March 18, 2026
WHEN: Today, Tuesday, March 17, 2026
WHERE: CNBC’s “Mad Money”
Following is the unofficial transcript of a CNBC exclusive interview with Nvidia Founder & CEO Jensen Huang on CNBC’s “Mad Money” (M-F, 6PM-7PM ET) today, Tuesday, March 17.
All references must be sourced to CNBC.
PART I
JIM CRAMER: Earlier today I got the chance to sit down with our host at GTC for the past couple of days. That's Jensen Huang, the renaissance man, founder, president and CEO of Nvidia. Take a look.
First, Jensen, I want to thank you. I have been with a number of people over the last six months whom you made, your company made millionaires. I have never seen it happen in 42 years on Wall Street. So thank you.
JENSEN HUANG: Thank you. Well, that's what -- that's why we do all this for, make a small difference in people's lives.
CRAMER: There are a lot of people who feel that your stock is tapped out, the institutions own all that they could possibly have. I think they have to look at it differently. I think your stock represents incredible value, and individuals understand that and a whole other cohort of mutual funds understand that. Yesterday, you presented things that would make it so it could be a level of growth that we have never seen. And yet your stock's a value stock. Have you thought about that?
HUANG: Well, we're a very large company, and yet we are accelerating growth at the scale that we currently are. And I think that's part of the story that a lot of people don't understand. It's probably difficult to understand how a company as large as we are could actually be accelerating growth. But the reason for that is, we're opening up so many new opportunities. We used to start out at the hyperscalers, but now we have expanded well beyond the hyperscalers. The number of new companies that we're working with, new countries we're working with just -- just really, really growing fast. And so we're accelerating our growth.
CRAMER: But -- and there's a lost narrative. And the narrative is this. There are a couple of companies that control your business. There's a Google and there's Amazon, there's Microsoft. They are spending a fortune and they're making nothing. Aren't you the principal reason why people even go to them?
HUANG: You know, we are, they're not just our customers. We are their market partners. We bring customers to them. And the reason for that is because, if you come to this conference, GTC, they're, all of these industries that built on top of CUDA. We integrate CUDA into their clouds, and then we get developers that come to their clouds to consume the computing. So they -- they're all here. AWS is here. Google Cloud is here. Azure is here. OCI is here. CoreWeave is here. And they're having a great time because we're bringing customers to them. And so that's number one. I think number two is that we're expanding beyond the hyperscalers. There's a -- there are many parts of the market that we could address that it's very difficult for other companies to address, because a lot of computing is on-prem, for example.
CRAMER: On premise, absolutely.
HUANG: All the work that we do with Dell, and Dell is growing incredibly, they have a huge pipeline ahead of them. HP is doing incredibly. They have got a huge pipeline ahead of them. I spoke with Lenovo yesterday. They have got a huge pipeline ahead of them. And all of that, all of those on-prem opportunities, people are still building data centers. They're building it around the world. They're building it in their companies. Those are very difficult to address for hyperscalers.
CRAMER: Well, also what I'm hearing is not really a semiconductor company. It's a company that is a platform with software, loaded with software. And if you decide that all this company is, is the four walls of a piece of metal, you're missing what is going to make it so we will put a man on the moon, a woman on Mars. A self-driving car will be able to drive on black ice, that we will see robots that take the place of the things that we don't want to do. These are not what people should -- they don't understand that. That's what you're talking about.
HUANG: We -- you know, we invented this chip called the GPU. It is so revolutionary. People forget that we're growing well beyond that. And so Nvidia is today really an A.I. infrastructure company. We built all the technology inside an A.I. factory, everything from GPUs, of course, networking switches and CPUs. And we optimize across the entire stack of software and chips and systems. And we have ecosystem partners that span $100 trillion. And so the company has really grown well past the GPU. We're very proud of the GPU, of course.
CRAMER: Sure.
HUANG: And we build the world's best GPUs. But the company is much, much larger than that.
CRAMER: Well, one of the things that I found myself thinking about was when we first met. It was like 10 years ago. You had been on TV with us before, but you talked about one day we'd have an agent, and I didn't understand it. But it turned out to be like Harvey the rabbit. It's right there, and it's going to make us so much smarter. And people think, well, sure, 10 years, I will love it. Maybe I get one in eight months.
