Nvidia to Invest Up to $100 Billion in OpenAI to Deploy 10 GW

Nvidia plans to invest up to $100 billion in OpenAI as the company deploys at least 10 gigawatts (GW) of the chipmaker’s systems. The deal, still set out in a letter of intent, ties the funding to the rollout of infrastructure that will require millions of processors and enormous amounts of power.

The first gigawatt is expected to come online in the second half of 2026 and will use Vera Rubin, Nvidia’s next data center platform for artificial intelligence. The companies expect to finalize the partnership’s details in the coming weeks.

An investment tied to deployment

The $100 billion will not arrive all at once. Nvidia plans to invest in OpenAI progressively as each gigawatt comes online, according to the joint announcement. The maximum amount works out to about $10 billion per gigawatt, although the companies have not yet published the full schedule or the financial terms for each tranche.

OpenAI will use the infrastructure to train new models and support everyday use of its products. The company says it already has more than 700 million weekly active users, a scale that makes running models — known as inference — as significant a computing need as training them.

Nvidia will be OpenAI’s preferred strategic partner for computing and networking. The companies will also coordinate their road maps: OpenAI will be able to adapt its software to Nvidia’s future machines, while the chipmaker will design its systems with the workloads of one of its most important customers in mind. The deal is not being presented as exclusive.

Ten gigawatts and four to five million GPUs

The scale becomes easier to understand when the power requirement is translated into equipment. Nvidia CEO Jensen Huang estimated on CNBC that 10 GW would represent between four and five million GPUs, although the final number will depend on the configuration and chip generation used.

A GPU is the specialized processor that performs much of the computation needed to train and run AI models. The project, however, goes beyond buying chips: it also requires CPUs, high-speed networking, cooling, buildings, connections to the power grid and energy generation.

As a physical benchmark, 10 GW is equivalent to the output of ten one-gigawatt power plants operating simultaneously. That does not mean OpenAI will build a single facility or consume all that capacity from day one. It does show the scale of the industrial challenge: securing land, permits, electrical equipment and energy supplies can be just as decisive as having the GPUs.

The platform selected for the first phase, Vera Rubin, will succeed the Blackwell family. Its use from the second half of 2026 indicates that the deal is designed to span several hardware generations, rather than simply address ChatGPT’s current needs.

The new deal adds to Stargate

The partnership expands an infrastructure race in which OpenAI is already working with Microsoft, Oracle, SoftBank and other partners. In January, OpenAI and SoftBank unveiled Stargate, a project aimed at mobilizing up to $500 billion over four years to build AI data centers in the United States.

The Nvidia agreement complements those plans rather than replacing them. OpenAI needs financing, power and data center operators; Nvidia supplies much of the hardware and networking that connects the processors. Microsoft remains a key technology and investment partner, but OpenAI is diversifying the infrastructure on which it trains and serves its models.

A relationship that also raises questions about demand

The deal has an unusual structure: the leading chip supplier is financing a company that will be one of its biggest buyers. For Nvidia, the investment could secure future demand and deepen reliance on its platform. For OpenAI, it reduces the challenge of funding in advance an expansion whose cost far exceeds that of a conventional venture capital round.

That relationship will fuel debate over circular arrangements in the AI industry. Some of the capital provided by Nvidia will help support a rollout that, in turn, will generate sales of Nvidia systems. That does not invalidate the demand — OpenAI needs more capacity to serve its users — but it does make it necessary to distinguish between customer-funded orders and deals backed directly or indirectly by the supplier itself.

It also concentrates risk. If OpenAI’s revenue growth does not keep pace with spending, if power availability delays the data centers or if model improvements reduce the need for computing, the rollout could proceed more slowly. The tranche-based structure limits some of that exposure: Nvidia only expects to approach the full $100 billion as the gigawatts come online.

The next step will be turning the letter of intent into definitive agreements. Until then, the $100 billion represents a conditional ceiling, not a completed transfer, and the 10 GW is a deployment target whose execution will begin no earlier than the second half of 2026.