Jensen Huang, Ultraman, and Masayoshi Son: A 20-Year Alliance

Original Title: "Jensen Huang, Ultraman, and Masayoshi Son: A 20-Year Alliance"
Original Author: Su Yang, Tencent Technology

OpenAI is locking in computing power for the next 20 years, and NVIDIA is also reaching beyond chips.

On August 17, local time in the United States, NVIDIA, OpenAI, and SB Energy, a subsidiary of SoftBank, confirmed their collaboration to build a large data center in the U.S. SB Energy will be responsible for development and operations, while OpenAI will be the client, with the data center entirely utilizing NVIDIA's computing power.

The most notable aspect of the three-party transaction is the role NVIDIA plays. It is both a power supplier and provides a guarantee of up to $105 billion for OpenAI's long-term lease, while also directly investing in the project construction. What was originally a transaction between developers, tenants, and financing institutions now includes a layer of a chip company.

Why is NVIDIA willing to take on such risks, and why is OpenAI locking in a 20-year computing power lease?

One fact and trend is that under the expanding demand for computing power, land, electricity, and data center capacity have become "bottleneck" resources, prompting various parties to scramble for positioning. However, in Huang's view, the balance sheets of cutting-edge AI labs do not compare to those of cloud giants, leading to the method of "chip companies participating as guarantors."

In reality, cloud giants are also "struggling forward."

According to an analysis by The Wall Street Journal of the latest financial reports from nine major tech companies, their off-balance-sheet commitments related to AI (not included in the balance sheet, mainly from chip procurement and long-term lease obligations for data centers) have approached $30 trillion, which is three times the total of current lease liabilities and long-term debts.

The data center project in collaboration with OpenAI and SB Energy is located in the PORTS-Pike park in Ohio, USA. It plans to build at least 10GW of new energy generation capacity, and once completed, the park will exclusively deploy NVIDIA's computing infrastructure, ultimately forming about 8GW of AI factory capacity.

The project construction is divided into two phases. The first phase plans a capacity of 4.25GW, with the first batch of 800MW expected to be operational in 2028, mainly utilizing existing AEP Ohio infrastructure. Subsequently, the project will need to continue building power plants, transmission lines, and other grid facilities, then expand the data center capacity to the planned target.

NVIDIA can also fulfill an additional capacity guarantee of 3.75GW based on future demand, but there are currently uncertainties regarding infrastructure and permitting approvals, and NVIDIA is not obligated to lease all of it.

The data center park in southern Ohio began construction in March this year

SB Energy and SoftBank plan to invest at least $4.2 billion in building new regional grid infrastructure. SB Energy is responsible for the construction, ownership, and operation of the data center, while OpenAI will use the capacity as it is built and delivered.

Currently, OpenAI has signed a 20-year lease with SB Energy. The agreement states that OpenAI will only start paying rent once the corresponding capacity is completed and available for lease.

Locking in long-term capacity in advance allows OpenAI to secure its future computing power needs. However, this does not mean NVIDIA will pay all of OpenAI's rent for 20 years.

According to the agreement, NVIDIA's maximum payment responsibility (or total payment obligation limit) for this transaction is $105 billion, mainly covering costs related to land, electricity, and data center infrastructure.

NVIDIA employs a residual value guarantee structure: if OpenAI stops leasing, SB Energy must find a new tenant. If there is no new lease, it will consider selling the related assets. NVIDIA will only cover the shortfall if the agreed minimum value is not met.

Thus, the $105 billion guarantee corresponds to the residual value of the already built data center assets and will phase into effect as the project is constructed and put into use, roughly covering the period from 2028 to 2030. As OpenAI pays rent and the data center capacity comes online, the actual risk exposure for NVIDIA will gradually decrease.

NVIDIA is willing to do this, primarily due to this risk exposure. Even if OpenAI reduces usage in the future, the already built computing capacity can still be transferred to cloud service providers, enterprises, AI labs, and startups.

On the same day this news was released, Jensen Huang wrote an article explaining why NVIDIA would participate in such projects. His judgment is based on the fact that AI factories require more and more resources. In the past, advanced chips, packaging, memory, and networks were the main investments in AI infrastructure. Now, land, electricity, and data centers must also be secured in advance.

In Huang's view, large cloud service providers and investment-grade enterprises typically have sufficiently large balance sheets and the ability to sign long-term contracts and build their own infrastructure. However, cutting-edge AI labs may not have such conditions.

These companies' training and inference needs are growing rapidly, and their revenues may increase accordingly, but locking in land, electricity, and data center capacity for decades in advance requires stable cash flow and strong financing capabilities, which many AI labs currently lack.

Thus, a new bottleneck has emerged.

