Jensen Huang On NVIDIA Stock After NVIDIA Earnings - NVDA Update
📅 May 21, 2026FinVid29 MIN4626 VIEWS29 SEGMENTS · 3 SPEAKERS
Jensen Huang On NVIDIA Stock After NVIDIA Earnings - NVDA Update
NVIDIA CEO Jensen Huang discusses NVIDIA, NVIDIA stock (NVDA stock), hyperscalers, datacenters in space, agentic AI, and much more following NVIDIA earnings. We learned many important details from the NVIDIA earnings report, CFO commentary, and NVIDIA earnings call. NVIDIA leadership told us that Vera CPUs open up a $200 TAM for NVIDIA, and they see $20 billion in standalone CPU revenue this year. Rental prices for NVIDIA H100 are up 20% YTD, and rental prices for NVIDIA A100 are up nearly 15% YTD. Production shipments of Vera R...
What Jensen Huang said
Written from the verified transcript and checked against it. Every figure links to the moment it was said.
Jensen Huang said AI has shifted from generative to agentic AI, where models can reason, plan, and use tools, making compute directly tied to revenue. He said Nvidia is gaining share in hyperscalers, including winning Anthropic as a customer, and that the non-hyperscaler segment (sovereign, enterprise, AI clouds) is half of the business and growing faster. On competition, he dismissed threats, saying many chip announcements get delayed or canceled. He confirmed Vera Rubin ships in Q3, is in full production with seven chips, and is designed for agents, with every frontier AI model company and hyperscaler ready to launch. He said supply chain is the largest in the world and planned for years, with no physical limits to scaling data centers in space, though most will remain terrestrial for a decade. On China, he said he expects nothing and has guided investors to expect nothing, noting Huawei is strong and Nvidia has largely conceded that market. He defended the $80 billion buyback, saying Nvidia generates enough cash to invest in the five-layer AI ecosystem. He called the stock's underperformance a mystery, arguing competition concerns are overblown and compute equals revenue.
Key takeaways
Vera Rubin is in full production with seven chips and ships in Q3, designed for agentic AI, with every frontier AI model company and hyperscaler ready to launch.
Nvidia is gaining share in hyperscalers and inference, including winning Anthropic as a customer, and the non-hyperscaler segment is half of business and fastest growing.
On China, Huang said he expects nothing and has guided investors to expect nothing, noting Huawei is strong and Nvidia has largely conceded that market.
Huang said Nvidia's supply chain is the largest in the world and planned for years, with no physical limits to scaling data centers in space.
Huang defended the $80 billion buyback, saying Nvidia generates enough cash to invest in the five-layer AI ecosystem and return capital.
The biggest thing that's happening is that AI has moved from generative AI to agentic AI. What that means is that an AI can now understand, reason about the question you give it, the task you give it, and it could plan and do work, use tools like a browser or a spreadsheet or PowerPoint or using simulators and C compilers. It could write code, generate code. So it could do work. So finally AI is not just interesting but it is doing productive work that's valuable. Now the important thing is as a result the AI model builders are now generating tokens which is basically what an AI is. It produces these tokens. These tokens are now profitable and so they want more compute so that they could generate more tokens for more revenues. In the AI era compute is revenues which is the reason why our demand for our compute is so sky-high.
Yeah, it was interesting that you guys for the first time broke down the data center revenue by hyperscalers and then some of the other categories like sovereign and other cloud AI. The hyperscaler number that's about what 50% of the data center revenues there. There have been questions about how sustainable the growth is there given just whether these incredible capex numbers can continue from the hyperscalers and also the increasing competition from AMD and others. What do you say to those concerns?
