Nvidia’s next fiscal year will have a surprising dependency: roughly a quarter of its revenue is expected to come from AI labs the company itself is financing. That is not speculation — it is the company’s own forecast, delivered by CFO Colette Kress on an earnings call that has reshaped how investors understand the AI boom.
The Loop Behind Nvidia’s Next-Generation Revenue
The arrangement is straightforward but consequential. Nvidia invests in an AI lab. The lab uses that money — or the credit Nvidia’s involvement unlocks — to buy Nvidia chips. Those purchases become Nvidia’s revenue. The cycle repeats.
Kress told analysts on August 26 that demand from these backed labs will contribute toward roughly a quarter of the company’s business next year. The scale is unprecedented for a semiconductor company.
Why This Financing Structure Matters to Investors
This is what analysts mean by circular financing — a term Nvidia used before anyone else did. Kress acknowledged the company recognised the scale of its support and knew some would call it circular financing. She said Nvidia sees it differently.
For investors, the distinction matters. Circular financing can inflate revenue figures if the ultimate end-user demand is weak. If labs are buying chips primarily because Nvidia funded them, the question becomes: what happens when the funding stops?
The $50 Billion Commitment and $500 Billion Pipeline
Nvidia has put nearly US$50 billion into the AI labs that buy its chips. That is not a small strategic bet — it is a balance sheet commitment that rivals the GDP of small nations.
Beyond what has already been deployed, the company has lined up commitments for more than $500 billion. This pipeline suggests Nvidia is not treating these investments as one-off support but as a structural part of its go-to-market strategy.
Who Is Affected: From Startups to Enterprise Buyers
The labs receiving Nvidia funding are not anonymous entities. They are the AI research organisations building the next generation of models — the ones competing with OpenAI, Anthropic, and Google DeepMind. For these labs, Nvidia’s investment is a lifeline that secures access to scarce chips.
For enterprise buyers, the implication is different. If a significant portion of Nvidia’s revenue is tied to labs it funds, the pricing and availability of chips for independent buyers could be affected. Nvidia’s balance sheet is effectively subsidising a segment of its own demand.
What Nvidia Says About the Circular Financing Debate
Kress did not dodge the question. She said the company recognised the scale of the support it was providing and knew some would call it circular financing. Her response framed it as a deliberate strategy rather than an accounting artefact.
Nvidia’s position is that these investments are not merely recycling money but building the ecosystem that will drive long-term AI adoption. The company sees itself as accelerating the market, not just propping up its own numbers.
Analyst Interpretation: Supportive or Concerning?
The debate among analysts is whether this model strengthens Nvidia’s moat or exposes it to concentration risk. Supporters argue that Nvidia is simply doing what platform companies do — investing in the ecosystem that makes their hardware indispensable.
Sceptics point out that if the labs Nvidia funds fail to generate sustainable revenue of their own, the circular loop could unwind. The $500 billion in commitments is a promise of future demand, but it is also a promise of future dependency.
Confirmed Facts vs What Remains Unclear
Confirmed: Kress stated on the August 26 earnings call that backed labs will contribute roughly a quarter of next year’s revenue. Nvidia has invested nearly $50 billion in these labs. Commitments exceed $500 billion.
Unclear: The exact breakdown of which labs receive funding and how much each contributes to revenue has not been disclosed. Whether these labs can achieve independent profitability remains an open question. The long-term sustainability of the circular financing model is unproven.
Why Nvidia’s Ecosystem Strategy Sets It Apart
Nvidia’s advantage is not just chip design — it is the full stack. The company’s CUDA software platform, networking technology, and ecosystem partnerships make its hardware more valuable than the sum of its parts. This is why labs accept Nvidia’s financing and why the loop works.
Competitors like AMD and Intel can match raw specifications, but they cannot easily replicate the network effect Nvidia has built. Every lab that adopts Nvidia’s stack reinforces the ecosystem, making it harder for challengers to break in.
Risks and Balanced View: The Bull and Bear Case
Bull case: Nvidia is building the infrastructure of the AI era. Its investments accelerate adoption, and the revenue from backed labs is real revenue — chips are shipped, models are trained, products are built.
Bear case: Circular financing can mask true end-demand. If the labs Nvidia funds are not viable businesses on their own, the revenue is essentially Nvidia paying itself. The $500 billion commitment could become a liability if the AI market cools.
The Broader Pattern: Big Tech’s Self-Funding AI Boom
Nvidia is not alone in this approach. Microsoft, Amazon, and Google have all invested billions in AI startups that use their cloud platforms. The difference is that Nvidia’s investments are more directly tied to its own revenue — the chips are the product, not just a service running on infrastructure.
This pattern suggests the AI boom is increasingly self-referential. Companies are funding the demand for their own products, creating a feedback loop that can amplify growth — and amplify risk.
What Investors and Industry Watchers Should Watch Now
For investors, the key metric is not just Nvidia’s revenue but the health of the labs it funds. Watch for disclosures about which labs are generating independent revenue and which are dependent on continued Nvidia support.
For industry observers, the question is whether this model is sustainable. If the AI market continues to grow, Nvidia’s circular financing will look visionary. If it stalls, the loop could become a liability.
What Could Happen Next
Nvidia’s next earnings calls will likely include more detail on the performance of its backed labs. The company may also face regulatory scrutiny if the circular financing model is seen as distorting market competition.
The $500 billion in commitments suggests Nvidia is planning for years of continued investment. Whether that bet pays off depends on whether the AI labs it funds can become self-sustaining businesses.
Our Take
Nvidia’s circular financing is not inherently problematic — it is how platform companies have always built ecosystems. But the scale here is different. A quarter of revenue from self-funded customers is a concentration risk that deserves scrutiny.
The company’s willingness to acknowledge the term before critics used it suggests confidence. But confidence is not the same as proof. The next few quarters will reveal whether this loop is a virtuous cycle or a house of cards.
Frequently Asked Questions
What is Nvidia’s circular financing model?
Nvidia invests in AI labs, which then use that money or the credit Nvidia’s involvement unlocks to buy Nvidia chips. Those purchases become Nvidia’s revenue, creating a loop where Nvidia funds its own customers.
How much of Nvidia’s revenue comes from backed labs?
CFO Colette Kress said on August 26 that demand from labs Nvidia backs will contribute to roughly a quarter of its business next year.
How much has Nvidia invested in AI labs?
Nvidia has put nearly US$50 billion into AI labs that buy its chips and has lined up commitments for more than $500 billion.
Is circular financing a risk for Nvidia?
It depends on whether the funded labs can become independently profitable. If they can, the model strengthens Nvidia’s ecosystem. If not, the revenue could be seen as Nvidia paying itself.
