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’s Price Target Cut at UBS
UBS analysts adjusted their price target for NVIDIA (NASDAQ:NVDA) to $1,150, down from $1,200, while maintaining their Buy rating on the stock. The revision comes ahead of NVIDIA's upcoming earnings release scheduled for May 22. Citing strong ongoing demand, UBS has also updated its revenue projections for NVIDIA.
The bank's analysts remain optimistic about NVIDIA's Blackwell and Hopper products, despite some concerns over the timing of shipments. While shipments for Blackwell are expected by December, the demand for Hopper is anticipated to remain strong, especially as it leads up to a significant product transition.
The demand for Blackwell, particularly in terms of system mix, has led UBS to revise its revenue and earnings forecasts upward for the 2025 calendar year. They now project NVIDIA's revenue to reach around $175 billion and earnings per share to approximate $41, markedly higher than the consensus estimates of $136 billion in revenue and $30 earnings per share.
NVIDIA Corporation Gains Investor Attention Amidst Growth in GPUs, AI, and Data Centers
NVIDIA Corporation (NVDA:NASDAQ) Gains Investor Attention
NVIDIA Corporation (NVDA:NASDAQ) has recently become a focal point for investors, marking its position as one of the most closely monitored stocks on Zacks.com. This heightened interest in NVDA is not without reason. The company, known for its groundbreaking advancements in graphics processing units (GPUs) for gaming and professional markets, as well as its foray into artificial intelligence (AI) and data center technologies, has shown promising potential for growth. This potential is a key driver behind its popularity among investors who are always on the lookout for stocks that could offer substantial returns.
The surge in NVDA's attention can be attributed to several factors. Firstly, the company's innovative edge in the GPU market has established it as a leader in the gaming industry, which continues to see exponential growth. Gamers and professionals alike rely on NVIDIA's technology for the best visual and performance experience. Secondly, NVIDIA's strategic expansion into AI and data center operations has opened new revenue streams. These sectors are rapidly growing, and NVIDIA's contributions are becoming increasingly critical, making it an attractive investment.
Moreover, NVIDIA's financial performance has been robust, with consistent revenue growth and strong profit margins. This financial health reassures investors of the company's stability and its ability to navigate through market fluctuations. Additionally, NVIDIA's research and development efforts ensure that it stays ahead of the curve, further solidifying its position in the market and making it a compelling choice for investors.
The interest in NVDA on platforms like Zacks.com reflects the broader market sentiment towards the stock. Analysts and investors alike are keenly watching NVIDIA's moves, as its technologies play pivotal roles in several high-growth industries. With the ongoing advancements in gaming, AI, and data centers, NVIDIA is well-positioned to capitalize on these trends, making it a noteworthy stock for investors to consider.
In conclusion, the surge in interest towards NVIDIA Corporation (NVDA) among investors is grounded in the company's innovative leadership, financial strength, and strategic positioning in high-growth markets. As it continues to push the boundaries of technology, NVDA remains a stock to watch, offering potential for significant returns. For those looking to dive deeper into NVIDIA's prospects, Zacks Investment Research provides comprehensive analyses and insights.
Nvidia Corp. and the AI Technology Surge: A Financial Analysis
Nvidia Corp. (NVDA:NASDAQ) and the AI Technology Surge
Nvidia Corp. (NVDA:NASDAQ) has been a standout performer in the stock market, largely due to the burgeoning demand for artificial intelligence (AI) technologies. This demand has not only propelled Nvidia's stock by an impressive 220% over the past year but has also positioned the company well beyond the confines of a typical chip manufacturer. As reported by Market Watch on April 16, 2024, Nvidia's broadening horizon into AI and other tech sectors has sparked predictions of a further 30% surge in its stock value. This optimism is rooted in the company's recent financial achievements, which reflect a robust growth trajectory and operational efficiency.
Nvidia's Financial Growth: A Closer Look
Delving into Nvidia's financials, the company has reported a remarkable 22% increase in revenue growth, underscoring a significant uptick in sales. This growth is a testament to the strong market demand for Nvidia's products, particularly in the AI sector. Moreover, the company's gross profit growth of approximately 25% indicates an improvement in profitability, suggesting that Nvidia is not only increasing its sales but is also becoming more efficient in its cost management.
The financial health of Nvidia is further highlighted by its net income growth of about 33% and operating income growth of around 31%. These figures reflect a substantial boost in the company's bottom line and efficient management, respectively. Nvidia's ability to enhance its operational performance while expanding its profit margins is a clear indicator of its strong market position and operational excellence.
Additionally, Nvidia's asset growth of about 21% and a minimal debt growth of 0.3% reveal a solid expansion in its asset base without significantly increasing its leverage. This strategic financial management has enabled Nvidia to maintain a healthy balance sheet. The standout growth in free cash flow by nearly 59% and operating cash flow by approximately 57% further emphasizes Nvidia's exceptional cash generation capabilities. These metrics not only demonstrate Nvidia's financial robustness but also its potential for sustained growth and investment in future innovations.
