WHEN: Today, Monday, December 1, 2025
WHERE: CNBC’s “Squawk on the Street”
Following is the unofficial transcript of a CNBC exclusive interview with Nvidia Founder & CEO Jensen Huang and Synopsys CEO Sassine Ghazi on CNBC’s “Squawk on the Street” (M-F, 9AM-11AM ET) today, Monday, December 1. Following are links to video on CNBC.com: https://www.cnbc.com/video/2025/12/01/nvidia-ceo-ai-is-going-to-transform-every-single-industry.html and https://www.cnbc.com/video/2025/12/01/nvidia-ceo-jensen-huang-on-synopsys-partnership-its-a-huge-deal.html
All references must be sourced to CNBC.
JIM CRAMER: Joining us now exclusively, and this is very exciting and timely, NVIDIA Founder and CEO Jensen Huang and Synopsys CEO Sassine Ghazi. And both these gentlemen, I think, have a lot to say about the larger issues beyond what we’ve been dealing with. Gentlemen, thank you for coming on so much on Squawk on the Street. It’s a timely moment.
JENSEN HUANG: Hey, Jim. Hey, Carl. Nice to see you.
SASSINE GHAZI: Thank you. Great to be here.
CRAMER: All right. So, Jensen, I’m going to take it head on. The first word that I saw when I was reading the partnership was expanded. So, if it’s expanded, explain to me why this is a big deal we’re spending some time on for the world’s investing populace.
HUANG: This is a huge deal. The partnership we’re announcing today is about revolutionizing one of the most compute-intensive industries in the world, design and engineering. Synopsys is pivoting across their company to transform their software and all the tools that the industry, the world’s been using for some 35 years to be GPU accelerated on NVIDIA. They’re going to pivot the company to build on top of NVIDIA CUDA, physical A.I., as well as Omniverse, so that we can revolutionize all of these tools from EDA to SDA, system design automation to CAE to computer-aided drug discovery. This is going to expand the market of computing into the world of design and engineering for the very first time. This partnership is going to be revolutionary for that entire industry, expanding their TAM, expanding the capabilities. You know what’s really amazing? Jim, this is really the combination of everything I showed you when you visited NVIDIA years ago. It’s taken this long for us to create the software stack necessary for Synopsys and the rest of the EDA industry and SDA industry in order for them to accelerate the software that they’ve historically only ran on CPUs. As a result, we’re able to do simulations at a speed and scale unimaginable in the past, so that we could do basically the entire engineering work inside a computer in a digital twin before we have to build it at all. So, the type of products we can invent and the quality that we could do, and the speed that we could do it at is going to be extraordinary.
CRAMER: Right, Jensen. I think that when you first introduced this to me, you explained to me over and over again because I was so fascinated by — by what could happen with a ChatGPT with the prompts, was, Jim, that’s business to consumer and it’s really, really important. But you better start thinking enterprise. Enterprise is, you were using a number that is 10 times the size of what I was thinking about. Are you still standing by that?
HUANG: Absolutely. If you look at what we’re doing today, if you look, we’ve been partnering with Synopsys for a very long time. NVIDIA was built on a foundation of design tools from Synopsys and of course many other companies like Cadence and Siemens and Dassault. These are very important companies that the entire engineering industry is built on top of. As a result of what we’re able to do today, we’re able to bring GPU-accelerated computing, NVIDIA’s CUDA, into the world’s industrial sector for the very first time. This is — this is physics — physical A.I. This is A.I. that obeys the laws of physics, that A.I. that interacts with the physical world. This is extremely complex stuff. It’s taken us years to be able to do this. And now, if you look at the world’s industrial sector, it’s measured in trillions of dollars. So, for both NVIDIA and Synopsys and the entire industry, this is a giant expansion of opportunity.
CRAMER: All right, so let me speak to you about this, Sassine, because when I spoke with you, the thing that was important was you were about to close the Ansys deal, and autos are another gigantic market. I’m trying to put things in perspective. You get the money from NVIDIA. It’s not exclusive. That’s important. But the partnership matters a great deal. That when I look at the engineering that you do in aerospace, in automotive, in industrial, I say to myself, wait a second, should I really be concerned that Gemini 3 may win the battle against Perplexity? Is — am I small thinking if I’m focused just on that niche?
GHAZI: So Jim, Synopsys’ roots have been providing essential solutions for semiconductor design and verification. With the Ansys’ acquisition, it expands our time for every engineering workload. Think about any product that you just mentioned, be it automotive, robotics, drones, machinery for industries. They’re getting so sophisticated. They’re going to become A.I.-driven, meaning to design these systems, you need sophisticated engineering solutions in order to deliver these systems on time, deal with the complexity at a cost that is affordable. So, now with the Ansys portfolio, it expanded our time significantly. In order to deliver these solutions and delivering it in time for the customer to be able to simulate, you need acceleration, be it the GPU, be it A.I., to change the workflow, digital twin of the whole system. You need to re-engineer engineering in order to deliver to these sophisticated future products.
