NVIDIA Corporation (NVDA) on Q3 2021 Results - Earnings Call Transcript
Operator: Good afternoon. My name is Jason, and I will be your conference operator today. At this time, I would like to welcome everyone to NVIDIA’s Third Quarter Financial Results Conference Call. All lines have been placed on mute to prevent any background noise. After the speakers’ remarks, there will be a question-and-answer session. Thank you. Simona Jankowski, you may begin your conference. Simona Jankowski: Thank you. Good afternoon, everyone and welcome to NVIDIA’s conference call for the third quarter of fiscal 2021. Colette Kress: Thank you, Simona. Q3 was another exceptional quarter with record revenue of $4.73 billion, up 57% year-on-year, up 22% sequentially and well above our outlook. Our new NVIDIA Ampere GPU architecture is ramping with excellent demand across our major market platforms. Q3 was also a landmark quarter, both for us and the industry as a whole. As we announced plans to acquire Arm from SoftBank for $40 billion, we are incredibly excited about the combined company’s opportunities and we are working through the regulatory approval process. For today, we will focus our remarks on our quarterly performance. Starting with gaming. Revenue was a record $2.27 billion, up 37% year-on-year, up 37% sequentially, and ahead of our high expectations. Driving strong growth was our new NVIDIA Ampere architecture-based GeForce RTX 30 series of gaming GPUs. The GeForce RTX 3070, 3080 and 3090 GPUs offer up to two times the performance and two times the power efficiency over the previous Turing-based generation. Our second generation NVIDIA RTX combines ray tracing and AI to deliver the greatest ever generational leap in performance. Operator: Certainly. Your first question comes from the line of John Pitzer from Credit Suisse. Your line is open. John Pitzer: Can you hear me? Jensen Huang: Yes. John Pitzer: Yes. Hey, guys. Congratulations on the solid results. Thank you for letting me ask the question. Just Colette, going back to your commentary around Mellanox, it seems like you’re guiding the January quarter to about $500 million, which means the core data center business is still growing nicely, call it, 6%, 7% sequentially. I’m just kind of curious, when you look at the core data center business, I know there’s not a direct correlation to server business. But, we’re clearly going through a cloud digestion in server and core vertical markets, enterprise, the servers are weak. When you look at your core data center business, do you feel as though that’s having an impact, and this is sort of the digestion that you saw kind of in late fiscal ‘20 -- sorry, fiscal ‘19 into ‘20, but you’re doing it still growing significantly year-over-year, or how would you characterize the macro backdrop? Colette Kress: Sure. Let me clarify for those also on the call. Yes, we expect our data center revenue in total to be down slightly quarter-over-quarter. The computing products, NVIDIA computing product is expected to grow in the mid-single-digits quarter-over-quarter as we continue the NVIDIA AI adoption and particularly as A100 continues to ramp. Our networking, our Mellanox networking is expected to decline meaningful quarter-over-quarter as sales to that China OEM will not recur in Q4, though we still expect the results to be growth of 30% or more year-over-year. The timing of some of this business therefore shifted from Q4 to Q3, but overall H2 is quite strong. So, in referring to overall digestion, the hyperscale business remains extremely strong. We expect hyperscale to grow quarter-over-quarter in computing products as A100 continues to ramp. The A100 continues to gain adoption, not only across those hyperscale customers, but again we’re also receiving great momentum in inferencing with the A100 and the T4. I’ll turn it over here to Jensen to see if he has more that he would like to add. Jensen Huang: Yes. Colette captured it very well. The only thing I would add is that our inference initiative is really gaining great momentum. Inference is one of the hardest computer science problems. Compiling these gigantic neural network computational graphs into a target device really, really -- has proven to be really, really hard. The models are diverse when you count vision to language to speech. And there are so many different types of models being created that model sizes are doubling every couple of months. The latency expectations are increasing all the time, -- or latency is decreasing all the time. And so, the pressure on inference is really great. The technology pressure is really great. And our leadership there is really pulling ahead. We’re in our seventh generation tensorRT. We, over the course of the last couple of years, developed an inference server. It’s called Triton, has been adopted all over the place. We have several hundred customers now using NVIDIA AI to deploy their AI services. This is in the early innings, and I think this is going to be our largest near-term growth opportunity. So, we’re really firing on all cylinders there between the A100s ramping in the cloud, A100s beginning to ramp in enterprise, and all of our inference initiatives are really doing great. John Pitzer: Jensen, maybe to follow on there just on the vertical markets, clearly work-from-home and COVID this year kind of presented a headwind to new technology deployments on-prem. I’m