HUANG: You get one sooner.
CRAMER: Really?
HUANG: I think -- well, the idea of agent, an agent is someone who is able to reason and act autonomously, has agency. There are two types of agents.
CRAMER: Has agency.
HUANG: That's right. There's two types of agents. There's one that is physical. It looks like a robot.
CRAMER: Right.
HUANG: And we recognize that as something that has agency. It can move by itself. It can understand us. It can reason, perform tasks. There's a digital version of that. And that digital version of that could do things like help me optimize my chip design, help me write software, help me plan a trip, help me, et cetera, et cetera, and organize my day. And so that agent is extremely useful. We use that kind of agent in our company across the board, software agents for software coding. They have made our software engineers incredibly productive. And those are agents. We're going to see agents in every single part of every single company. And it's going to help us become a lot more productive.
CRAMER: Well, I have deliberately kept all my questions so far to the outside of trillion dollars. Everything you talked about is not covered by the trillion.
HUANG: That's right.
CRAMER: Because I think people were, let's say, kind of what have you done for me lately about that. But everything we talked about is going to be in the numbers, perhaps even in the next 18 months. And those who were selling calls and selling puts and making a little bit of money with the stock at 183 are missing the big picture. I know they are the Lilliputians in the equation. There is something much bigger going on. Why do you think the individual sees the bigger and not the institution?
HUANG: Well, because they don't see all the things that we're inventing all the time. When I talked about the trillion dollars, I wanted to give people a reference to last year. This is our Blackwell plus Vera Rubin. And, of course, the purchase orders and the forecast that we have are the things that are in production today. A lot of the things that we're talking about here are going into production soon. And so these are going to be on top of and new and beyond. We're inventing things all the time. All of the self-driving car announcements that we just made, all the robotics announcements we made, the agent announcements that we made, all the new systems that are being introduced here are not in production and already counted in those numbers. They're going into production. And so we still have 21 months to the end of 2027. Oh, my gosh, there's a lot of new businesses that we're going to book and a lot of new businesses that we're going to expand our growth beyond a trillion.
CRAMER: Yesterday, I was with Rene Haas.
HUANG: Yes.
CRAMER: It does sound like that you're going to also not dominate, because you don't want to -- you're a friend. You're not trying to crush anybody. But the CPU business could make you a lot of money, again, not in the trillion.
HUANG: Data processing is going to go through a whole new reset, a whole new reinvention. And the reason for that is because these agents use data processing at a speed that no humans can. And so we're going to access corporate data, enterprise data a lot faster. And we need a new type of processor to do that. And so we invented a new type of CPU we call Vera CPU that's designed for CPU of the A.I. era, if you will.
CRAMER: OK.
HUANG: Yes.
CRAMER: Well, I also—
HUANG: Brand-new type of CPU. It's going to grow the industry. It's going to be good.
CRAMER: I heard one of the things that that could be involved with that, one of the things that, geez, didn't people realize that you came up with a chip that was faster, better and certainly more useful than -- when it came to inference, than other companies that are so proud of their inference chip? No need to knock anyone. I mean, you’ve got customers that do a great job. But your inference chip with combined Vera Rubin is much cheaper, cheaper by token, cheaper -- but total cost of ownership. I mean, look, I don't mean to be a salesperson for it, but wasn't your inference gambit much better than what's out there now?
HUANG: The thing I wanted to teach the world to recognize, and it's a very important idea, the cost of the system for computing and the cost of the token it generates are unrelated.
It is very, very possible that the most expensive system, the ones that we make, generate the lowest-cost tokens because it's so efficient. It's so performant. And it generates so many more tokens per second, intelligence per second, than any other system. The token cost is the lowest. And so people have to think about the efficiency of their factories, the performance of their factory, and make sure that the output is what they consider. You have to take, in order to calculate cost, its output divided by input, and so—
CRAMER: But you know who gets it? Zuckerberg.
HUANG: Yes.
CRAMER: He's not here, but he's the one.
HUANG: Yes.
CRAMER: It's very clear. It's the force multiplier. He gets it. I wish he could come out and say it, but why should he? All it does is make it so everybody else figures it out.
