Nvidia (NVDA)
Financing Partnership with six financial giants.
Yesterday the Financial Times reported that Nvidia (NVDA) was teaming up with large financial firms to assemble a $500bn funding package of more than $500bn for AI infrastructure development.
Today more details on this were given in an article written by Nvidia CEO Jensen Huang which was published on Linked-in. it can be found here.
So far the AI investment boom has been financed by the Hyperscalers and Nvidia, the public debt and equity markets and the private market. There have on balance sheet and off-balance sheet financings.
Investors have expressed several concerns
The scale of the investment is so large, it is overwhelming the capacity of previously strongly cash generative companies. Alphabet, Amazon, Oracle have negative free cash flow, and Meta is likely to join them.
The huge increase in borrowing by the hyperscalers in the public debt markets has pushed up borrowing costs and credit spreads.
Nvidia has used its prodigious cash flows to invest in neo clouds and other companies building up compute capacity. This has led to criticism that it is vendor financing or circular financing.
In the article, Huang argues the nature of compute has changed.
We have moved from an era in which companies bought chips and built datacentres project by project to one in which AI factories can be financed as productive infrastructure — with repeatable platforms, long-term institutional capital and a diverse customer base that uses compute to create revenue.
AI is creating real value, and the infrastructure behind it is becoming one of the world’s most productive assets.
A New Infrastructure Asset
Huang argues compute is an infrastructure asset.
NVIDIA compute is …a complete AI factory platform including accelerated computing, networking, systems software, AI frameworks and a global developer ecosystem.
NVIDIA DSX AI factories can run the world’s broadest range of AI models, modalities and algorithms — language, vision, speech, biology, physical AI and robotics. One NVIDIA AI factory can serve many customers and many workloads. That makes it flexible and fungible.
It is a flexible use productive industrial asset.
When needs change, the factory can be used by another customer, another cloud or another operator. This broad ecosystem gives NVIDIA compute a deep market of potential users and offtakers, helping protect residual value.
Companies assume Nvidia chips have a 3-4 year useful life and they depreciate them down to zero over the period.
Huang argues this may be an error as the CUDA software stack can be used to extend the useful up to a decade
CUDA makes the factory better over time. Every generation of NVIDIA software improves the performance, efficiency and total cost of ownership of already- installed infrastructure. …software innovation allows an AI factory to produce more intelligence at lower cost throughout its life, extending its useful economic value.
NVIDIA A100 is a powerful example. NVIDIA introduced the Ampere-based A100 in 2020, and six years later, it remains in active commercial use for AI training, fine-tuning, inference and high-performance computing. Customers continue to commit capacity for multi-year deployments, extending A100’s economic life toward a decade.
The per user charges for using old GPUs has risen over time
One-year H100 rental pricing rose from about $1.70 per GPU-hour in October 2025 to about $2.35 per GPU-hour in March 2026. Cross-provider on-demand median pricing rose from roughly $2.00 per GPU-hour in October 2025 to $2.70 in June 2026. Blackwell capacity commands a premium, with reported B200 cloud rates spanning approximately $5.30 to $7.05 per GPU-hour.
A decade-long asset with growing revenues will appeal to lenders especially as demand for compute us much greater than supply.
The listed institutions… “are also among the world’s leading infrastructure investors, with deep expertise in underwriting long-lived, productive assets. Together, we are creating repeatable financing platforms to help the AI ecosystem build the factories it needs.”
The more than $500 billion figure represents aggregate third-party capital that these platforms are designed to mobilize over time — the capital is not NVIDIA revenue, a single fund or a commitment to a single customer.
The financial institutions will independently assess each opportunity — the customer, demand, utilization, cash flow and residual value.
NVIDIA provides the AI factory platform. The financial institutions provide long-term capital and financing expertise.
It is not circular financing.
We are bringing independent, long-term institutional capital into the AI infrastructure market….This is the beginning of an open capital market for AI infrastructure.
Nvidia has some risks as in some cases it will commit to buy the infrastructure at the end of its financing period at a price agreed now.
In some cases, NVIDIA may provide a residual-value support mechanism for up to 25% of an opportunity, assessed carefully on a project-by-project basis. That support is limited, residual-value based and designed to complement — not replace — independent underwriting.
Our role is to help unlock a very large pool of independent capital while maintaining disciplined risk exposure.
Can the market absorb this capacity?
There is discipline in the model. Each financing partner will independently evaluate demand, utilization, cash flow and residual value. Capacity will be built around real customer economics.
Where is the return on investment?
The return is in the usefulness of AI.
An AI factory turns energy and data into valuable intelligence. Its customers are broad: frontier AI labs, AI clouds, enterprises and nations. They are building AI because it has become useful — doing valuable work across every industry.
Companies are using AI to write software, discover drugs, design products, serve customers, automate operations and build new services.
AI factories make this possible. More compute creates better AI; better AI creates more usage; more usage creates more revenue; and more revenue drives more compute.
This is the virtuous cycle of the AI industrial revolution.
The Infrastructure of Intelligence
Every industrial revolution has been built on infrastructure: electricity, transportation, communications and computing, with every buildout enabled by external financing.
AI factories are the infrastructure of the intelligence era.
With these partnerships, NVIDIA and the world’s leading financial institutions are creating a new way to finance the infrastructure that will power this industrial revolution. We will make AI factories more accessible to the companies, industries and nations building the future.
Our View
This is an interesting development. The institutions are already involved in AI infrastructure financing.
For example, BlackRock has a venture to finance the development and operation of a 1 GW Meta datacentre in El Paso Texas.
This is a welcome additional $500bn financing over time. If the money is disbursed over four years, it averages about $125bn per year.
As a comparison, the hyperscaler are investing around $1 trillion ARR. This project is a meaningful additional but not a transformative one.
Nvidia implies they will not engage in any more circular financing. They may however still have some additional exposure as they have committed to purchase 25% of the residual value of some of the assets. They can pick and choose the asset.