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NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI—the next era of computing—with the GPU acting as the brain of computers, robots and self-driving cars that can perceive and understand the world.


  • vGPU Software
    • Quadro Virtual Data Center Workstation (Quadro vDWS) delivers the most powerful virtual workstation from the data center or cloud to any device, anywhere.
    • NVIDIA GRID™ Virtual PC (vPC) and Virtual Apps (vApps) are the virtualization solutions that deliver a user experience that’s nearly indistinguishable from a native PC. With server-side graphics and comprehensive management and monitoring capabilities, GRID future-proofs your VDI environment.
  • NVIDIA DGX Systems
    • DGX Station is the only personal supercomputer for leading-edge AI development. Designed for your office environment, it’s built on the same software stack powering all DGX systems, for easy experimentation, from your desk to the data center.
    • DGX-1 The essential instrument for AI research, designed to accelerate your data center and streamline your deep learning workflow. Experiment faster, train larger models, and get insights starting on day one.
    • DGX-2 Break through the barriers to AI speed and scale with NVIDIA DGX-2, the first 2 petaFLOPS system that engages 16 fully interconnected GPUs for 10X the deep learning performance.
  • NVIDIA Tesla GPUs

    Accelerate your most demanding HPC and hyperscale data center workloads with NVIDIA® Tesla® GPUs. Data scientists and researchers can now parse petabytes of data orders of magnitude faster than they could using traditional CPUs, in applications ranging from energy exploration to deep learning.


GSA Schedule Contracts

GSA Schedule 70

GSA Schedule 70 GSA Schedule No. GS-35F-0119Y Term: December 20, 2011- December 19, 2021

SEWP Contracts


Contract Number: Group A Small: NNG15SC03B Group D Other Than Small: NNG15SC27B Term: May 1, 2015 - April 30, 2020

State & Local Contracts

City of Seattle Contract

Contract #0000003265 Term: December 19, 2021


Contract # CMAS 3-12-70-2247E Term: through March 31, 2022

State of New Mexico Contract

Contract Number: 80-000-18-00002 Contract Period: August 1, 2017 – August 1, 2021



Latest News

Carahsoft Technology Corp., The Trusted Government IT Solutions Provider™, today announced that it plans to make NVIDIA® programmable graphics processing units (GPUs) and related technologies ...



Artificial intelligence (AI) promises to impact the world’s geopolitical hierarchy like no other technology in history. With the most powerful countries in a race to establish AI dominance, Rep. Will Hurd (R-Texas), chairman of the House Subcommittee on Information Technology, presided over a seri...


Power the most compute-intensive workloads with virtual GPUs.


The Top Four Reasons Windows 10 VDI Needs GPUs


The NVIDIA Deep Learning Institute (DLI) trains developers, data scientists, and researchers on how to use artificial intelligence and accelerated computing to solve real-world problems across a wide range of domains. In deep learning courses, you’ll learn how to train, optimize, and deploy neural...


This infographic outlines how NVIDIA DGX Systems are essential instruments for AI research built on the new NVIDIA Volta GPU Platform.


This presentation outlines how accelerated computing has revolutionized a broad range of industries with over five hundred applications optimized for GPUs to help accelerate everyday work.

Solutions Brief

Across the enterprise, there’s a growing need for graphics and compute acceleration with fast, secure access from anywhere, on any device. Engineers, designers, and architects are using powerful applications that rely on graphics-intensive datasets and need to be accessed by distributed teams fr...

The presence of extraordinary amounts of data, to train on, to learn from, and to explore, represents a golden age of computing. But beneath this incredible opportunity lies a massive challenge. Traditional CPU compute cannot keep pace with the growth in data, and as a result, even the most soph...