HUANG: Well, last year, we were very, very fortunate to add new A.I. companies to all the A.I. companies we have been working on. And so one of the ones that we added, of course, is Meta superintelligence labs.
CRAMER: Right.
HUANG: And they're all in on A.I. It's really terrific. Another one that we added that we're really proud of, it's Anthropic. And so Anthropic is a—
CRAMER: Well, I was going go there next. Darn it.
HUANG: Yes.
CRAMER: We, can we go to Anthropic in the next segment?
HUANG: Sure.
CRAMER: Because they may be where we're really headed. I want to have more with Jensen Huang. He's the co-founder and CEO of Nvidia in one moment.
PART II
CRAMER: Before the break, you saw the first part of my interview with Jensen Huang, the founder, president and CEO of Nvidia. But since this is the largest company on Earth, they almost single-handedly orchestrated the entire A.I. revolution. You better believe that conversation ran long.
So take a look at the final part of our discussion.
Jensen.
HUANG: Jim.
CRAMER: People who are born in the next five years, could they live to 100 because of Nvidia?
HUANG: Absolutely. There's no question that science is going to help us live longer.
CRAMER: And Nvidia is the power of science.
HUANG: And, yes, I think it's -- I really can't wait. I really can't wait.
CRAMER: Now, who will determine what they do with you to make us get to 100? Will it be Anthropic? Will it be Eli Lilly? Who's going to work on that?
HUANG: Both.
CRAMER: Good.
HUANG: Yes, both. The work that we do with Eli Lilly is, well, I call them Lilly. What we have done is we have set up a co-innovation lab, a research lab, where their scientists and our scientists get together. And they're working on digital biology, how to advance the discovery of new drugs. And the large language models, the A.I. models used for digital biology, understands biology, not just language. And so that work is very, very different. The work that we do with Anthropic, we're just so happy that last year that they decided to adopt Nvidia's architecture as well. So this is a -- it gives us an opportunity to really boost their output and boost their compute. Their demand is so high, they need compute capacity like crazy. As you know, in the old world of computing, the computer was used to store files and interact with drag-down menus and things like that. But, today, the computers are a factory of tokens. And these computers generate revenues. It generates growth for companies like Anthropic and OpenAI. And so I'm really delighted that we're able to serve Anthropic as well and really increase their output.
CRAMER: We're kind of trapped here. We think, what is Google going to do? Well, they're going to, they have got a TPU. We have got Trainium at Amazon. But no one's talking about the possibility that OpenAI and Anthropic could be your largest customers a few years from now.
HUANG: Yes, no doubt. First of all, we have a great partnership with Google. We bring lots of customers to Google. And they're working on Vera Rubin right now as we speak. And they're going to be one of the first to get to market with Vera Rubin. We have great engineering and technical and marketing relationships with them. We bring lots of customers to them. The thing that people don't realize, Nvidia's architecture is the only architecture in the world that supports confidential computing, which means companies like OpenAI and Anthropic could take their really their valuable models completely protected inside our computer, so that even the people who operate the computer can't see their models. Even the people that operate the computer can't see the models. That says they could run their models anywhere. They could run it across all the clouds. So OpenAI is in Azure today. They could be, they were in CoreWeave. They're in OCI. They're going to go to Amazon on top of Nvidia's architecture. Anthropic could run across AWS, but now Anthropic is going to run in Microsoft and other places. And so our architecture with confidential computing is really a game changer for us.
CRAMER: Well, another game changer that we didn't talk enough OpenClaw. I mean, OpenClaw is something that sounds like a force multiplier bigger than we have ever had.
HUANG: It was open-sourced just recently, a few weeks ago. It is now the largest, most popular, the most successful open-sourced project in the history of humanity.
CRAMER: Well, this is like ChatGPT when you told me in November it would be big, and then it turned out to be in January the thing.
HUANG: Huge.
CRAMER: This could be the next thing.
HUANG: This is definitely the next ChatGPT.
CRAMER: Well, then why the hell aren't people talking? I'm saying, why aren't people talking about it?
HUANG: Well, there are phenomenons of OpenClaw all over the world as we speak.