Huang wrote that the growth of these companies is "not limited by algorithms or customer demand, but by the availability of computing power."

NVIDIA's involvement in data center infrastructure (LPS, Land, Power and Shell) is aimed at solving this problem. However, this does not mean NVIDIA is ready to provide similar services to all customers. Huang emphasized that NVIDIA will only choose a few high-quality sites with clear, long-term computing needs.

Huang revealed that each generation of NVIDIA AI factory systems deployed in the PORTS-Pike park may correspond to about 1.5 million NVIDIA GPUs, or about $150 billion to $200 billion in NVIDIA revenue.

The term "each generation" is crucial. For NVIDIA, what is actually locked in during the 20-year agreement period is the infrastructure that will support its computing systems long-term, rather than fixed orders for a specific generation of GPUs.

OpenAI's long-term commitments further amplify this opportunity.

Huang stated that OpenAI's existing and planned commitments correspond to about 12GW of NVIDIA computing power. If PORTS-Pike continues to expand, the related capacity will increase. Based on this scale, by 2030, the deployment opportunities related to OpenAI may correspond to about $600 billion in NVIDIA computing power value.

In the past, chip companies "invested" in customers, sparking discussions about circular financing. Now, the relationship has progressed further, with chip companies directly laying out data centers to back construction, providing "guarantee endorsements" for the computing needs of cutting-edge labs, while also ensuring that data center construction will bring them continuous orders.

The computing power story of PORTS-Pike is not just about NVIDIA and OpenAI.

In the past two years, AI companies and large tech firms have been frantically building data centers, but increasingly, much of the infrastructure is not directly purchased by them but secured through leases, long-term procurement agreements, joint ventures, and other financing structures.

The Wall Street Journal recently analyzed the latest securities filings from nine major tech companies, including Alphabet, Amazon, Microsoft, Meta, Oracle, NVIDIA, Broadcom, SpaceX, and AMD, and found that as of the latest filing, their off-balance-sheet commitments related to AI totaled about $30 trillion.

Compared to about $600 billion in capital expenditures over the past year, the scale of off-balance-sheet commitments signed by these companies is much larger.

Meta's Hyperion data center is a typical example.

This data center located in Louisiana covers an area equivalent to 1,700 football fields and is managed by a fund held by Blue Owl Capital, which is responsible for construction. Meta is one of the few partners and also a tenant, with its rent providing cash flow for bondholders.

Before starting to pay rent, this obligation will not be fully reflected in Meta's balance sheet. As of June this year, Meta disclosed that its total lease obligations that have not yet begun reached $347 billion, which includes the Hyperion project.

As of June, Meta has leased the Hyperion data center in Louisiana, but rent has not yet begun, and related lease obligations have not been fully accounted for in the balance sheet.

According to statistics, the nine companies' lease payment commitments that have not yet begun total about $1.2 trillion, which is four times the amount disclosed a year ago. Purchase commitments and other contractual obligations amount to about $1.9 trillion.

Among them, Alphabet's changes are particularly notable.

As of June 30, Alphabet's purchase commitments and contractual obligations reached $811 billion, up from $332 billion three months prior. Alphabet explained that these obligations mainly involve "technological infrastructure and inventory," as well as agreements to ensure energy supply for data centers. Some energy agreements even extend to 2054. However, Alphabet did not explain in detail why related commitments increased by nearly $480 billion in just one quarter.

The expansion risks are not limited to data center leasing and chip procurement. Some companies' commitments also include purchasing stocks from other companies or providing guarantees for other tenants' leases. NVIDIA itself has also committed to making a $27 billion equity investment during the fiscal year ending April 26, 2027.

But another risk lies in the expansion of debt. Some tech companies have begun frequently entering the capital markets for debt financing. Alphabet and Amazon recently reported negative free cash flow, with capital expenditures exceeding the cash generated from operations.

Alphabet, Amazon, and Meta's previously healthy cash flows (blue bars) are expected to collectively turn negative in the remaining time of 2026 and 2027 (gray bars).

And these figures do not fully reflect the cash flow pressures that may arise from future trillions of dollars in off-balance-sheet commitments. More troubling is that many purchase commitments and long-term leases cannot be easily canceled. This means that even if future AI demand does not meet expectations, they still have to pay for the signed agreements. In this case, the giants will be forced to cut other expenditures and may further borrow money to maintain these infrastructures.

Morgan Stanley's accounting analysts warned in an April report that as these types of off-balance-sheet commitments become more frequent, larger, and more complex, it will become increasingly difficult for investors to assess a company's true leverage level.

Now, PORTS-Pike stands at the forefront of this trend. But who can guarantee that the demand for computing power will always be infinitely aggressive in expansion and will not slow down?

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