kind of curious, if we expect sort of an enterprise recovery in general next year, how do you think that will translate into your vertical market strategy? And is there anything else above and beyond that you can do to help accelerate penetration of AI into that end market? Jensen Huang: Yes. John, that’s a good point. I mean, it’s very clear that the inability to go to work is slowing down the adoption of new technology in some of the verticals. Of course, we’re seeing rapid adoption in certain verticals, like for example using AI in health care to rapidly discover new vaccines and early detection with outbreaks and robotic applications. So, warehouses, digital retail, last mile delivery, we’re just seeing just really, really great enthusiasm around adopting new AI and robotics technology. But in some of the more traditional industries, new capabilities and new technologies are slow to deploy. One of the areas that I’m really super excited about is the work that we’re doing in remote work and making it possible for people to collaborate remotely. We have a platform called Omniverse. It’s in early beta. The feedback from the marketplace has been really great. And so, I’ve got a lot more to report to you guys in the upcoming months around Omniverse. And so -- but anyways, I think, when the industry recover, we serve -- our fundamental purpose as a company is to solve the greatest challenges that impact the industry where ordinary computers can’t. And these challenges are -- serve some of the most important applications in the verticals that we address. And they’re not commodity applications. They’re really impactful, needle-moving applications. So, I have every confidence that when the industries recover, things will get designed. Cars will be designed, and planes will be designed, and ships will be designed, and buildings will be designed. And we’re going to see a lot of design, and we’re going to see a lot of simulation. We’re going to see a lot of robotics applications. Operator: Your next question comes from the line of C.J. Muse from Evercore. Your line is open. C.J. Muse: You talked about in your prepared remarks limited availability of capacity components. You suggested perhaps a few months to catch up. Curious if you can speak to the visibility that you have for both, gaming and data center into your April quarter? Jensen Huang: Yes. Colette, do you want me to take that real quick and maybe you can help me out? Colette Kress: Yes, absolutely. Jensen Huang: So, C.J., first off, we have a lot of visibility into the channel, as you know, especially for gaming. And we know how many weeks of inventory is in what parts of the channel. We’ve been draining down the channel inventory for Turing for some time. And meanwhile, we’ve also expected a very, very successful launch with Ampere. And even with our bullish demand expectation and all of the Amperes that we built, which is one of the fastest ramps ever, the demand is still overwhelming. And this I guess in a lot of ways is kind of expected, the circumstances are -- it’s been a decade since we’ve invented a new type of computer graphics. I mean, two years ago, we invented and it set the industry on course to create the type of images that we see today. But, it’s very clear that the future is going to look something much, much more beautiful. And we invented NVIDIA RTX to do that. And it has two capabilities, one based on ray tracing and the other one is based on artificial intelligence image generation. The combination of those two capabilities is creating images that people are pretty ecstatic about. And at this point, it’s defined the next-generation content. And so when we -- it took us 10 years to invent it. We launched it two years ago and took our second generation to really achieve the level of quality and performance that the industry -- that they really expect. And now, the demand is just overwhelming. And so, we’re going to continue to ramp fast. And this is going to be one of our most successful ramps ever. And it gives our installed base of some 200-million-plus GeForce gamers the best reason to upgrade in over a decade. And so, this is going to be a very large generation for us is my guess. And then, with respect to data center, we’re ramping into A100. A100 is our first generation of GPUs that does several things at the same time. It’s universal. We position it as a universal because it’s able to do all of the applications that we in the past had to have multiple GPUs to do. It does training well. It does inference incredibly well. It does high-performance computing. It does data analytics. And so, it’s able -- the Ampere architecture is able to do all of this at the same time. And so, the utilization for data centers is -- and the utility is really, really fantastic, and the reception has been great. And so, we’re going to ramp into all of the world’s clouds. I think, starting this quarter, we’re now in every major cloud provider in the world, including Alibaba or Golan, and of course the giants, the Amazon, the Azure and Google Clouds. And we’re going to continue to ramp into that. And then, of course, we’re starting to ramp into enterprise, which in my estimation, long term will still be the largest growth opportunity for us, turning every industry into a AI, turning every company into AIs and augment it with Al and bringing the iPhone moment to all of the