Oracle Buys Tens of Thousands of Nvidia A100, H100 GPUs

Nvidia Hopper H100 GPU and DGX systems
(Image credit: Nvidia)

Oracle on Tuesday announced plans to deploy tens of thousands of Nvidia's top-of-the-range A100 and H100 compute GPUs to its Oracle Cloud Infrastructure (OCI). The A100 and H100 GPUs will be available for Oracle's cloud customers for their AI workloads enabled by Nvidia's AI software. The deal's exact terms remain behind closed doors, but we are talking about a transaction worth hundreds of millions of dollars.

The new collaboration between Nvidia and Oracle will make AI training, computer vision, data processing, deep learning inference, and simulation available to all enterprise customers. They will not have to invest hefty sums into deploying their data centers with Nvidia's expensive compute GPUs. Oracle already offers OCI clients access to high-performance computing instances and will now provide them with various AI capabilities.

Enterprise clients of Oracle's OCI will be able to access all of Nvidia's AI platforms, including the following:

  • AI Enterprise — a set of engines that can be used for AI model training, compute vision, conversational AI, data processing, recommender systems, and simulation, among others.
  • RAPIDS — acceleration for Apache Spark data processing on the OCI Data Flow fully-managed Apache Spark service, including bare metal instances like BM.GPU.GM4.8 with A100 Tensor Core GPUs.
  • Clara — medical imaging, genomics, natural language processing, and drug discovery (coming soon).

Nvidia's A100 and H100 compute GPUs are pretty expensive. Even previous-generation A100 compute GPUs cost $10,000 to $15,000 depending on the exact configuration, and the next-generation H100 products promise to be even more costly. So while Oracle is unlikely to buy Nvidia's compute GPUs for retail prices, it still pays a premium for Nvidia's hardware and software.

Keeping in mind that we are talking about tens of thousands of computing GPUs along with Nvidia's NVLink switches and possibly data processing units, we would expect the deal between Nvidia and Oracle to be worth hundreds of millions of dollars, which is quite an unprecedented contract. In any case, working with Oracle is vital for Nvidia as shortly it will not be able to sell compute CPUs to customers in China.

"Our expanded alliance with Nvidia will deliver the best of both companies' expertise to help customers across industries — from healthcare and manufacturing to telecommunications and financial services — overcome the multitude of challenges they face," said Safra Catz, CEO of Oracle.

Anton Shilov
Contributing Writer

Anton Shilov is a contributing writer at Tom’s Hardware. Over the past couple of decades, he has covered everything from CPUs and GPUs to supercomputers and from modern process technologies and latest fab tools to high-tech industry trends.

  • gg83
    Nvidia has a crap ton of extra silicon right? so I wonder if this deal never would have happened, and I bet oracle got a sweet price.
    Reply
  • Co BIY
    gg83 said:
    Nvidia has a crap ton of extra silicon right? so I wonder if this deal never would have happened, and I bet oracle got a sweet price.

    I don't think there are a ton of A100 and H100 chips laying around. There is a good chance this deal has been in development since before these wafers were purchased.
    Reply
  • renz496
    gg83 said:
    Nvidia has a crap ton of extra silicon right? so I wonder if this deal never would have happened, and I bet oracle got a sweet price.

    maybe. maybe not. a few weeks ago we also heard many of nvidia client in china are trying to secure nvidia A100 as many as possible before the restriction to sell AI related chip to china taking effect sometime in 2023. back then it is reported that nvidia and TSMC are working together to increase A100 chip production for this matter.

    plus stuff like this you don't see cheap price and suddenly the company interested to buy those hardware. nvidia most often dominating the sales of professional hardware even if their solution is tons more expensive than competitor because of their software ecosystem that cover lots of things that most often their competitor are not.
    Reply