CRAMER: Wow, re-engineer engineering. I’m looking at Carl, it’s so important to try to put everything in perspective. Because Jensen, if you were here and we didn’t have the Synopsys, I would be saying, are you worried that the spend on A.I. for the data center is now well exceeding the cash flows for several of the key companies, for Oracle and OpenAI, and that perhaps the investment in OpenAI. that you’ve made maybe should be a little more iffy? Are these the kinds of questions? Is the CapEx unsustainable for this kind of — for the hyperscalers? Are these the kinds of questions that are really just part of the horse race and not part of the fourth industrial revolution that you’ve taught me about?
HUANG: Most people only see the tip of the iceberg and they see a partial part of the picture, as you know. You know, I think what’s going on at the foundation, we’re going through a platform shift from classical general-purpose computing running on CPUs to a new way of doing computing, accelerated computing running on GPUs. That old way of doing is going to continue to, to exist, of course, but the world is shifting to this new way of doing computing. That, the cash flow of the world’s hyperscalers are, at the core, really about supporting this platform shift. With or without Agentic A.I., with or without chatbots, the world’s hyperscalers would have made this platform shift anyhow, because this is a much more efficient way of doing computing. General purpose computing has really run its course, Moore’s law, as you know, is slowing tremendously. And so, the world needs a more powerful, more capable way of doing computing going forward. And so, at the — at the foundation, it’s that. The second thing to realize is that A.I. is not just chatbots. Chatbots are incredible, cognition A.I. is very important, but A.I. covers the entire world of physical A.I., industrial A.I., robotics, sciences, digital biology. A.I. is going to transform every single industry. This is the part that we’ve been talking about for a very long time. You and I have been talking about this literally for years. It’s just less visible because consumers don’t have to use engineering tools that we use from Synopsys and Cadence and others. We don’t — you know, our companies use these tools because it’s mission critical to us. These industrial applications, these industrial tools where accelerated computing and A.I. are now in the process of revolutionizing are foundational to our industries. It’s not optional to us. It’s mission critical to us. And now for the first time, we’re at the tipping point of that and we’re going to revolutionize the industrial software industry with it.
GHAZI: And just to give you a sense, Jim, what Jensen is referring to, you’re taking a workload that may run for two, three weeks and reducing it to hours. And that’s the value we’re delivering to the customers through this partnership and accelerating the software on GPU from NVIDIA.
CARL QUINTANILLA: Right. Although, Jensen, I’m sure you can sympathize with viewers who are trying to keep up with just your deal flow. We’re trying to keep up with your deal flow. And I guess you must — I’m wondering your communication strategy. How do you keep people afloat when they can’t be expected to understand that view from 40,000 feet?
HUANG: Well, I’ll just kind of keep trying harder, Carl. I think that the important concept here is that accelerated computing and A.I. is revolutionizing every single industry. Of course, it started in the consumer segment. And the reason why it starts in the consumer segment is because getting the answer 90 percent right is a pretty magical thing. But the industrial segment, that 10 percent you don’t get right, becomes mission critical. And so, it takes longer for us to create the tools, create the technology necessary for the industrial sectors, the enterprise segments, to be able to adopt this technology. But the time is now here. This platform shift that happened starting about 10 years ago, starting in consumers, is now in the process of happening across the world’s industries. Let me give you one statistic. I think this is actually about the same time that I met Jim. During that year, 2016, the world’s scientific supercomputers was 90 percent CPUs and 10 percent GPUs. This year, it’s 90 percent GPUs and 10 percent CPUs. The platform shift has happened. Now, that’s in scientific computing. What Synopsys does — what this industry does with engineering, is founded on science, founded on physics, and so principled physics. We’re in the process of making the shift in this industry now. This is one of the most computing-intensive industries in the world. And now, during this transition, we’re now doing the platform shift for this entire industry and elevating it with A.I. We’re going to expand the market really tremendously for this industry. It’s a really exciting time.
CRAMER: OK, so let me just follow up on that, gentlemen, because business to consumer is very, very big. But what I’ve been concerned about is, OpenAI is almost entirely right now business to consumer. We like Google so much. Obviously, they’re winning the horse race right now. How do we convince people, and you did it to me, but I’m struggling with others, that business to business is really the nirvana of what you’re doing. And the business to consumer, while very exciting to white collar, very exciting to people who want to play with it and get answers, it’s not a sideshow, but it’s much smaller than what we should be thinking about.