world’s largest industries. And so, we’re ramping into that, and we’re seeing a great deal of enthusiasm. Operator: Your next question comes from the line of Stacy Rasgon from Bernstein Research. Your line is open. Stacy Rasgon: You said that the extra week was contributing incrementally to revenue and OpEx. Can you give us some feeling for how much is contributing to revenue and OpEx in Q4? And does that impact, at least on the revenue side, differ, say between like gaming and data center? And then, how should we think about it impacting seasonality into Q1 as that extra week rolls off? Colette Kress: Sure. Let me try this one, Jensen. Yes, we’ve incorporated that 14th week into our guidance for both, revenue and OpEx. We will likely have incrementally positive impact on revenue, although it is tough to quantify, okay? Our outlook also reflects incremental OpEx for Q4 in primarily two different areas in terms of compensation and depreciation. And given that our employees with such a material power of our OpEx, it will -- it can be close to one-fourteenth of the quarter. Now, when we look a little bit farther, we should think about the incremental positive in both, gaming and data center from that extra week as there hopefully will be extra supply, but not likely as much as one-fourteenth of the quarter of revenue as enterprise demand is essentially project-based, and game demand though is tied to the number of gaming that gamers that might be shopping for the overall holiday. So, again, still very hard for us to determine at this time. Normally, between Q4 and Q1 there is seasonality in gaming, seasonality downward. But, we’ll just have to see as we are still supply-constrained within this Q4 to see what that looks like. From an OpEx standpoint, we’ll probably expect our OpEx to be relatively flattish as we move from Q4 to Q1. Operator: Your next question comes from the line of Vivek Arya from Bank of America. Vivek Arya: Thanks for taking my question and congratulations on the strong growth. Jensen, my question is on competition from internally designed products by some of your larger cloud customers, Amazon and Google and others. We hear about competition from time to time. And I wanted to get your perspective. Is this a manageable risk? Is the right way to think that they are perhaps using more of your product in their public cloud, but they are moving to internal products for internal workloads? Just how should we think about this risk going forward? Thank you. Jensen Huang: Thanks, Vivek. Most of the cloud vendors, in fact, I believe all of the cloud vendors use the same infrastructures largely for their internal cloud and external cloud, or have the ability to or largely do. And, there’s -- the competition, we find to be really good. And the reason for that is this. It just suggests that acceleration -- they make it very clear, that acceleration is right path forward for training and inference. The vast majority of the world’s training models are doubling in size every couple of months, and it’s one of the reasons where our demand is so great. The second is inference. The vast majority of the world’s inference is not on CPUs. And nothing is better than the whole world recognizing that the best way forward is to do inference on accelerators. And when that happens, our accelerator is the most versatile. It is the highest performance. We move the fastest. Our rate of innovation is the fastest because we’re also the most dedicated to it, we’re most committed to it, and we have the largest team in the world to it. Our stack is the most advanced, giving us the greatest versatility and performance. And so, we see spots of announcement here and there. But, they’re also our largest customers. And as you know that we’re ramping quite nicely at Google, we’re ramping quite nicely at Amazon and Microsoft and Alibaba and Oracle and others. And so, I think, the big takeaway is that -- and the great opportunity for us if you look at the vast amount of workload -- AI workload in the world, the vast majority of it today is still on CPUs. And it’s very clear that this is going to be an accelerated workload. And we’re the best accelerator in the world. And, this is going to be a really big growth opportunity for us in near term. In fact, we believe it’s our largest growth opportunity in near term. And we’re in the early innings of it. Operator: Your next question comes from the line of Harlan Sur from JP Morgan. Your line is open. Harlan Sur: Good afternoon. Thanks for taking my question, and great job on the quarterly execution. The Mellanox networking connectivity business was up 80% year-over-year. I think, it was up about 13%, 14% sequentially. I know there was upside in October from one China customer, but it did grow 70% year-over-year last quarter, and you’re still expecting 30% year-over-year growth next quarter. If I remember correctly, I think, InfiniBand is about 40% of that business; Ethernet Cloud is about 60%. Jensen, what are the big drivers, especially since we’re in the midst of a cloud spending digestion cycle? And I just saw that the team announced their next-gen 400-gig InfiniBand solution, which should drive another strong adoption cycle with your supercomputer customers. When does this upgrade cycle start to fire? Jensen Huang: Yes. Let’s see. Our data center business consists of supercomputing centers, which is small, high-performance