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Yann Le Cun meta AI
Meta’s chief AI scientist, Yann LeCun (Julien De Rosa/Getty Images)
GP-who?

Just four companies are hoarding tens of billions of dollars worth of Nvidia GPU chips

Each Nvidia H100 can cost up to $40,000, and one big tech company has 350,000 of them.

Jon Keegan

Meta just announced the release of Llama 3.1, the latest iteration of their open source large language model. The long-awaited, jumbo-sized model has high scores on the same benchmarks that everyone else uses, and the company said it beats OpenAi’s ChatGPT 4o on some tests. 

According to the research paper that accompanies the model release, the 405b parameter version of the model (the largest flavor) was trained using up to 16,000 of Nvidia’s popular H100 GPUs . The Nvidia H100 is one of the most expensive, and most coveted pieces of technology powering the current AI boom. Meta appears to have one of the largest hoards of the powerful GPUs. 

Of course, the list of companies seeking such powerful chips for AI training is long, and likely includes most large technology companies today, but only a few companies have publicly crowed about how many H100s they have.  

The H100 is estimated to cost between $20,000 and $40,000 meaning that Meta used up to $640 million worth of hardware to train the model. And that’s just a small slice of the Nvidia hardware Meta has been stockpiling. Earlier this year, Meta said that it was aiming to have a stash of 350,000 H100s in its AI training infrastructure – which adds up to over $10 billion worth of the specialized Nvidia chips. 

Venture capital firm Andreesen Horowitz is reportedly hoarding more than 20,000 of the pricey GPUs, which it is renting out to AI startups in exchange for equity, according to The Information

Tesla has also been collecting H100s. Musk said on an earnings call in April that Tesla wants to have between 35,000 and 85,000 H100s by the end of the year.  

But Musk also needs H100s for X and his AI company xAI. This week, Musk boasted on X that xAI’s company’s training cluster is made up of 100,000 H100s. 

A tweet from Elon Musk stating that xAI has 100,000 H100 GPUs.
Source: X @elonmusk https://x.com/elonmusk/status/1815325410667749760


Musk was recently sued by Tesla shareholders for allegedly re-directing 12,000 of the H100s intended for the car maker’s AI training infrastructure to xAI instead. When asked about this diversion in yesterday’s Tesla Q2 earnings call, Musk said that the GPUs were sent to xAI because “the Tesla data centers were full. There was no place to actually put them.”

The H100s are in such demand that people are being paid to sneak them into China, to bypass U.S. export controls. You can watch unboxing videos of these graphics cards, and there are even a few for sale on Amazon – including one for $34,749.95 (with free delivery).

OpenAI hasn’t said how many H100s they are sitting on, but The Information reports that the company rents a cluster of processors dedicated to training from Microsoft at a steep discount as part of Microsoft’s $10 billion investment in OpenAI. The training cluster reportedly has the power of 120,000 of Nvidia’s previous gen A100 GPUs, and will be spending $5 billion to rent more training clusters from Oracle over the next two years, according to The Information’s report. OpenAI does appear to have a special relationship with Nvidia — in April, Nvidia CEO Jensen Huang “hand-delivered” the first cluster of the company’s next generation H200 GPUs to co-founders Sam Altman and Greg Brockman. 

A tweet by OpenAI’s Greg Brockman with a photo featuring Brockman, OpenAI CEO Sam Altman and Nvidia CEO Jensen Huang
Source: X @gbd https://x.com/gdb/status/1783234941842518414

Nvidia declined to comment for this story, and Meta, X, OpenAI, Tesla, and Andreessen Horowitz did not respond to requests for comment. 

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OpenAI acquires Astral, adding talent to Codex team

OpenAI has acquired open-source Python tool developer Astral, bringing aboard additional coding talent for its Codex team.

The company said the acquisition will help Codex “expand beyond coding” by helping address a wider range of development tasks, such as planning, testing, and code maintenance.

