Nvidia to Derive 25% of Next Year’s Revenue from Funded Labs

Nvidia has deployed nearly US$50 billion into AI labs purchasing its chips, securing commitments for over $500 billion in total.

On August 26, CFO Colette Kress informed analysts that these labs, backed by Nvidia’s balance sheet, will account for roughly a quarter of the company’s business next year.

This structure, often termed circular financing, was acknowledged by Nvidia before analysts coined the phrase. Kress noted on the earnings call that while the company recognizes the scale of its support, it views the arrangement differently.

The mechanism is straightforward: Nvidia invests in an AI lab, which uses the funds or credit to build a data center filled with Nvidia chips. These purchases generate revenue, boosting Nvidia’s stock price and cash reserves, enabling further investment.

What Nvidia has committed

Kress disclosed partnerships with six investment firms—Apollo Global Management, BlackRock, Blackstone, Brookfield Asset Management, Goldman Sachs, and KKR—to create financing platforms raising over $500 billion for lab infrastructure.

Nvidia secured land, power, and building capacity with SB Energy for facilities hosting only Nvidia equipment. The first phase supports 4.25 gigawatts for OpenAI, with total commitments reaching 12 gigawatts through 2030. For an unnamed second lab, Nvidia provides credit support for nearly two gigawatts.

These partnerships await definitive agreements, meaning binding contracts are not yet signed. The $500 billion represents intent rather than committed capital.

Nvidia also supports smaller cloud operators by guaranteeing a portion of their capacity, providing lenders with a steady income stream. In return, Nvidia shares in revenue above this floor, earning from both equipment sales and rental income.

Why Nvidia rejects the circular financing label

Kress provided three key arguments to contextualize these figures.

She emphasized that external lenders evaluate each deal independently, and Nvidia does not issue loans. Shipped chips go to investment-grade customers or those backed by such entities. If a customer defaults, equipment can be redeployed, limiting Nvidia’s exposure.

Kress explained that labs require assistance due to high computing demand outpacing their financial capacity. As young companies lacking long-term contracts and credit ratings, they face funding hurdles. Their growth is constrained not by technology or demand, but by access to computing resources.

The primary risk is customer default, which would cause Nvidia to lose both the sale and investment. Kress argues hardware can be resold, a claim valid only while demand exceeds supply, which Nvidia currently maintains.

BofA Securities’ Vivek Arya asked Jensen Huang how Nvidia funds labs developing rival chips, like OpenAI’s Jalapeño. Huang stated Nvidia sells a versatile platform usable across any cloud throughout an AI system’s lifecycle, unlike single-service rival chips. He expressed regret only for not investing more and sooner.

The agent assumption underneath it all

Kress told Morgan Stanley’s Joseph Moore that AI agents require 15 to 100 times the computing power of human users. Huang believes AI has recently shifted toward being predominantly agentic, though Nvidia provided no supporting data.

Based on this, Nvidia guided for $108 billion in quarterly revenue and projected approximately 70% year-over-year growth through January 2028, a figure Kress attributed to supply constraints rather than demand.

Kress warned that memory prices are rising faster than anticipated, guiding margins down to 74% this quarter and 71–72% in the fourth. She attributed memory scarcity largely to the ongoing AI infrastructure buildout.

Nvidia’s next report is scheduled for November 17. Kress did not disclose which lab receives credit support for nearly 2 gigawatts.

See also: NVIDIA Jetson Orin Nano 2 brings physical AI to drones and robots

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