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DeepSeek And Nvidia Logos
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The trillion-dollar mystery surrounding DeepSeek’s Nvidia GPUs

There’s a cloud of suspicion hanging over the type and number of Nvidia GPUs DeepSeek used to train its R1 models.

At the center of the story of DeepSeek’s breakthrough achievement with its R1 models lies the Nvidia hardware that powered the servers that trained those models.

In December 2024, DeepSeek researchers released a paper that outlined the development and capabilities of the new DeepSeek-V3 large language model. In the paper, the researchers said they were able to train their powerful, efficient model over 2.78 million GPU hours of computing time on a cluster of only 2,048 Nvidia H800 GPUs. That is a very small number of GPUs for a model that matched or beat OpenAI’s state-of-the-art o1 model in some benchmarks.

For comparison, Meta trained its Llama 3.1 models on two clusters, using a total of 39.3 million GPU hours with 49,152 Nvidia H100 GPUs. Last week, Mark Zuckerberg said that Meta is planning on ending 2025 with over 1.3 million GPUs.

Released in 2023, the H800 is a GPU thats similar to the H100 but is tailored for the Chinese market to comply with US export controls concerning national security parameters that the Biden administration rolled out in 2022. Reuters reported that the main thing Nvidia changed in the H800 was that it “reduced the chip-to-chip data transfer rate to about half the rate.”

But The Wall Street Journal reports that government officials found the H800 exploited technical loopholes that met the strict requirements of the ban, but still gave Chinese buyers very powerful AI chips. To close the loophole, in October 2023, the US government banned the export of H800s as well.

It appears that DeepSeek was able to acquire its H800s during that short window of availability.

DeepSeek’s claims are drawing suspicion from some observers in the AI industry, but most appear to be just speculation. Scale AI CEO Alexandr Wang told CNBC that he suspected DeepSeek has “about 50,000 H100s, which they can’t talk about obviously because it is against the export controls that the United States has put in place,” and in a tweet, Elon Musk replied, “Obviously.” Musk, meanwhile, has bragged about xAI’s “Colossus supercluster,” which is powered by 100,000 H100 GPUs, and that he plans to scale up to 1 million of the expensive Nvidia chips.

There have been reports of H100s being smuggled into China through a series of intermediaries on the black market, but no evidence that DeepSeek did so.

Adding to the confusion, DeepSeek cofounder Liang Wenfeng said that the company does own a cluster of 10,000 Nvidia A100 GPUs, a cheaper and less powerful AI chip.

The H100 has earned a status of being one of the most coveted pieces of computer hardware in the AI age. Even when other chips are used, the power is sometimes expressed as a number of “H100-equivalent” GPUs.

Nvidia is in the process of rolling out its next-gen H200 Blackwell GPUs, and last year CEO Jensen Huang hand-delivered the first DGX H200 server to OpenAI headquarters.

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Jon Keegan

EPA: xAI’s Colossus data center illegally used gas turbines without permits

The Environmental Protection Agency has ruled that xAI violated the law when it used dozens of portable gas generators for its Colossus 1 data center without air quality permits.

When xAI set out to build Colossus 1 in Memphis, Tennessee, CEO Elon Musk wanted to move with unprecedented speed, avoiding all of the red tape that could slow such a big project down.

To power the 1-gigawatt data center, Musk took advantage of a local loophole that allowed portable gas generators to be used without any permits, as long as they did not spend more than 364 days in the same spot. That allowed xAI to bring in dozens of truck-sized gas generators to quickly supply the massive amount of power the data center needed to train xAI’s Grok model.

The new EPA rule says the use of such portable generators falls under federal regulation, and the company did need air quality permits to operate the turbines. xAI is also using dozens of such generators to power its Colossus 2 data center just over the border in Alabama.