The observed 29% growth in book value per share is another positive sign for investors, indicating an increase in shareholder equity. This growth, coupled with the company's minimal increase in debt, underscores Nvidia's strong financial position and operational efficiency. As Nvidia continues to capitalize on the growing demand for AI and expand its market reach, its financial growth metrics provide a solid foundation for the optimistic outlook presented by Market Watch.
Nvidia's Market Surge: A Financial Performance Analysis
Nvidia's Impressive Market Surge and Financial Performance
Nvidia (NVDA:NASDAQ) has seen its stock price soar by over 230% in the past year, a testament to the company's strong market presence and the positive sentiment from consumers and investors alike. This surge in stock value is not just a reflection of market optimism but is deeply rooted in Nvidia's impressive financial achievements and operational efficiency. As reported by Megan Brantley from LikeFolio on the Schwab Network, this growth trajectory places Nvidia in a favorable position, indicating a robust outlook for the company.
The financial prowess of Nvidia is evident in its recent quarterly report, which showcases a revenue of $22.1 billion and a gross profit of $16.79 billion. These figures are significant, as they highlight Nvidia's ability to not only generate substantial sales but also to retain a large portion of these revenues as profit, after accounting for the cost of revenue which stands at about $5.31 billion. The operating expenses, totaling roughly $3.18 billion, further underscore the company's efficiency in managing its costs, contributing to its overall financial health.
Nvidia's operational efficiency is further demonstrated by its asset turnover ratio of 0.93 over the trailing twelve months (TTM), indicating the company's effectiveness in utilizing its assets to generate sales. This is complemented by an inventory turnover ratio of approximately 3.15, which shows how Nvidia is able to sell and replenish its inventory effectively throughout the year. Moreover, an operating profit margin of 54.12% TTM is a clear indicator of Nvidia's capability to control its operational costs and maximize profitability, which is crucial for sustaining growth and delivering value to shareholders.
The balance sheet of Nvidia reveals a strategic allocation of resources, with about $5.28 billion held in inventory and approximately $5.26 billion in net property, plant, and equipment. These investments are indicative of Nvidia's commitment to bolstering its operational capabilities and infrastructure, ensuring the company remains at the forefront of technological advancements and market demands. This strategic investment not only supports Nvidia's current growth but also lays the foundation for future expansion and market dominance.
In summary, Nvidia's remarkable year-over-year stock price increase is a reflection of its strong financial performance, operational efficiency, and strategic investments. The company's ability to generate significant revenue and profit, coupled with its effective use of assets and management of operational costs, positions Nvidia as a leader in the market. These financial and operational metrics not only validate the positive consumer sentiment towards Nvidia but also highlight the company's potential for sustained growth and profitability in the future.
NVIDIA Named a New Top Pick at Cantor
Cantor Fitzgerald analysts maintained their Overweight rating and a $1,200 price target on NVIDIA (NASDAQ:NVDA), highlighting the continued strong momentum in AI as a driving force for the company, anticipating another significant beat and raise in performance.
With a growing range of AI applications and increasing adoption rates, NVIDIA is expected to see further benefits from the launch of its Blackwell product in the fourth quarter of 2024, potentially accelerating revenue through 2025 and supporting EPS projections between $30-35. Given its current trading at 29 times the lower end of this EPS range, NVIDIA is viewed as attractively valued as a principal facilitator and beneficiary of AI advancements. NVIDIA remains a top pick for Cantor Fitzgerald, with upcoming earnings anticipated to serve as a catalyst for further stock appreciation.
NVIDIA’s Price Target Raised at Piper Sandler
Piper Sandler analysts boosted their price target on NVIDIA Corporation (NASDAQ:NVDA) to $1,050 from $850, maintaining an Overweight rating. Following the GTC conference, where NVIDIA made numerous product and partnership announcements, the analysts highlighted the introduction of the Blackwell GPU architecture, which succeeds the Hopper architecture.
This new development is seen as bolstering NVIDIA's already dominant position in the hardware market. NVIDIA is praised as the premier provider of a complete hardware and software suite for the shift to accelerated computing and generative AI over the next decade. Notably, NVIDIA accelerated its release schedule to one major product launch annually starting this year.
NVIDIA’s Price Target Raised at Mizuho
Mizuho analysts increased their price target for NVIDIA Corporation (NASDAQ:NVDA) to $1,000 from the previous $850, while maintaining a Buy rating on the stock. The analysts emphasized NVIDIA as the leading beneficiary in the near-term artificial intelligence (AI) landscape, with AMD and Broadcom also gaining significant benefits.
The analysts anticipate strong momentum in NVIDIA's AI-driven revenue through 2024/25, underpinned by the GH200, B100, and B200 models, forecasting data center revenues to reach approximately $89 billion in 2024, with potential for further upside. By 2027, AI data center revenues could approach $280 billion, with NVIDIA at the forefront and AMD and Broadcom experiencing robust growth in their AI segments.
Specifically, AMD is expected to be a major player in the expanding AI GPU market, potentially achieving AI revenues of around $4-5 billion in 2024, significantly exceeding current projections, and possibly hitting around $18 billion by 2027. Broadcom, with its custom silicon solutions for customers, is poised to see its AI revenues increase from an estimated $8 billion in 2024 to possibly $20 billion in 2027, positioning it strongly in the AI technology race.