HUANG: Well, consumer IT is exciting. You know, it moves quickly. New technologies could be introduced quickly because, as I mentioned, getting 90 percent right in recommending a movie or 90 percent right in recommending an ad or 90 percent right in recommending, you know, the next item in your — in your basket is plenty delightful. However, in the world of designing cars, planes, factories, you know, building NVIDIA chips, you’ve got to be perfect. And the reason for that is because we have so much at stake. And so this industry requires the technology to be extraordinary. It takes longer time. But when it happens, the size of the industry is incredibly large. As you as you know, the world’s hundred trillion-dollar industry is largely industrial and enterprise to enterprise. These are enterprise, you know, serious industrial enterprise applications that are now being transformed —
CRAMER: OK.
HUANG: — by this platform shift.
CRAMER: But Sassine, am I supposed to believe that what will happen at the Dell conference call where Jeff Clarke talked exactly about A.I. factories, that we’re going to see a new shift, that we should be thinking about how much G.M. is spending, how much BMW is spending, how much Siemens is spending, how much the big Korean shipyards are spending. Is that what we should now add to the mix and not just Perplexity against Anthropic?
GHAZI: Exactly. If you think of all the companies you just mentioned and the percentage of R&D they invest in automation and software, et cetera, is going to become exponential, driven by the complexity and the sophistication of what they’re building. So, if they were spending two percent of their revenue in R&D that dedicated to the software automation and the technology is going to get significantly higher due to complexity in order for them to remain competitive and delivering for the future.
CRAMER: All right. And then, Jensen, I know — I’m sorry, go ahead.
HUANG: Here’s an easy way to think about it. You know, one of the things that’s really important is almost all industrial companies, companies that make things like NVIDIA, like GM, like Boeing. These are companies that spend probably hundreds of hundreds of millions, maybe very low billions of dollars in engineering software tools. However, the amount that they spend in prototyping all of those products is easily 10, 20 times higher. It’s just it’s absolutely the same case here at NVIDIA. We — we spend a few hundred million dollars in EDA tools and design tools. However, we spend billions of dollars in prototyping it. In the future, we’re going to prototype all of these products digitally so that we don’t waste any money when we build it physically. In order to build — in order to prototype things digitally simulated inside a digital twin. This is all the things I’ve been talking to you about.
CRAMER: Right.
HUANG: All of a sudden, the market opportunity increases by a factor of 10 to 100.
CRAMER: OK, so last question. Right now, we spend a lot of time talking about Google and what they’re doing with their own — their own TPU. And we talk about whether Meta will do it. But one thing that you taught me was you like to think 20 years forward and then backward. I’m thinking about Vera Rubin. I had to go read that Richard Feynman book because you mentioned he’s a pretty funny guy. But I mean, when I look at the Vera Rubin and the Feynman, am I going to be saying, you know what, that was a great thing those other guys had during that nine-month window that Jensen allowed them to have?
HUANG: You know, listen, we’ve been — we’ve been competing with ASICs now for quite a long time, and Google has had ASICs for a long time. NVIDIA’s, NVIDIA, and they did a great job, as you know, and I’ve always been complimentary.
CRAMER: Right. Always.
HUANG: What NVIDIA does is much more versatile. Our technology is much more fungible. Notice the announcement today. Accelerating Synopsys design tools, the EDA, the SDA, the CAE tools requires a computer architecture like CUDA. It’s not available for ASICs. And so NVIDIA can address markets that are much, much broader, not just chatbots. We’re also everywhere. We’re in every cloud. We’re in every single OEM. We’re on-prem. And we’re also at the edge. And so the NVIDIA opportunity is much, much larger. And you’re now seeing a real tangible example of an opportunity that we could do with our platform that nobody else can. And so this is a very big opportunity for us, huge opportunity to reinvent the EDA industry, the design and engineering industry for Synopsys and the rest of the industry, and a growth opportunity for us because this is so computationally intensive.
QUINTANILLA: I was just thinking the classic book is surely you’re joking, Mr. Feynman.
CRAMER: Yeah.
QUINTANILLA: Maybe it should be surely you’re joking, Mr. Huang.
CRAMER: Because of Jensen, yes. Jensen really helped. Jensen, I didn’t get to ask you about how none of your revenue includes China. Should I have just included that as a boiler point that you can’t talk about what’s going on? Kind of a coda.
HUANG: Well, you know, I would — I would like everybody to just assume that China is a bonus opportunity in the future. At the moment, we got plenty of our demand is really strong, as you know, demand is really skyrocketing. And — and over the next couple of years, we’ve got a lot of demand we have to go serve. And if — if China comes along, which I believe is going to be in the best interest of the United States, as well as China and the rest of the world, that’s going to be a huge bonus opportunity for us.
CRAMER: All right, I want to thank Sassine Ghazi from Synopsys, a great company that was more than a 30-billion-dollar acquisition that made advances. And Jensen Huang comes on. And Jensen, I can’t thank you enough for giving us the perspective that you gave me almost a decade ago, that business consumers very interesting focus on business to business. Thank you so much, gentlemen.
GHAZI: Thank you.
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