The hyperscalers is where the AI frontier models are. And we're gaining share there. We're gaining share there because we've already always supported OpenAI and xAI and Meta and Microsoft's AI and a whole bunch of other AI startups. But this year, we had the benefit of also winning Anthropic. We're helping them scale capacity so that they could have more reach, generate more revenues and grow their company. And so with Anthropic, we're scaling very very quickly. We've got big plans for them. And so we're gaining share in AI inference. We're gaining share in hyperscale. The second category is a category that you really have to have a complete solution including CPUs and GPUs and networking and switches and data processing and security processing and the whole software stack which Nvidia is quite unique in having. And so the second category whether it's industrial on-prem with manufacturing or enterprise on-premise, AI native clouds, the CoreWeaves, the NBS's, NScale, so many others, and of course the sovereign AI nations where they want to have their own governance and they want to build themselves all of these different data centers. In the second category, Nvidia is fairly unique in being able to serve and that represents half of our business and it's also the fastest growing.
I was going to say it's growing a lot faster even than the hyperscaler business. But on that there are also questions lately Jensen about whether these hyperscaler customers which are so critical are also becoming competitors. You know Andy Jassy of Amazon talked on the last call about their chip business which he said if it was a standalone would be worth $50 billion a year and sort of hinted that they'd be selling maybe open to selling chips externally. So is this a threat to your dominance if they start doing it themselves?
We have a lot of competition but as you know we're very good at this and so just because a competitor emerges, the path, the journey from announcing a chip to eventually building a sustainable business is a long journey and so we continue to serve all of our hyperscale clouds and they have projects internally. Many of the projects are delayed and many projects are canceled and some of them are sustained and so I think a lot of it is quite noisy. We don't let it distract us. We only focus on supporting our hyperscale partners, helping the AI model builders grow and as I mentioned, while competition and the number of announcements is growing, our overall share is growing and growing quite fast and so we're doing very well.
You're also very bullish obviously about the Vera Rubin launch and you confirmed shipping in Q3. Can you just tell us a little bit about how that's going to change the business overall and what the pipeline looks like?
The thing that's really great about Vera Rubin is that it's designed in the same systems architecture as Grace Blackwell. So it's easy for our customers to integrate and adopt. The second thing is whereas Grace Blackwell was designed for inference, Vera Rubin was designed to run the entire pipeline, the entire processing stack of an agent. Everything from the orchestration of the agent which usually runs on CPUs to the inference, the thinking part of the agent which runs on GPUs or the tool use that runs on GPUs and CPUs. So the combination that entire pipeline end to end from short-term memory that runs on CPUs and GPUs to long-term memory that runs on storage, Nvidia has an architecture for every aspect of the agent pipeline. And so whereas Grace Blackwell was for inference, Vera Rubin is for agents. Vera Rubin is in full production, seven different chips. It's the most complex computing system the world's ever made. We're going to be very successful with it. Whereas Grace Blackwell, we didn't have the benefit of every frontier AI model supporting it at the get-go. In the case of Vera Rubin, every one of the frontier AI model companies, every one of the hyperscalers, literally every single data center customer in the world is already fully geared up to launch with Vera Rubin. So, it's going to be an exciting launch.
What is the barrier to getting this going smoothly? Is the memory shortage impacting you at all when it comes to launching this or even when it comes to thinking about your next innovation?
Well, as you know, Nvidia is a very large company. So, our supply chain is literally the largest in the world and we've been planning this for several years. You know, we started planning with the Hopper generation and got more than twice as large with Grace Blackwell and it's going to get more than twice as large with Vera Rubin. And so we've been planning our supply chain for quite some time. And I think it's fair to say that everything is challenging at the scale that we're working. You know, there's nothing easy about the work that we do. Everything from the copper backplane of our Vera Rubin that we partner with Amphenol to do this is incredibly complicated copper scale-up system to silicon photonics to HBM memories and LPDDR memories and CoWoS of three different types, there's CoWoS S, CoWoS R, CoWoS L, the amount of technology that's integrated in Vera Rubin I could go on and on but it's just kind of mind-blowing, kind of staggering. But that's what we're good at. We are the largest single company in the world focused in building this and we have every single company as a customer. And so, we have a lot of responsibility to really lift the entire AI ecosystem in the coming months.
So, do you feel good about the supply chain? But Jensen, do you feel good about the margins, the 75% margins and the ability to hold those in an environment where costs are going up?
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