GTC: Nvidia Launches AI Data Platform and Reasoning Models
Nvidia has unveiled its AI Data Platform, a reference design for storage providers to build infrastructure that supports AI reasoning workloads, alongside a new family of open reasoning AI models, at the company’s GTC conference in San Jose.
The AI Data Platform enables Nvidia-Certified Storage providers to develop systems with specialised AI query agents. These agents aim to generate insights from corporate data in near real time, leveraging Nvidia AI Enterprise software including NIM microservices for the new Nvidia Llama Nemotron models.
“Data is the raw material powering industries in the age of AI,” says Jensen Huang, Founder and CEO of Nvidia. “With the world’s storage leaders, we’re building a new class of enterprise infrastructure that companies need to deploy and scale agentic AI across hybrid data centres.”
Nvidia introduces Llama Nemotron models for business reasoning
The company also announced the open Llama Nemotron family of models with reasoning capabilities, designed to provide developers and enterprises a foundation for creating advanced AI agents that can work independently or as connected teams.
Built on Meta’s Llama models, the Nvidia Llama Nemotron reasoning family delivers on-demand AI reasoning capabilities. Nvidia enhanced the models during post-training to improve multistep math, coding, reasoning and complex decision-making.
This refinement process boosts accuracy by up to 20% compared with the base model and optimises inference speed by five times compared with other leading open reasoning models. The improvements mean the models can handle more complex reasoning tasks while reducing operational costs.
Several leading companies are collaborating with Nvidia on its new reasoning models, including Accenture, Amdocs, Atlassian, Box, Cadence, CrowdStrike, Deloitte, IQVIA, Microsoft, SAP and ServiceNow.
Nvidia hardware and software combine for enterprise AI solutions
The AI Data Platform incorporates the company’s latest Blackwell GPUs, BlueField DPUs and Spectrum-X networking to accelerate AI query agent access to enterprise data storage systems. According to Nvidia, BlueField DPUs deliver 1.6 times higher performance than CPU-based storage while reducing power consumption by 50%.
Spectrum-X networking accelerates AI storage traffic by 48% compared with traditional Ethernet through adaptive routing and congestion control techniques.
The infrastructure utilises the Nvidia AI-Q Blueprint for developing systems that can reason and connect to enterprise data. This blueprint incorporates NeMo Retriever microservices to speed up data extraction and retrieval processes on Nvidia GPUs.
The Llama Nemotron model family is available as Nvidia NIM microservices in Nano, Super and Ultra sizes, each optimised for different deployment needs. The Nano model delivers accuracy on PCs and edge devices, the Super model offers accuracy and throughput on a single GPU, and the Ultra model provides agentic accuracy on multi-GPU servers.
Nvidia conducted extensive post-training on Nvidia DGX Cloud using curated synthetic data generated by Nvidia Nemotron and other open models. The tools, datasets and post-training optimisation techniques will be openly available, giving enterprises flexibility to build custom reasoning models.
Industry partners implement Nvidia AI capabilities
Several storage providers are working with Nvidia to build custom AI data platforms. DDN is incorporating the capabilities into its Infinia AI platform, while Dell is creating AI data platforms for its PowerScale and Project Lightning solutions.
Hewlett Packard Enterprise is integrating the platform into HPE Private Cloud for AI, HPE Data Fabric, HPE Alletra Storage MP and HPE GreenLake for File Storage.
Microsoft is integrating Llama Nemotron reasoning models and NIM microservices into Microsoft Azure AI Foundry, expanding the Azure AI Foundry model catalog with options for customers to enhance services like Azure AI Agent Service for Microsoft 365.
SAP is using Llama Nemotron models to advance SAP Business AI solutions and Joule, the AI copilot from SAP.
“We are collaborating with Nvidia to integrate Llama Nemotron reasoning models into Joule to enhance our AI agents, making them more intuitive, accurate and cost effective,” says Walter Sun, Global Head of AI at SAP. “These advanced reasoning models will refine and rewrite user queries, enabling our AI to better understand inquiries and deliver smarter, more efficient AI-powered experiences that drive business innovation.”
ServiceNow is harnessing Llama Nemotron models to build AI agents that offer performance and accuracy to enhance enterprise productivity across industries.
Accenture has made Nvidia Llama Nemotron reasoning models available on its AI Refinery platform to enable clients to develop and deploy custom AI agents tailored to industry-specific challenges.
Deloitte is planning to incorporate Llama Nemotron reasoning models into its recently announced Zora AI agentic AI platform designed to support and emulate human decision-making with agents that include functional and industry-specific business knowledge.
“Reasoning and agentic AI adoption is incredible,” says Huang. “Nvidia’s open reasoning models, software and tools give developers and enterprises everywhere the building blocks to create an accelerated agentic AI workforce.”
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