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By the end of July, the chipmaker Nvidia’s equity value in both listed and unlisted companies had reached $95.6 billion, while the figure at the start of 2020 was less than $100 million. Nvidia said its total equity investments are currently about $99 billion.① Nvidia made its fortune riding the AI boom, and now it is also “stepping in the middle” to help the next phase of that wave develop… ② Compared with the impressive profit statement figures unveiled on Wednesday, some industry insiders believe Nvidia’s bigger change may be showing up on its balance sheet. Faced with such astonishing capital expansion, Nvidia CEO Jensen Huang showed no sign of concern on Wednesday—instead, he seemed calm: “If I have any regrets, it’s that at the time we didn’t invest more, and earlier, in these AI labs.” And perhaps these massive equity investments are only the tip of the iceberg in Nvidia’s broader capital chess game… $Nvidia (NVDA.US)$ Chief Financial Officer Colette Kress said that frontier AI labs’ demand for computing power is growing “explosively,” but its “expansion speed has far outstripped the limits that their own balance sheets and creditworthiness can support.” Put simply, the fastest-growing Nvidia’s core customers urgently need large-scale AI infrastructure, but their own financial conditions are simply unable to foot such expensive bills. And Nvidia is filling that gap. This capital-support strategy is gradually becoming an increasingly important part of Nvidia’s core business. Kress revealed that by next year, those AI labs supported by Nvidia’s balance sheet backing are expected to contribute about one-quarter of the company’s business share. In recent months, as the “Balance-Sheet-as-a-Service” model has taken off, Wall Street investors have begun to frequently jokingly call Nvidia the “central bank for AI.” The “Balance-Sheet-as-a-Service” model led by Nvidia—using Nvidia’s strong financial backing to continuously “pump blood” into customers so they can maintain their high procurement spending—has even given rise to a rare practice in the industry: allowing some large customers to delay payment for data center procurement for up to a year. According to the results released on Wednesday, $Nvidia (NVDA.US)$ accounts receivable (customer unpaid amounts) jumped to $63.1 billion, and the average days sales outstanding also extended from the prior 45 days to 60 days. Not only that, Nvidia is also “guarding the road” for customers in a more direct way. For some AI cloud service providers, Nvidia sets a minimum revenue guarantee to help them obtain financing smoothly; once a customer’s actual revenue exceeds that threshold, Nvidia can take a share of the upside. “Under this model, we are not just making loans,” we candidly acknowledge. “Under this model we can earn a double return: not only profit from front-end hardware sales, but also share in the returns from leasing income.” Nvidia’s $Nvidia (NVDA.US)$ results on Wednesday also disclosed guarantee facilities as high as $108.5 billion. The vast majority—$105 billion—is closely tied to the construction projects of the SB Energy data centers built for OpenAI. A clarification is needed: this massive amount of money is not cash that Nvidia needs to directly pay out right now. As nine data centers are scheduled to come online around fiscal year 2029, the guarantee obligation will take effect in stages and decline correspondingly as OpenAI gradually settles its outstanding payments. At the same time, $Nvidia (NVDA.US)$ is actively guiding more external capital to be injected into this construction boom. The company said it has already reached preliminary agreements with multiple large investment institutions, with the intention of raising more than $500 billion of social capital to flow into AI infrastructure construction. Its logic is simple: Nvidia does not want to shoulder all the costs of the boom by itself; instead, it wants to help these projects obtain financing more easily. This aligns with Nvidia’s view of AI infrastructure as an “investable asset class.” The strategy also follows a trend the company showed signs of in the previous quarter: at that time, Nvidia’s massive “cash-generating engine” was already injecting capital into both sides of AI trading—supply and demand. Now, major tech giants are also increasingly relying on debt financing to keep their AI mega-construction plans afloat. In any case, Nvidia’s current portfolio size is already large enough to affect its profits, and its balance sheet itself is also evolving into an indispensable underlying pillar for AI infrastructure. Investing regularly in $Nvidia (NVDA.US)$ stock is a very good strategy. Come on!$NVDAB

With OpenAI and other tech giants rolling out their own chips, analysts have begun to believe that $NVIDIA (NVDA.US)$'s near-monopoly position in the advanced AI chip arena is facing a “threat.”
On Tuesday (August 25), OpenAI disclosed technical details of the company’s first custom inference chip, Jalapeno, claiming that the chip’s response speed and energy efficiency performance have surpassed NVIDIA’s GB300. At present, $Google-C (GOOG.US)$, $Amazon (AMZN.US)$, $Meta Platforms (META.US)$, and others are also developing their own AI chips.
Yole Group technology analyst Adrien Sanchez said Jalapeno is a chip designed specifically for inference, indicating that “chips designed by ultra-large cloud service providers (hyperscalers) can now match—and even exceed—NVIDIA Blackwell-class GPUs in inference energy efficiency.”