Nvidia wins a huge order worth US$500 million! Yin data center bought 16,000 H100/GH200 in one go

Nvidia is going to make a big deal?

The first sale is 16,000 GPUs, worth 500 million, in US dollars.

The company that placed the big order is Yotta from India, which is a data center and server company.

It is said that by 2025, Yotta will have a total of 32,000 NVIDIA H100 and GH200 GPUs.

Who is Yotta?

The word Yotta originally means the largest decimal unit prefix in the metric system, the size is 10 to the 24th power, and the Chinese translation is "Yao".

As a data center hosting service provider, Yotta is committed to building a super-scalable, high-density data center ecosystem to meet the growing data demand.

Currently, Yotta has two larger data centers in India, Yotta D1, NCR-Delhi and Yotta NM1, Navi Mumbai.

Yotta D1, NCR-Delhi is part of a pan-India network of interconnected colocation facilities.

The data center has a rack capacity of 5,000, IT Power of 28.8 MW, and energy efficiency of 1.4.

Yotta NM1, Navi Mumbai Data Center is a pioneer in the history of hyperscale data center development in India. Located on the campus of Mumbai Data Center, the company provides the highest quality hosting services.

Rack capacity 7200, IT Power 50 MW, energy usage efficiency 1.4.

sky-high price order

According to Reuters, the purchase period for this large order is 2025 In March of this year, the total value was US$500 million.

Yotta CEO Sunil Gupta said that among the 16,000 GPUs, there are two models: H100 and GH200.

You must know that the price of an H100 GPU will exceed US$30,000 in 2022, and the GH200 will be even more expensive.

So, 500 million US dollars can’t actually buy a lot of GH200. We don’t know the exact amount, but it is estimated to be several thousand H100 and a small amount of GH200. It is still unknown how much discount Indian companies can get from Nvidia.

In addition to this order, Yotta also bought 16,000 GPUs last year. But that time I bought all H100s, and the delivery time was July this year.

What’s more interesting is that the total order price last year was almost US$500 million. In this way, the two orders together easily exceeded US$1 billion. It has to be said that it is a sky-high price order.

However, in fact, H100 is not too expensive to buy. After all, H200 is also available, so the price of H100 needs to be reduced somewhat. Therefore, Yotta CEO Gupta said that the company did not increase its budget too much and also bought back many high-end GPUs.

Having said that, since the United States banned Nvidia from exporting high-end GPUs to China, such a large market has disappeared.

Moreover, the slightly inferior H800 GPU that Nvidia later produced specifically for the Chinese market was also prohibited from exporting. This large order from India can be regarded as making up for part of Nvidia's GPU exports. blank.

Yotta buys so many GPUs that they will eventually be deployed in the artificial intelligence data center of the Gujarat International Financial Technology City (GIFT-City), which will open in March this year.

Currently, the place is still under construction.

Yotta officially predicts that by 2030, India’s machine learning industry will reach US$14 billion. Gupta said this is only possible with complete and robust infrastructure.

"To put it bluntly, whether it can work depends on American hardware. To put it bluntly, it is NVIDIA's hardware."

Will be deployed in the international financial technology of Gujarat City’s artificial intelligence data center, which will open in March.

You know, Yotta is not the only Indian company to have recently struck a deal with Nvidia.

In September last year, Nvidia announced a partnership with India’s Reliance Industries and the Tata Group.

Both companies are very large in scale. Reliance Industries is a giant in the fields of energy production, finance, biotechnology, and telecommunications.

The same is true for the Tata Group, whose main business areas include communications and information technology, engineering, materials, services, energy, consumer products and chemical products.

#However, it is unclear how many GPUs Tata or Reliance have committed to deploying to develop their artificial intelligence-related services.

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