computing, which is a much larger part of super computing, much larger than supercomputing, and then hyperscale and enterprise, which about 50-50. Of the data center business, the accelerated computing part is not very much associated with digestion than others. It’s much more associated with workloads and our new product cycles, the TCO that we bring in and AI inference, the type of models that the cloud service providers are deploying, whether they’re deploying new AI models, based on deep learning, and how much of it that we -- how much of those workloads that we’ve completed, the porting to our accelerators and ready it for deployment. And so, those are the factors associated with accelerated computing. It’s really about the apps, it’s really about the workloads and really driven by AI. On the other hand, the networking part of our business is more connected to CPU business because they’re much more broad-based. The networking part of our business is driven by this idea of new hyperscale data center architecture called disaggregation. It’s software disaggregation, not necessarily hardware disaggregation. Software disaggregation, where this type of software called Kubernetes orchestrate microservices that are deployed across the data center. So, one service, one application isn’t monolithic running on one computer anymore. It’s distributed across multiple computers and multiple nodes, so that the hyperscale data centers can more easily scale up and scale out according to the workloads and according to the demand on the data center. And so, this disaggregation has caused the networking between the compute nodes to be of all vital importance. And because Mellanox is the lowest-latency, highest-performance, highest-bandwidth network that you can get the TCO benefit at the data center scale is really fantastic. And so, when they’re building out data centers, Mellanox is going to be much more connected to that. In the enterprise side of it, depending on new CPU cycles, it could affect them. If a CPU cycle were to delay a little bit, it would affect them by a quarter, it would pull-in by a quarter -- it would affect them by pull-in of a quarter. And so, those are kind of the dynamics of it. I think, that the net-net of it is that it’s a foregone conclusion at this point that AI is going to be the future of the way software is run. AI is the most powerful technology force of our time. And acceleration is the best path forward. And so, that’s what drives our computing business. And the networking business has everything to do with the way architecture of data centers, cloud data centers, which is architected with micro services now. And that’s what foundationally drives their -- our networking work business demand. And so, we’re really well-positioned in these two fundamental dynamics because as we know, AI is the future and cloud computing is the future. Both of those dynamics are very favorable to us. Operator: Your next question comes from the line of Timothy Arcuri from UBS. Your line is open. Timothy Arcuri: Thanks a lot. I wanted to ask a question that was asked before in a bit of a different way. If I look at the core business, excluding Mellanox, the core data center business, it was up about 6% sequentially the past two quarters, and your guidance sort of implies up about that much again in January, which is certainly good, and there is some cloud digestion. But, of course you have Ampere still ramping as well, which should be a pretty good tailwind. So, there seems to be some offsetting factors. So, I guess, I wonder if you feel like your core data center revenue is still being constrained right now by some market digestion. And kind of how you sort of balance or handicap these two factors? Thanks. Jensen Huang: Our growth is -- in the near term is more affected by the cycle time of manufacturing and flexibility of supply. We are in a good shape to -- and all of our supply is -- informs our guidance. But, we would appreciate shorter cycle times; we would appreciate more agile supply chains. But, the world is constrained at the moment. And so, we just have to make the best of it. But, even in that condition - even in that condition, we’ve -- all of that is building for our guidance, and we expect to grow. Operator: Your next question comes from the line of Aaron Rakers from Wells Fargo. Your line is open. Aaron Rakers: Yes. Thanks for taking the question, and also congratulations on the quarter. I wanted to go back to kind of the Mellanox question. I know prior to the acquisition, Mellanox was growing maybe in the mid to high-20% range. These last two quarters, it’s grown over 75%. I guess, the simple question is how do you think about the growth rate for Mellanox going forward? And on that topic, we started to hear you talk more about BlueField and data processing units. I think, in your commentary, you alluded to server OEM design wins incorporating these DPUs. What are you looking at, or when should we think about the DPU business really starting to inflect and become a material driver for the business? Thank you. Jensen Huang: Long term, every computer in the world will be built like a data center. And every node of a data center is going to be a data center in itself. And the reason for that is because we want the attack surface to be basically zero. And today, most of the data centers are only protected as a periphery. But