To power the 1-gigawatt data center, Musk took advantage of a local loophole that allowed portable gas generators to be used without any permits, as long as they did not spend more than 364 days in the same spot. That allowed xAI to bring in dozens of truck-sized gas generators to quickly supply the massive amount of power the data center needed to train xAI’s Grok model.

The new EPA rule says the use of such portable generators falls under federal regulation, and the company did need air quality permits to operate the turbines. xAI is also using dozens of such generators to power its Colossus 2 data center just over the border in Alabama.

tech
Rani Molla

Trump to push Big Tech to fund new power plants as AI drives up electricity costs

President Donald Trump is expected to announce a plan Friday morning that would require Big Tech companies to bid on 15-year contracts for new electricity generation capacity. The move would effectively force companies to help fund new power plants in the PJM region as soaring demand from AI data centers pushes up electricity costs across the US power grid.

Earlier this week, Trump called on tech giants to “pay their own way,” arguing that households and small businesses should not bear the cost of power infrastructure needed to support energy-hungry data centers.

Microsoft quickly responded, saying it would “pay utility rates that are high enough to cover our electricity costs,” along with committing to other changes aimed at easing pressure on the grid. Other major tech companies are expected to follow suit, though Wedbush Securities analyst Dan Ives warned the added costs could slow the pace of data center build-outs.

As we’ve noted, forcing tech companies to shoulder higher electricity costs is likely to hit some firms harder than others. Companies like Microsoft, Google, and Amazon can pass at least some of those costs on to customers by selling data center capacity downstream. Meta, in contrast, does not have a cloud business, meaning its AI ambitions lack a direct revenue stream to offset rising power costs.

So far tech stocks don’t appear to be affected much in premarket trading. However utility companies most levered to the AI boom certainly are, with Vistra, Constellation Energy, and Talen Energy deep in the red ahead of the open as analysts at Jefferies warn that these firms face risks from this plan.

Earlier this week, Trump called on tech giants to “pay their own way,” arguing that households and small businesses should not bear the cost of power infrastructure needed to support energy-hungry data centers.

Microsoft quickly responded, saying it would “pay utility rates that are high enough to cover our electricity costs,” along with committing to other changes aimed at easing pressure on the grid. Other major tech companies are expected to follow suit, though Wedbush Securities analyst Dan Ives warned the added costs could slow the pace of data center build-outs.

As we’ve noted, forcing tech companies to shoulder higher electricity costs is likely to hit some firms harder than others. Companies like Microsoft, Google, and Amazon can pass at least some of those costs on to customers by selling data center capacity downstream. Meta, in contrast, does not have a cloud business, meaning its AI ambitions lack a direct revenue stream to offset rising power costs.

So far tech stocks don’t appear to be affected much in premarket trading. However utility companies most levered to the AI boom certainly are, with Vistra, Constellation Energy, and Talen Energy deep in the red ahead of the open as analysts at Jefferies warn that these firms face risks from this plan.

tech
Jon Keegan

OpenAI working to build a US supply chain for its hardware plans, including robots

When OpenAI purchased Jony Ive’s I/O, it entered the hardware business. The company is currently ramping up to produce a mysterious AI-powered gadget.

But OpenAI plans on making more than just consumer gadgets — it also plans on making data center hardware, and even robots.

Bloomberg reports that OpenAI has been on the hunt for US-based suppliers for silicon and motors for robotics, as well as cooling systems for data centers.

AI companies are looking toward robots as a logical next step for finding applications for their models.

OpenAI told Bloomberg that US companies building the AI brains of robots might have an edge against the Chinese hardware manufacturers that are currently making some impressive humanoid robots.

Bloomberg reports that OpenAI has been on the hunt for US-based suppliers for silicon and motors for robotics, as well as cooling systems for data centers.

AI companies are looking toward robots as a logical next step for finding applications for their models.

OpenAI told Bloomberg that US companies building the AI brains of robots might have an edge against the Chinese hardware manufacturers that are currently making some impressive humanoid robots.

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