CRAMER: So tell people how you use it. You used it to say, I'm going to ChatGPT it—
HUANG: In one line of code, you could get yourself -- I would get a small computer. We have one that's called DGX Spark. You could also set it up in the cloud. In one line of code, you could create for yourself your own agent. And you could then, after that, just ask the agent to do whatever you wanted to ask it.
CRAMER: Can the agent be a lot smarter than us?
HUANG: We're still quite smart.
CRAMER: Well, can we ask the agent to build us a heart, so that we don't have to have human transplants? It can build us a heart that is artificial so that we get away from the idea—
HUANG: I would have it do all kinds of mundane stuff first.
CRAMER: OK.
HUANG: Like, for example, design me a kitchen.
CRAMER: OK.
HUANG: Here's a picture of my current kitchen. Here's a picture of a kitchen I would love to have. Now, I would like you to go off and design that kitchen and select furniture to put in it. It'll go off and learn how to design a kitchen, use 3-D tools, and actually read manuals. You can just see, watch it, reading manuals, trying new things, and then it'll come back with a design. And it'll reflect on it. It'll say, hey, this design that I came up with isn't as good as the one that you showed me a picture of. Let me try again.
CRAMER: Well, OK, so let's deal with the company that's laying people off—
HUANG: Every carpenter could now be an architect. Every plumber will become an architect. We're going to elevate the capability of every—
CRAMER: Well, then why are companies laying off people, saying that, you know what, Nvidia is giving us the opportunity to do more with less? Why not do more with more?
HUANG: Because you're out of imagination. For companies with imagination, you will do more with less.
CRAMER: Yes. Yes.
HUANG: For companies that are, when the leadership just out of ideas, they have nothing else to do, they have no reason to imagine greater than they are, then, when they have more capability, they don't do more.
CRAMER: Now, to go -- let's follow up on imagination because that's really at the heart of things.
HUANG: We have -- I have so many things to do. If I could just have—
CRAMER: Well, don't I have to learn how to talk to the agent to be able to get the -- I think that people are going to have to be taught how to talk to the agent.
HUANG: One of the things that's really great is that these agents speak English or any language you like them to.
CRAMER: OK.
HUANG: If it goes off, if it only spoke English at the time, you could just ask it, I would like you to learn Japanese. And it has to go off and learn Japanese. This is really fantastic.
CRAMER: OK. How about if I ask the agent why your stock's still stuck at 183 after all the things you announced yesterday?
HUANG: The market is a magical place, but it can't hold us back forever. And the reason for that is, our growth is accelerating. Our customer base is expanding well beyond the hyperscalers. We're adding more and more A.I. capabilities onto our platform. Used to be just OpenAI. Now it's OpenAI and xAI and Meta and now Anthropic, and, of course, OpenClaw. OpenClaw is such a big deal. OpenClaw is as big of a deal as ChatGPT, no doubt, yes. And so we have added all of this into our platform and now our growth is just accelerating.
CRAMER: I struggle because I think, when the numbers come out, we're going to say, wow, the stock is as cheap as Mondelez, that you're as cheap as Oreos.
HUANG: You know, I guess our company is just at a scale that nobody's ever seen before.
CRAMER: Right. And it's hard.
HUANG: Maybe -- yes, maybe that's the hard part. Yes.
CRAMER: Well, I think that if -- no one's ever -- if you decide you're just a semiconductor company, then, yes, I mean, wow, what an aberration.
HUANG: Yes.
CRAMER: But if you're something bigger, with imagination, they could see that your company might be earning $10 trillion.
HUANG: Yes. It's not outside—
CRAMER: Is it -- do you remember you told me you worked backwards, you go 20 years and work back?
HUANG: That's right.
CRAMER: Isn't it possible that we're talking to the first $10 trillion dollar company?
HUANG: Absolutely, absolutely possible. And that's our hope. And I think we're on our way there. The market will take care of itself. Our growth is accelerating. Our customer base is expanding. The number of ways that we're using A.I. is growing. And now, of course, OpenClaw is a very big deal.
CRAMER: Well, let's do something that we saw yesterday. We saw tokens that were demonstrably almost not -- no, more than lifelike. How about that? And you once showed me, we could do shading. Well, you have gone far beyond that. Amazon, let's give it -- let's go right there. Amazon has the creative rights to James Bond. Why would they have to hire someone, pay them a fortune, when James Bond could look much more realistic using your technology?