in the future, if you would like cloud computing to be the architecture for everything and every data center is multi-tenant, every data center is secure, then you’re going to have to secure every single node. And each one of those nodes are going to be a software-defined networking, software-defined storage, and it’s going to have per application security. And so, the processing that it will need to offload, the CPUs, is really quite significant. In fact, we believe that somewhere between 20% to 40% of today’s data centers -- cloud data centers is the capacity, the throughput, the computational load is consumed running basically the infrastructure overhead. And that’s what the DPUs intended -- was designed to do. We’re going to offload that, number one; and number two, we’re going to make every single application secure. And confidential competing, zero trust computing will become a reality. And so, the importance is really quite tremendous. And I believe therefore that every single server in the world will have a DPU inside someday, just because we care so much about security and just because we care so much about throughput and TCO. And it’s really the most cost-effective way of building a data center. And so, I expect our DPU business to be quite large. And so, that’s the reason why we’re putting so much energy into it. It’s a programmable data center on a chip, think of that way, and data center infrastructure on a chip. It is the reason why we’re working with VMware on taking the operating system in the data center, the software-defined operating system in the data center, putting bring it on BlueField. And so, this is a very important initiative for us. I’m very excited about it, as you can imagine. Operator: Your next question comes from the line of Ambrish Srivastava from BMO Capital Markets. Your line is open. Ambrish Srivastava: Yes. Thank you very much. Colette -- and I apologize if I missed it, but for Mellanox, do you expect it to get back to the growth trajectory on a sequential basis in the April quarter? And I’m assuming that the shortfall in the current quarter is from a pull-in from Huawei? Colette Kress: So, our impact to our Q4 guidance for Mellanox, yes, is impacted by a sale to a China OEM for Mellanox. That will not recur in Q4. And as we look forth into Q1 of April, we’re going to take this a quarter at a time and provide thoughts and guidance for that once we turn the corner to the new fiscal year. Jensen Huang: At the highest level, Colette, I think, the -- it’s safe to say that high-speed networking is going to be one of the most important things in cloud data centers as we go forward. And the vast majority of the world’s data center is still built for the traditional hyper-converged architecture, which is all moving over to microservices-based disaggregate --software-defined disaggregated architectures. And that journey is still in its early days. And so, I fully expect future cloud data centers -- all future data centers are going to be connected with high-speed networking inside. They call it east-west traffic. And, all of the traffic will be secured. And so, imagine building firewalls into every single server. And imagine every single transaction, every single transmission inside the data center to be high speed and fully encrypted. And so, pretty amazing amount of computation is going to have to be installed into future data centers. But, that’s an accepted requirement now. And I think, our networking business, Mellanox is in the early innings of growth. Operator: Your final question today comes from the line of William Stein from Truist Securities. Your line is open. William Stein: Great. Thanks for taking my question. You’ve given us some pieces of this puzzle. But, I’m hoping maybe you can address directly the sort of SKU-by-SKU rollout of Ampere. We know that we didn’t have a ton of SKUs last quarter. There were more in this quarter that you just announced. Now, you’re doing sort of this refresh it sounds like with double the memory on the A100. Is the T4 going to be refreshed? And if so, when does that happen? And, are there other, either systems or chips that are still waiting for the Ampere refresh that could potentially contribute to an extended cycle as we look at the next year? Jensen Huang: Yes. In terms of the total number of SKUs that we’ve ramped of Ampere, we’re probably somewhere along a third to a half of the SKUs at this point, maybe a little bit less. Yes, it’s less. The way that you could think through it, you could reverse engineer it, it is like this. You know what our gaming lineup looks like for desktops. And so, traditionally, we try to have a new architecture in every single segment. And we’ve not gone below 499 yet. And so, there’s a very big part of the marketplace that we’re still in the process of addressing. And then, the second thing is laptops. None of the Ampere architecture has launched for laptops. And then, there’s workstations. And you do the same thing with desktops and workstations and laptops workstations. And none of those have gone out yet. And then, there’s data center. And our data center business for cloud, you’ve seen some of the early versions of it, A100. But, then, there’s cloud computing for graphics, there’s cloud gaming. For those enterprise, edge enterprise applications, enterprise data analytics applications. And so, there’s a fair number