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Nvidia denies pausing AI cloud commitments initiative after reported partner backlash — report claims company told cloud providers it could only lease its GPUs to Nvidia-approved customers

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Why This Matters

Nvidia's recent actions highlight its efforts to maintain control over its AI GPU ecosystem amid growing demand and regulatory concerns. The company's evolving approach to AI compute partnerships underscores the delicate balance between expanding access and managing competitive and legal risks, impacting how cloud providers and AI developers collaborate. This development signals a cautious yet strategic shift in Nvidia's AI industry influence, affecting both industry players and consumers relying on AI infrastructure.

Key Takeaways

Nvidia on Friday denied a report by the Wall Street Journal claiming that the company had put some transactions under its recently introduced 'take or pay' AI Compute Partnership on hold, less than two months after unveiling the initiative in early July and days before detailing the effort in its earnings call. The transactions were reportedly paused as some partners were irritated with Nvidia's attempts to influence their operations and because it raised internal concerns about potential antitrust scrutiny.

"The new business model we introduced in July that opens up compute access to the fast-growing AI ecosystem is still in place and continues to evolve due to high demand," a spokesperson for Nvidia told Tom's Hardware.

The report itself does not establish that Nvidia has abandoned the AI Compute Partnership program under which the company committed to rent capacity of newly built AI data centers as well as their minimum revenue, but claims that it put some deals on hold. Meanwhile, Nvidia's denial indicates that the program continues to exist, but is evolving, which means changing.

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Per the report, it looks like Nvidia attempted to control how its 'AI Compute Partners' rented their capacity. The company told some cloud providers participating in the program that they could lease its GPUs only to customers approved by Nvidia, according to the WSJ report. The company also preferred to spread available capacity across multiple smaller AI companies instead of allowing a single large customer to take most or all of it. Some cloud operators reportedly pushed back against these restrictions, arguing that they should retain control over which customers they serve. Perhaps, in turn, Nvidia put some of the deals on hold.

While Nvidia does not lend any money or directly finance AI data center buildouts (which essentially means circular financing), it provides demand commitments and guaranteed revenue levels, which perhaps raised internal concerns about potential antitrust scrutiny. As a result, Nvidia could be revising the terms of the deals it inks with partners.

$36 billion of commitments

Modern AI data centers cost billions of dollars that must be spent on the premises, infrastructure, and compute hardware well before an operator has secured enough customer contracts to finance the buildout. Meanwhile, banks or infrastructure investors want confidence that enough of the future facility capacity will actually be rented. Under the program, Nvidia intends to use its own demand commitment on a portion of the facility's capacity in exchange for a percentage of the facility's revenue if demand is strong. This makes financing AI data centers easier as from the lender's perspective, part of the project's revenue stream is effectively supported by Nvidia rather than depending entirely on the operator's ability to find customers.

"Nvidia provides a take-or-pay commitment on a portion of the facility's capacity, a minimum revenue guarantee that gives lenders the confidence to underwrite the project, and in exchange, we share in a portion of the NeoCloud's revenue earned above that floor," explained Colette Kress, chief financial officer of Nvidia, during the company's earnings call. "In this model, we get paid twice, once on the hardware sale, and again through the share of rental revenue, a highly recurring stream layered on top of a one-time equipment purchase."

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