ensuring it is user-friendly and serves as a smooth transition for those currently using Mistral 7B. To encourage adoption by researchers and businesses alike, we are providing both pre-trained base models and instruction-tuned checkpoints, all under the Apache license. A remarkable feature of Mistral NeMo is its quantization awareness, which enables FP8 inference while maintaining high performance levels. Additionally, the model is well-suited for a range of global applications, showcasing its ability in function calling and offering a significant context window. When benchmarked against Mistral 7B, Mistral NeMo demonstrates a marked improvement in comprehending and executing intricate instructions, highlighting its advanced reasoning abilities and capacity to handle complex multi-turn dialogues. Furthermore, its design not only enhances its performance but also positions it as a formidable option for multi-lingual tasks, ensuring it meets the diverse needs of various use cases while paving the way for future innovations.

Media

Media

Integrations Supported

NVIDIA NIM
NVIDIA NeMo

Integrations Supported

C
EvalsOne
Fleak
HTML
HoneyHive
Humiris AI
Julia
Kiin
Klee
Literal AI
Mammouth AI
Microsoft Foundry Models
Mistral AI
Nebius Token Factory
PromptPal
ReByte
Toolmark

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Free
Open source
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

developer.nvidia.com/nemo-retriever

Company Facts

Organization Name

Mistral AI

Date Founded

2023

Company Location

France

Company Website

mistral.ai/news/mistral-nemo/

Categories and Features

Embedding Models

Not specified

Reranking Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Small Language Models

Not specified

Popular Alternatives

Popular Alternatives

Jamba Reviews & Ratings

Jamba

AI21 Labs
Mistral Small Reviews & Ratings

Mistral Small

Mistral AI
Olmo 2 Reviews & Ratings

Olmo 2

Ai2
NVIDIA NeMo Reviews & Ratings

NVIDIA NeMo

NVIDIA
Mistral 7B Reviews & Ratings

Mistral 7B

Mistral AI