of exciting new products we still have in front of us. Operator: That concludes our Q&A for today. I now turn the call back to Ms. Jankowski for closing remarks. Simona Jankowski: Actually, that will be for Jensen. Operator: My apologies. Jensen Huang: Okay. Thank you. Thank you, Simona. This was a terrific quarter. NVIDIA is firing on all cylinders. And the RTX has reinvented graphics and has made real-time ray tracing the standard of next generation content, creating the best ever reason to upgrade for hundreds of millions of NVIDIA gamers. AI, where software writes software no humans can, is the most powerful technology force of our time and is impacting every industry. NVIDIA AI again swept MLPerf training and now inference as well, extending our leadership in this important new way of doing computing. NVIDIA AI’s new Triton inference server, a platform that I will speak a lot more about in the future and a lot more frequently because it’s important, and our full stack optimized platform are gaining rapid adoption to operate many of the world’s most popular AI-enhanced services, opening a major growth opportunity. Data centers are the new unit of computing. Someday, we believe there will be millions of autonomous data centers distributed all over the globe. NVIDIA’s BlueField DPU programmable data center on a chip and our rich software stack will help place AI data centers in factories, warehouses, 5G base stations and even on wheels. And with our pending acquisition of Arm, the company that builds the world’s most popular CPU, we will create the computing company for the age of AI, with computing extending from the cloud to trillions of devices. Thank you for joining us today. I wish all of you happy holidays. And please do stay safe, and I look forward to seeing you guys next time. Operator: That concludes today’s conference call. You may now disconnect.
NVIDIA Corporation's Market Position Amid New AI Chip Export Restrictions
- The Biden administration's new export restrictions on AI chips aim to limit China and Russia's access to advanced AI technologies, potentially impacting NVIDIA's international sales.
- NVIDIA's stock experienced a slight decrease following the announcement of these restrictions, indicating investor concerns about the company's future business operations.
- The company's dominant position in the GPU market for AI and machine learning applications remains strong despite potential challenges from geopolitical factors.
NVIDIA Corporation, listed as NASDAQ:NVDA, is a prominent player in the technology sector, particularly known for its advanced AI chips. The company is a leader in the graphics processing unit (GPU) market, which is crucial for AI and machine learning applications. NVIDIA faces competition from companies like AMD and Intel, but it remains a dominant force in the AI chip industry.
On January 6, 2025, Sheldon Whitehouse engaged in a sale transaction of NVIDIA shares. This transaction comes at a time when the Biden administration is set to implement new export restrictions on AI chips. These restrictions aim to limit China and Russia's access to advanced AI technologies, as highlighted by Bloomberg. This move could potentially affect NVIDIA's international sales and market strategies.
The Biden administration's decision to tighten export restrictions is part of a broader strategy to maintain U.S. dominance in the AI sector. Companies like NVIDIA and AMD are expected to be impacted by these new regulations. The announcement of these restrictions has already led to a slight decline in NVIDIA's stock price, reflecting investor concerns about the potential impact on the company's business operations.
NVIDIA's stock is currently priced at $140.11, experiencing a slight decrease of 0.03, which translates to a 2.14% drop. The stock's trading range for the day was between $137.89 and $143.95. Over the past year, NVIDIA's stock has seen a high of $153.13 and a low of $53.56. The company's market capitalization is approximately $3.43 trillion, with a trading volume of 218,985,854 shares.
The new export restrictions could pose challenges for NVIDIA's ability to sell AI chips to foreign markets. As reported by Ian King on "Bloomberg The Close," these additional limits are part of a strategy to regulate the international distribution of advanced AI technology. This development underscores the importance of monitoring geopolitical factors that can influence NVIDIA's market performance and strategic decisions.
Nvidia Beats Q3 Estimates but Falls Short on Q4 Guidance Amid High AI Expectations
Nvidia’s (NASDAQ:NVDA) third-quarter results surpassed Wall Street expectations, yet its fourth-quarter guidance fell short of the high investor anticipations driven by strong AI demand. Following the announcement, Nvidia’s shares declined by over 2% in pre-market today.
In Q3, the company reported earnings per share of $0.81 and revenue of $35.1 billion, exceeding analyst forecasts of $0.75 EPS and $33.09 billion in revenue. The data center segment generated $30.8 billion, marking a 17% increase from the previous quarter and a 112% rise year-over-year, outperforming the expected $28.84 billion.
For the fourth quarter, Nvidia projected revenue of $37.5 billion, plus or minus 2%, compared with the anticipated $37.09 billion. The company also forecasted GAAP gross margins of 73.0%, with a possible variance of 50 basis points.
