Dan Ives’s bullish view of Nvidia rests on a distinction: he saw the stock’s weakness as a reaction to worries about financing the AI buildout, not proof that demand for Nvidia’s chips had faded. He kept an Outperform rating and a $300 price target, while describing Nvidia as central to the AI boom.
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7 That is an investment thesis, not a resolution of the credit risks facing the companies building AI infrastructure.
Why Ives saw a pullback as an opportunity
The growth outlook remained strong. Nvidia projected roughly 70% revenue growth for fiscal 2028, while warning that memory-component shortages could limit how quickly it expands.
33 In other words, the company’s outlook pointed to supply as a constraint on growth—not weak demand. That helped support Ives’s argument that a share-price decline did not necessarily mean the business outlook had deteriorated.
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Recent results gave the growth case a concrete foundation. Nvidia reported second-quarter fiscal 2027 revenue of $96.2 billion, up 106% year over year, including $89 billion in data-center revenue, up 117%.
30 These are reported results, distinct from the company’s forward-looking fiscal 2028 outlook.
Large deployment plans offered another sign of demand. Nvidia and Amazon Web Services announced plans to deploy two million additional Nvidia GPUs across AWS infrastructure in 2027 and 2028.
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37 The plan indicates intended future deployment; it does not establish that every GPU has already been installed or that all future capacity will be used profitably.
Ives’s thesis extended beyond chips alone. Coverage of his call pointed to Nvidia’s full-stack hardware and software advantages, framing its position in terms of the broader architecture used to build and operate AI infrastructure.
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8 But the available reporting does not establish the details of a separate argument about CUDA code-rewriting costs, or document a specific shift in his thesis from AI training toward reasoning, agents and robotics. Those details should not be treated as confirmed elements of his October 16 case.
Ives also described the AI investment cycle as being in its “third inning,” signaling his view that the opportunity had room to develop further.
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The financing caveat: demand is not the same as financial resilience
Financing was part of the debate, not a side issue. Bloomberg’s coverage of Ives’s October 16 appearance said he discussed CoreWeave, Nvidia’s cost of capital and credit markets.
2 Other coverage summarized his view that CoreWeave’s pressure could be a buying opportunity because of demand and backlog.
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That bullish argument does not, by itself, show that every AI infrastructure customer can fund construction, manage borrowing costs or earn an attractive return on new computing capacity. Reporting also put Nvidia’s $6.3 billion CoreWeave capacity commitment at the center of the financing discussion.
9 The available sources do not establish the specific figures raised in the question about CoreWeave’s debt and lease obligations, bond yields, Nvidia’s equity stake or the exact terms for purchasing unsold capacity. They therefore do not allow a firm conclusion about how Ives weighed those individual exposures.
What the evidence can—and cannot—confirm
The sources support the broad account: Ives maintained a bullish Nvidia rating and $300 target, pointed to a strong growth outlook and supply-constrained chip demand, and addressed concerns about credit and AI infrastructure financing.
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33 They do not consistently verify the precise claim that Nvidia fell roughly 5% over two sessions, so that figure should be treated cautiously.
The central tension is straightforward: Nvidia’s reported growth, its forward outlook and planned customer deployments bolster the demand case.
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37 But they do not settle the separate question of whether the financing behind the wider AI buildout is sustainable. Ives’s view was that the pullback created an opportunity despite those concerns—not that the concerns had gone away.