Responding to the “$500 billion financing question”! Jensen Huang: Nvidia’s “AI factories” are becoming “investment-grade assets”; real demand exists and it is definitely not “circular financing”

Nvidia CEO Jensen Huang has personally stepped in to endorse the company's plan to mobilize over $500 billion in AI infrastructure financing in partnership with six major financial institutions. He made it clear that Nvidia's AI factory computing power is becoming an investable asset class, with demand stemming from real business scenarios. Independent institutional investors will conduct due diligence on each project separately, dismissing external doubts of "circular financing."

On August 10, Jensen Huang announced on social platform X that Nvidia had reached agreements with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR to jointly establish an independent financing platform, with the aim to mobilize over $500 billion in third-party capital over time to support AI infrastructure construction. He emphasized that the $500 billion refers to the total amount of third-party capital that the above platforms are designed to mobilize, “neither Nvidia’s revenue nor a commitment by a single fund or to a single customer.”

After the announcement, Nvidia’s stock price fell by as much as 3.2%. The price of the 5-year Credit Default Swap (CDS) measuring the company's credit risk rose to 77.215 basis points on Monday, about 5.3 basis points higher than the previous trading day, the largest single-day gain in two weeks. Analysts believe that this reflects the market's growing attention to Nvidia’s potential credit risk amid such massive financing models.

Wallstreetcn article previously reported, quoting sources from the Financial Times, that Nvidia is looking to jointly raise up to $500 billion with Wall Street giants Apollo, Blackstone, BlackRock’s GIP, Brookfield, Goldman Sachs, and KKR as a consortium for AI infrastructure projects, covering AI chip procurement, power production, and data center construction.

Following related reports, "Dr. Doom" Jim Chanos posted a sarcastic comment on Nvidia’s joint AI infrastructure financing with Blackstone and other financial giants, likening it to the financial engineering of the 2008 financial crisis, and implying that if the AI bubble bursts, the parties involved may repeat the fate of Wall Street executives being questioned by Congress at that time.

AI Factory: From "Buying Chips" to "Financeable Infrastructure"

In his post, Jensen Huang systematically explained the asset logic behind Nvidia’s AI factory, seeking to redefine the market’s perception of this business model.

He stated that the AI industry has moved from the era where enterprises purchased chips project by project and built their own data centers to a new stage where AI factories can be financed as productive infrastructure—with replicable platforms, long-term institutional capital support, and a diversified customer base using computing power to generate revenue.

Jensen Huang emphasized that Nvidia's computing power is not merely chips, but a comprehensive AI factory platform that includes accelerated computing, networking, system software, AI frameworks, and a global developer ecosystem.

He pointed out that a single Nvidia AI factory can simultaneously serve multiple customers and workloads, offering flexibility and interchangeability; when the needs of one customer change, the factory can be used by another customer, another cloud provider, or another operator, "This broad ecosystem gives Nvidia’s computing power a vast potential user market, helping to protect residual value."

Huang characterized the above collaboration as "the beginning of open capital markets for AI infrastructure." He stated, these financial institutions are all leading global infrastructure investors with deep expertise in underwriting long-term productive assets; together, both sides will build a replicable financing platform to support the factories needed for the AI ecosystem.

CUDA Software Continues to Appreciate, A100 Still in Commercial Use Six Years On

Jensen Huang focused on the long-term economic value of Nvidia’s computing assets, supported by concrete data.

He explained that CUDA software continues to enhance the performance, efficiency, and total ownership cost of installed infrastructure, allowing AI factories to deliver more intelligence at lower cost throughout their lifecycle, thereby extending their economic value.

Taking the A100 as an example: Nvidia launched the Ampere-based A100 in 2020, and six years later it remains commercially active in AI training, fine-tuning, inference, and high-performance computing, with clients continuing to sign multi-year capacity deals. "The economic life of A100 is extending toward ten years."

On GPU rental pricing, Huang cited market data showing that the H100 one-year rental price has risen from about $1.70 per GPU hour in October 2025 to about $2.35 in March 2026; median cross-provider on-demand pricing increased from about $2.00 per GPU hour in October 2025 to $2.70 in June 2026. The Blackwell series commands an even greater premium, with B200 cloud prices at about $5.30 to $7.05 per GPU hour.

He believes the above data demonstrates the lasting economic value of Nvidia’s computing power.

Direct Response to "Circular Financing" Doubts

Addressing the market’s main concern over "circular financing," Jensen Huang set up a Q&A section in his article to respond directly.

He said the very design of this financing arrangement is intended to address this concern. Demand comes from leading AI labs, AI-native startups, enterprise customers, cloud providers, and countries building AI services—“the demand is real.” Each capital provider will independently conduct due diligence on every project, evaluating client credentials, demand, utilization, cash flow, and residual value. "Nvidia provides the platform, and investors make independent financing decisions."

Regarding Nvidia’s own risk exposure, Huang revealed that in some cases, Nvidia may provide up to 25% residual value support for a single project, "prudently assessed project-by-project." He emphasized this ratio is “far lower than other computing power financing arrangements” and is supplemental rather than a substitute for independent due diligence.

Jensen Huang concluded by placing the construction of AI factories in a broader historical context. He stated that every industrial revolution has been built on infrastructure—electricity, transportation, communications, and computing—and each phase has relied on external financing. "AI factories are the infrastructure of the intelligent era."

He summarized the business logic of AI as a positive feedback loop: Companies use AI to write software, develop drugs, design products, serve customers, automate operations, and build new services; more computing power brings better AI, better AI leads to more usage, more usage brings more revenue, and more revenue drives further investment into computing power.

"This is the virtuous cycle of the AI industrial revolution."

Jensen Huang stated that through this collaboration, Nvidia and the world's leading financial institutions will jointly provide infrastructure financing for this industrial revolution, making AI factories more accessible to businesses, industries, and nations.

Wallstreetcn article also noted that this cooperation is not Nvidia’s first deep involvement in AI industry chain financing.

Previous reports indicated that Nvidia was in talks to provide up to $25 billion in credit guarantees for OpenAI and was discussing financing $350 billion for OpenAI’s chip procurement plan; last month Nvidia also announced an expanded partnership with South Korea’s SK Group, with total business volume expected to exceed $500 billion. These moves show that Nvidia is gradually transitioning from a chip supplier to the capital mobilization core of the AI infrastructure ecosystem.

"Dr. Doom" Draws Parallels to 2008: Next Congressional Hearing?

Simultaneously with Huang’s post, Wall Street’s famous short seller, also known as “Dr. Doom,” James Chanos, shared a thought-provoking comment on social media. He wrote:

“These guys’ next time sitting at the same table explaining AI financing could well be at a Congressional hearing in 2031…”

Chanos’s implication references the 2008 financial crisis—at the time, executives from major Wall Street financial institutions were forced to attend Congressional hearings due to the systemic risks posed by subprime mortgages, credit default swaps, and CDOs. He compared Nvidia’s joint financing arrangement with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR to those financial engineering operations, suggesting that if the AI infrastructure investment bubble pops in a few years, Jensen Huang and these financial executives may together face Congressional inquiries.

Notably, when someone in the comments below his post asked if the parties involved would face criminal charges, Chanos clarified: “No one said anything about going to jail.”