NVIDIA Corporation's Impressive Earnings and Market Position
- NVIDIA Corporation (NASDAQ:NVDA) reported earnings per share (EPS) of $0.81, surpassing estimates and showcasing strong financial performance.
- The company's revenue of $35.08 billion exceeded expectations, driven by its Data Center segment, despite concerns over supply constraints.
- NVIDIA's valuation metrics, such as a high price-to-earnings (P/E) ratio of 56.74 and a price-to-sales ratio of 31.59, reflect market expectations for future growth but also suggest the stock is overvalued.
NVIDIA Corporation, listed as NASDAQ:NVDA, is a leading player in the technology sector, known for its graphics processing units (GPUs) and artificial intelligence (AI) capabilities. The company competes with other tech giants like AMD and Intel. On November 20, 2024, NVIDIA reported earnings per share (EPS) of $0.81, surpassing the estimated $0.75, and actual revenue of $35.08 billion, exceeding the estimated $33.17 billion.
The positive earnings report contributed to a favorable market sentiment, as highlighted by the Dow Jones Industrial Average gaining over 100 points. Despite this, the CNN Money Fear and Greed Index remains in the "Neutral" zone, indicating a balanced market sentiment. This suggests that while NVIDIA's performance is strong, broader market conditions remain cautious.
NVIDIA's Q3 2025 earnings call featured key executives like Colette Kress and Jensen Huang, along with analysts from major financial institutions. The call provided insights into the company's financial performance and strategic direction. The strong results were largely driven by the Data Center segment, although concerns about supply constraints for its Hopper and Blackwell GPUs persist.
Despite impressive earnings, NVIDIA's stock is considered overvalued at $145 per share, with a projected compound annual growth rate of 3.4% over the next five years. The company's valuation is under scrutiny, especially given its $3.6 trillion market cap. The high price-to-earnings (P/E) ratio of 56.74 reflects market expectations for future growth, while the price-to-sales ratio of 31.59 indicates a premium on sales.
NVIDIA's financial metrics reveal a strong liquidity position, with a current ratio of 4.10, and a conservative debt-to-equity ratio of 0.13. The enterprise value to sales ratio of 31.60 and enterprise value to operating cash flow ratio of 60.71 highlight the company's valuation relative to revenue and cash flow. The earnings yield of 1.76% provides insight into the return on investment, despite the high valuation.
Redburn-Atlantic Starts Coverage on NVIDIA with Buy Rating, Citing Growth in Accelerated Computing
Redburn-Atlantic analysts initiated coverage on NVIDIA (NASDAQ:NVDA), assigning a Buy rating and setting a price target of $178 on the stock. The analysts highlighted NVIDIA’s leadership in accelerated computing, a field that has become increasingly relevant as traditional advances in computing efficiency, such as Moore’s Law and Dennard scaling, have slowed.
Currently, accelerated computing is heavily driven by artificial intelligence workloads. Over the next decade, however, the cost efficiencies of this technology are expected to broaden its appeal, making it a valuable tool for a variety of traditional computing tasks and software applications. NVIDIA is positioned to benefit from this shift, as AI-driven coding capabilities developed in the first wave of AI will likely support a new wave of accelerated computing by updating core software used in general-purpose computing.
The analysts acknowledged that adoption of accelerated computing may not progress in a linear fashion but emphasized that the fundamental drivers supporting its growth are structural.
Nvidia’s Blackwell and Hopper GPUs in High Demand, Says Morgan Stanley
NVIDIA (NASDAQ:NVDA) is seeing robust demand for its Hopper and Blackwell GPUs, according to a note from Morgan Stanley. the bank reported that Nvidia's Blackwell chips have entered volume production, driven by significant interest from major customers, presenting strong growth potential for the company. As a result, the company’s shares gained more than 4% intra-day on Tuesday.
Oracle recently announced plans to construct a Zettascale AI supercluster using 131,000 Nvidia Blackwell GPUs, delivering 2.4 ZettaFLOPS of AI performance. This move has further boosted Nvidia’s outlook and positively impacted its semiconductor suppliers.
At a recent event, Oracle reportedly requested additional GPU supply, signaling optimism for the Asia-based AI semiconductor supply chain. Morgan Stanley now projects that TSMC’s CoWoS (Chip-on-Wafer-on-Substrate) capacity will increase to 80,000-90,000 wafers per month by 2025, up from earlier estimates of 70,000.