HUANG: Well, I'm going to have to advocate for the actors. And the reason for that is because A.I. is a probabilistic technology. We can make things look more realistic. But a great actor, a great artist brings out something that is the intangibles. And we never know what it is.
CRAMER: OK. Then how about Olaf? Let's go there. Disney doesn't have to have real actors. They can have you.
HUANG: Yes, but Olaf is Olaf. And so I'm going to take a side of the artist. I'm a -- deep love of artists. And I love the work that they do. You know that, in a lot of ways, Jim, you're an artist. I'm an artist. We bring out something that is outside of the average distribution, some intangible that the world didn't predict. Great companies do that. Great people do that. You do that. You're out of the distribution. The thing about A.I. is that we could recreate the distribution. We can recreate something. We can create something that's realistic. But we probably won't create something that is unexpectedly incredible. And that's where the artists and actors, they bring out that—
CRAMER: We want humanity. We want the da Vinci.
HUANG: And I want them to keep doing that. Yes.
CRAMER: When you talk about Michelangelo, we don't want to replace him.
HUANG: We can make their work more productive. Like, for example, maybe they didn't have a perfect take and they didn't want to go back to the studio and do that perfect take. They could take all of the takes that they have already taken and then extrapolate that extra take. And maybe that extra take, it's going to be exactly perfect. It's exactly the way the directors wanted it.
CRAMER: Let's get a little pedestrian, but it does matter.
HUANG: Yes.
CRAMER: Your stuff burns hot. We worry about the environment. The first time we had a serious talk about fire and you were able to find fire and ended it before a forest burned down, it must hurt you to see how hot your machines burn. I know someone who's buying 2,000 Caterpillar engines attaching them to the Marcellus Shale, pipeline that gives, and running in the middle of West Virginia a giant data center. I didn't think you set out to have that happen.
HUANG: We need energy to produce anything. Our country needs energy.
CRAMER: Right.
HUANG: We convert, what Nvidia's A.I. factories do, they convert energy into valuable intelligence tokens. It's just this magical piece of instrument. It's giant like this, and, of course, right, and much, much bigger than these. And when all connected together and you apply energy to it and monetizable tokens, valuable tokens come out. Well, it takes energy to do so. It takes a lot of energy to produce enormous amounts of it. Nvidia's a very large company. We're going to be building lots and lots of these factories around the world and all over the United States. And it's going to produce incredible economic value, but it's going to take energy. We are the most energy-efficient architecture in the world. It is the reason why they called me the token king. Nvidia is the inference king.
CRAMER: Well, I want to know how long the inference king and the token king is going to continue to work.
HUANG: You know, people ask me how long I'm going to work. I'm hoping to die on the job. And I'm not hoping to die any time soon.
CRAMER: Can you make it so that you live to 100 and die on the job? Because then we will be dealing with a company that could be $20 trillion.
HUANG: That's my dream come true. That's my dream come true.
CRAMER: Did you ever think about it when you were waiting tables at Denny's, that you might be able to create a $10 trillion to $20 trillion company?
HUANG: I was just trying to make it through the shift. When you're on the job, you got to stay focused on the job. That's why I don't wear a watch. I'm 100 percent there. And when I wasn't—
CRAMER: What was the biggest tip you ever got?
HUANG: A couple bucks.
CRAMER: Couple bucks.
HUANG: A couple of $2, $3. That was fine.
CRAMER: I want again to emphasize how many lives you have changed. You got together with the millionaires for our investing club.
HUANG: Thank you.
CRAMER: I have only seen institutions make incremental amounts of money for people. I have never seen a person and a company make people not of means into incredible means. I have never seen it. It is joyous. It is ethereal what you do, ethereal.
HUANG: Thank you.
CRAMER: Never seen it before.
HUANG: And I just want to say it's a privilege to do so, and I'm just getting started.
CRAMER: Jensen Huang, co-founder and CEO Nvidia. And I have to tell you, the idea that we will look back and say 183, that number will be nothing, nothing at all, because we're going so much higher. Thank you.
HUANG: Can't hold us back forever.
CRAMER: Absolutely.
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Stephanie Hirlemann
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