Gurley argues cloud GPU hosting is a commodity service, making credit-based investments questionable.
“Here's another here's a way to really drill in on that, you know, going back to Ultra Hosting Company. Let's assume for the sake of this discussion that the service being provided is a commodity.”
Gurley calls the Altman-Masa plan to compete with Nvidia radical given AMD and others have decades head start.
“There are already people competing with Nvidia. AMD's competing with Like, there are other people that have somewhat of a head start. Like decades.”
Gurley says new chip startups face impossible barriers competing with Nvidia for TSMC capacity and achieving good yields.
“How are you going to out compete Nvidia for TSMC's time? Right. Like, how are you going get on that place? And it's hard, you know?”
Gurley calls plans to compete with Nvidia radical given existing competitors like AMD already have decades-long head starts.
“There are already people competing with Nvidia. AMD's competing with Like, there are other people that have somewhat of a head start.”
Gurley reports Nvidia alone accounts for 5% of S&P 500 returns while 493 other companies contribute only 4%.
“The other mag six are responsible for 5%. And then the other 493 companies in the S and P 500 are responsible for 4% of the 14% year to date returns.”
Gurley explains single NVIDIA nodes sell at or below cost because large systems unlock capabilities impossible with single nodes.
“And this starts to get at that because you can do things with the large systems that you just can't do with a single node.”
Gurley explains NVIDIA's networking, NVLink, and CUDA advantages emerge specifically in the largest system deployments.
“That's when the networking piece thrives. That's where NVLink thrives. That's where CUDA really comes alive in the biggest systems that are out there.”
Gurley argues NVIDIA's competitive advantage is strongest in the largest systems, not at the edge.
“it appears to me that NVIDIA's competitive advantage is strongest where the size of the system is largest, which is another way of saying what Renee said. It's flipping it on its head.”
Gurley realizes NVIDIA needs multiple large system companies like CoreWeave to maximize its competitive advantage.
“Like like like if if the biggest systems are where the biggest competitive advantage is, you need as many of these big system companies as you can possibly have.”
Gurley argues NVIDIA's moat is misunderstood as people think a better chip alone could win against it.
“I think there's a notion out there that as soon as someone invents a new chip, a better chip, that they've won.”
Gurley observes Elon Musk obtained roughly 10% of NVIDIA's quarterly availability for x.ai despite massive demand.
“And he walks in and takes what equate sounds looks like about 10% of the quarter's availability.”
Gurley says analysts miss NVIDIA's ecosystem thinking and multi-year planning beyond current architecture.
“I think analysts always focus on the current architectural bet. But I think one of the biggest takeaways from this conversation is that we're thinking about the entire ecosystem and many years out.”
Gurley argues NVIDIA's scaling strategy prepares for distributed training future, not just dependence on million GPU clusters.
“It's not such that you're only dependent on a world where there's a 500,000 or a million GPU cluster. It's by the time there's distributed training, you'll have written the software to enable that.”
Gurley explains NVIDIA's moat comes from a decade building full stack including GPU, CPU, networking, and especially software.
“But the truth is you've been spending the past decade building the full stack from the GPU to the CPU to the networking, and especially the software and libraries that enable applications to run on NVIDIA.”
Gurley argues NVIDIA's moat is misunderstood because it spans the full stack, not just chips.
“one of the most misunderstood things about NVIDIA is how deep the true NVIDIA moat is, right?”
Gurley argues NVIDIA's competitive advantage is strongest in the largest system deployments, not at the edge.
“NVIDIA's competitive advantage is strongest where the size of the system is largest, which is another way of saying what Renee said.”
Gurley says NVIDIA differentiation is greatest at largest cluster size for LLM pre-training.
“One, the NVIDIA differentiation as we've talked about is greatest at the largest cluster size. So if pre training, once again, I only equate this to LLMs, you know, I don't think of FSD problem.”
Gurley states NVIDIA holds 98% of purchased AI workloads when captive workloads are excluded.
“If you just look at, I guess, workloads people are purchasing to do work on their own, so you take the captives out, you're at 98, right?”
Gurley warns NVIDIA bulls defending the company against DeepSeek may trigger sanctions that hurt NVIDIA's revenues.
“So you're an NVIDIA bull think you're protecting NVIDIA by exposing DeepSeek, and you may end up with sanctions that end up hurting NVIDIA's revenues.”
Gurley reports NVIDIA promised to buy any unsold CoreWeave capacity, calling this commitment unusual and debt-enabling.
“That is very unusual. That's not the same as making an investment. That could easily help CoreWeave with their debtors and and getting more debt financing.”
Gurley reveals NVIDIA promised to buy any CoreWeave service availability they cannot sell to others.
“One of the more peculiar of all the deals is, and this was disclosed in a CoreWeave filing, was NVIDIA has promised to buy any of CoreWeave's service availability that they can't sell to anyone else. That is very unusual. That's not the same as making an investment.”
Gurley questions Nvidia's contract guaranteeing to buy CoreWeave's excess capacity as abnormal business practice.
“But then they wrote a contract with CoreWeave, which said if CoreWeave ever has extra capacity, we'll buy that capacity, which presumably helps it get more debt financing, that kind of thing.”
Gurley argues circular deals explain why Nvidia's multiple won't go higher despite strong growth.
“People wanna understand why the Nvidia multiple won't go higher. I think it's the circular deals. Like if they're not material, don't do them.”
Gurley cites rumors of thirty billion dollar Nvidia investment into OpenAI, calls modern venture capital sport of kings.
“And so, there's rumors today of a $30,000,000,000 investment from Nvidia into OpenAi on top of everything they've already already raised and spent.”
Gurley mentions rumors of a thirty billion dollar investment from Nvidia into OpenAI and calls it a sport of kings.
“And so, there's rumors today of a $30,000,000,000 investment from Nvidia into OpenAi on top of everything they've already already raised and spent. So it it I I call it a sport of kings,”
Gurley cites rumors of thirty billion dollar Nvidia investment into OpenAI, calling it sport of kings venture capital.
“there's rumors today of a $30,000,000,000 investment from Nvidia into OpenAi on top of everything they've already already raised and spent.”
Gurley argues open models are inevitable in high-stakes software competition, reacting to NVIDIA-Hugging Face acquisition talks at $13B valuation
“Open, open, open. As I wrote in the @washingtonpost, open-models are the inevitable outcome of high stakes software competition. The more at stake - the more likely open wins. This is water running downhill. https://t.co/6x5qoLbw0k https://t.co/wAH0xjej7q”