In the near term, demand for Nvidia’s Hopper H200 GPUs remains strong, especially among smaller cloud service providers and sovereign AI projects, easing concerns about inventory buildup. Morgan Stanley estimates that 450,000 Blackwell chips will be produced in the fourth quarter of 2024, creating a potential revenue opportunity exceeding $10 billion for Nvidia.
The bank also noted that while Nvidia is addressing some technical challenges with its GB200 server racks, these issues are typical for new product launches and are being resolved as part of the standard debugging process.
Nvidia Corporation (NASDAQ:NVDA) Sees Bullish Sentiment Amid AI Dominance and Favorable Macroeconomic Conditions
- Timothy Horan of Oppenheimer sets a price target of $215 for NASDAQ:NVDA, indicating an 81.69% potential upside.
- The Federal Reserve's decision to cut interest rates by 50 basis points has positively impacted the technology sector, particularly benefiting Nvidia due to its stronghold in the AI industry.
- Nvidia's stock has experienced a surge, with a notable increase of $4.5 or approximately 3.97% in a single day, reflecting its substantial market presence and investor interest.
Nvidia Corporation (NASDAQ:NVDA) is a leading player in the technology sector, particularly known for its significant contributions to the artificial intelligence (AI) industry. Timothy Horan of Oppenheimer's recent price target of $215 for NVDA, indicating an 81.69% potential upside from its current price, underscores the bullish sentiment surrounding Nvidia's stock. This optimism is rooted in Nvidia's strong market position and its pivotal role in driving advancements in AI technology.
The broader technology sector, especially companies like Nvidia that are at the forefront of AI, has been positively impacted by the Federal Reserve's decision to cut interest rates by 50 basis points. As Dan Ives of Wedbush Securities pointed out, this move has bolstered the dominance of Big Tech in the markets, with Nvidia being a prime beneficiary due to its stronghold in the AI sector. The rate cut has created a more favorable macroeconomic environment for growth stocks, encouraging investors to reassess their positions on AI and Nvidia.
Nvidia's stock has indeed been surging, as highlighted by The Motley Fool, with a notable increase of $4.5 or approximately 3.97% in a single day. This surge is attributed to the optimistic outlook on the macroeconomic landscape following the rate cut, which has particularly favored growth stocks like Nvidia. The company's market capitalization of around $2.89 trillion and its trading volume of 279.87 million shares reflect its substantial presence and investor interest in the market.
Furthermore, the coverage initiation by William Blair, awarding Nvidia an outperform rating with a potential 41% upside, emphasizes the market's underappreciation of Nvidia's total addressable market. This analysis by Sebastien Naji suggests that Nvidia's current valuation does not fully reflect its market potential, reinforcing the optimistic projections for the company's future performance.
Overall, the combination of a favorable macroeconomic environment, Nvidia's dominance in the AI sector, and the bullish outlook from financial analysts contributes to the strong performance and promising future of Nvidia's stock. The company's significant market capitalization and the recent surge in its stock price further underscore its leading position in the technology sector and its potential for continued growth.
NVIDIA Started With Outperform Rating at William Blair, Cites AI Leadership and Explosive Growth in Data Center Revenue
NVIDIA (NASDAQ:NVDA) received a new bullish rating from William Blair, which initiated coverage with an Outperform rating, citing the company's leadership in parallel computing and dominance in the AI sector.
William Blair highlighted NVIDIA's long-standing expertise in designing parallel computing systems, which has driven the company’s expansion into high-growth areas like gaming, automotive, and high-performance computing (HPC). The firm noted that NVIDIA’s data center revenue saw explosive growth of 217% in 2024 and is projected to grow by another 132% in 2025, pushing revenue to over $110 billion, up significantly from $15 billion in 2023.
NVIDIA's growth is largely attributed to its system-level approach, which has expanded its total addressable market (TAM) from GPUs, worth about $100 billion, to encompass the broader $800 billion semiconductor market and the $1.6 trillion cloud services industry.
The report also emphasized NVIDIA’s robust software ecosystem, particularly CUDA, which boasts over 5 million active developers, along with strategic acquisitions like Mellanox and Cumulus, enhancing its capabilities in networking and systems engineering.