OpenAI said Codex has seen “3x user growth and 5x usage increase” since the start of 2026, and has over 2 million weekly active users.

Software development is emerging as one of the key battlegrounds where OpenAI is competing for market share with Anthropic, which has been enjoying success with its Claude Code product.

OpenAI said it will continue to support Astral’s open-source software projects.

OpenAI said Codex has seen “3x user growth and 5x usage increase” since the start of 2026, and has over 2 million weekly active users.

Software development is emerging as one of the key battlegrounds where OpenAI is competing for market share with Anthropic, which has been enjoying success with its Claude Code product.

OpenAI said it will continue to support Astral’s open-source software projects.

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Elon Musk gives an estimate for Tesla’s AI6 chip timeline... while the AI5 is still unfinished

Tesla CEO Elon Musk said yesterday that the company’s AI6 chip could, with “some luck and acceleration using AI,” be finalized and sent to manufacturing by December. For those paying attention, Tesla hasn’t confirmed that its previous chip, the AI5, has reached tape-out, with Musk saying only that the design is in “good shape” and “almost done.” Still, Musk is already talking about subsequent chips AI6, AI7, AI8, and beyond.

Here’s a roundup of when these chips are expected, what they’re supposed to do, and what Musk himself has said about them.

While the AI5 and AI6 will be made by TSMC and Samsung, respectively, Musk has said Tesla eventually aims to manufacture its future AI chips at Tesla’s upcoming Terafab factory in Austin.

tech

NHTSA expands Tesla FSD probe, focusing on whether system can detect when cameras can’t see the road

The National Highway Traffic Safety Administration said it is expanding its probe into Tesla’s Full Self-Driving system into an engineering analysis covering about 3.2 million Teslas, a majority of its vehicles that are on the road in the US, Reuters reports.

The agency is focusing on Tesla’s “degradation detection system,” which is meant to recognize when its camera-based technology cannot reliably perceive the road and prompt drivers to intervene:

“Available incident data raise concerns that Tesla’s degradation detection system, both as originally deployed and later updated, fails to detect and/or warn the driver appropriately under degraded visibility conditions such as glare and airborne obscurants. In the crashes that ODI has reviewed, the system did not detect common roadway conditions that impaired camera visibility and/or provide alerts when camera performance had deteriorated until immediately before the crash occurred.”

Tesla CEO Elon Musk has long argued that the company’s self-driving approach does not require the expensive lidar sensors used by rivals such as Waymo.

The agency is focusing on Tesla’s “degradation detection system,” which is meant to recognize when its camera-based technology cannot reliably perceive the road and prompt drivers to intervene:

“Available incident data raise concerns that Tesla’s degradation detection system, both as originally deployed and later updated, fails to detect and/or warn the driver appropriately under degraded visibility conditions such as glare and airborne obscurants. In the crashes that ODI has reviewed, the system did not detect common roadway conditions that impaired camera visibility and/or provide alerts when camera performance had deteriorated until immediately before the crash occurred.”

Tesla CEO Elon Musk has long argued that the company’s self-driving approach does not require the expensive lidar sensors used by rivals such as Waymo.

$1B

Apple is behind the rest of Big Tech when it comes to developing its own AI, but that hasn’t stopped it from cashing in on the AI boom. The iPhone maker stands to bring in more than $1 billion in App Store fees this year from other companies’ generative-AI apps, mostly from ChatGPT, The Wall Street Journal reports, citing data from App Magic.

Unlike rivals pouring hundreds of billions into AI infrastructure, Apple’s spending has been relatively modest, with its overall capital expenditure actually declining last quarter. Its lucrative App Store model lets Apple profit from AI as a gatekeeper without fully joining the expensive race to build it.

Multicolor Sticks

OpenAI is shipping everything. Anthropic is perfecting one thing.

The two AI titans are in a race to grow revenues, but they have very different strategies for releasing products. And one approach appears to be winning out.

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