NVIDIA Ships World’s Most Advanced AI System — NVIDIA DGX A100 — to Fight COVID-19; Third-Generation DGX Packs Record 5 Petaflops of AI Performance

NVIDIA DGX A100 systems start at $199,000 and are shipping now through NVIDIA Partner Network resellers worldwide. Storage technology providers DDN Storage, Dell Technologies, IBM, NetApp, Pure Storage and Vast plan to integrate DGX A100 into their offerings, including those based on the NVIDIA DGX POD and DGX SuperPOD reference architectures.

NVIDIA DGX-Ready Data Center partners offer colocation services in more than 122 locations across 26 countries to help customers seeking cost-effective facilities to host their DGX infrastructure. Customers can take advantage of these services to house and access DGX A100 infrastructure inside validated, world-class data center facilities.

Further information, including detailed technical specifications and ordering details, is available at www.nvidia.com/DGX-A100.

About NVIDIA
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. More information at http://nvidianews.nvidia.com/.

Media Contact:
Shannon McPhee
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Certain statements in this press release including, but not limited to, statements as to: the benefits, performance, features and availability of our products, technologies and services, including NVIDIA DGX A100, NVIDIA A100 Tensor Core GPUs, DGX SuperPOD, NVIDIA Mellanox InfiniBand interconnects, DGX SuperPOD reference architecture, NVIDIA DGXpert program, NVIDIA DGX-Ready Software program, NVSwitch interconnect fabrics, NVLink technology, Mellanox’s In-Network Computing and network acceleration engines, NVIDIA DGX software stack, and NVIDIA DGX-Ready Data Center partners are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners' products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company's website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.

© 2020 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, DGX, NVIDIA DGX A100, NVIDIA DGX SuperPOD, NVLink and NVSwitch are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/4a14145b-a64e-4cbf-8652-369053370558

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NVIDIA DGX A100

The world’s most advanced AI system, NVIDIA DGX A100 packs a record 5 petaflops of performance in a single node.


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