Microsoft Has Purchased Nearly 500k Nvidia Hopper GPUs For AI Acceleration In 2024

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Spending Over $30 billion On AI GPUs From Nvidia Alone!

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Microsoft will end the year as the company that purchased the most NVIDIA Hopper GPUs in 2024. Thanks to the latest data from the Financial Times, we know that Microsoft acquired nearly half a million graphics cards from NVIDIA in 2024 alone. Of course, 100% of these graphics cards will be used exclusively to accelerate artificial intelligence.

Now, don’t think that their coronation is far behind. Companies like ByteDance (TikTok) and other Chinese giants like Tencent and Meta have bought nearly a quarter of a million graphics cards.

When discussing NVIDIA Hopper graphics cards, we refer to the NVIDIA H100, H800, H20, and H200 graphics chips. These companies buy any available GPUs to expand and create new data centres related to AI learning and acceleration. They can’t sit back and wait for a specific model to become available, even more so with this fierce competition already racing for AI.

Microsoft alone spent over $30 billion on AI GPUs, almost double the amount that NVIDIA’s second-largest buyer, ByteDance, spent. The company bought around 230,000 graphics cards.

It’s not bad, despite the sanctions imposed on Chinese companies. The main purchases are the NVIDIA H800, a special version that can be sold in China. There is talk of the sanctioned NVIDIA H100 obtained through third parties.

It is also striking to see Tesla / xAI with about 200,000 GPUs purchased. For context, it is officially known that they have accumulated more than 1 million graphics cards for their AI projects.

Outside of this Top 5, we have other American companies such as Amazon, which bought less than 200,000 graphics cards, and Google, which bought around 160,000 units.

AI, AI and More AI

Nuclear Reactor
Nuclear Reactor

We’re seeing the world’s top tech companies invest much of their capital into AI alone. According to Vlad Galabov, director of cloud and data centre research at Omdia, NVIDIA GPUs account for almost all of these companies’ capital expenditures for the server business, including Meta, Tesla/xAI, Amazon, and Google

That’s why companies like Amazon, Google, and Meta are working on custom AI training and inference solutions. Google has its TPU, Amazon has its Trainium and Inferentia chips, and Meta has its MTIA.

The hyperscalers are eager to develop their in-house solutions, but NVIDIA’s control over the software stack and timely product updates seem difficult to break. Of course, we are just around the corner from its new NVIDIA Blackwell GPUs, which promise a huge leap in performance. And yes, as it could not be otherwise, all these companies have already “fought” to see who gets a greater allocation of them during the first months of their launch.

It should be remembered that even Meta is looking for a nuclear partner. Microsoft announced its plans to restart a nuclear reactor to power these NVIDIA GPUs, which would allow it to have the energy to train its AI for 20 years. And in the AI race, there is another race, which is to have access to all the energy necessary for this rapid expansion.

What’s your take on this new AI race among trillion-dollar-worth companies? Share your thoughts in the comment section below. 

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