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.
Wolfe Research Raises NVIDIA Price Target to $150, Citing Strong Supply Chain Growth
Wolfe Research analysts increased their price target for NVIDIA (NASDAQ:NVDA) to $150 from $125 per share, citing promising supply chain checks that indicate substantial growth for the company in 2025.
According to the research note, recent supply chain data points to over 50% content growth for NVIDIA GPUs in 2025. This growth is attributed to the transition to Nvidia's new Blackwell platform, which promises higher average selling prices (ASPs) and an improved product mix.
Wolfe Research also anticipates potential unit growth, noting early indications of a 50% increase in GPU units for 2025. While this figure is approached cautiously in their current estimates, it is acknowledged as a potential upside to their revised projections. Nvidia's data center business is highlighted as a key growth driver, with at least 50% growth expected in 2025. This is supported by factors such as cloud service providers adopting the Blackwell platform, better allocations for enterprise customers, and additional revenue streams from "Sovereign AI."
The report also anticipates higher networking attach rates for Nvidia's GB200, including both InfiniBand and NVDA Spectrum-X solutions, which are essential for optimizing AI cluster performance.
Based on these revised estimates, Wolfe Research projects Nvidia's 2026 revenue to reach $177.0 billion and EPS to hit $4.03. The new $150 price target is based on a valuation of approximately 37 times their 2026 EPS, consistent with Nvidia's historical averages. Wolfe Research maintains their Outperform rating for Nvidia, emphasizing the company's strong earnings momentum and long-term potential in the AI sector. They note Nvidia's significant outperformance compared to broader markets and its peers in the semiconductor industry.
New Street Research Downgrades NVIDIA Amid Uncertain Growth Outlook
New Street Research analysts downgraded NVIDIA (NASDAQ:NVDA) to Neutral from Buy with a price target of $135 on the stock. The analysts explained that current consensus expectations project a 35% increase in GPU revenues for 2025, aligning with previous predictions. They see limited further upside based on information from the value chain. The downgrade to Neutral reflects a belief that significant upside will only occur under a bullish scenario where the outlook beyond 2025 improves significantly, a scenario the analysts do not yet fully support.
The analysts also noted that the current consensus anticipates revenue growth slowing to the mid-teens, potentially threatened by slowing hyperscale capital expenditures and increased competition from ASICs and AMD. If these factors remain constant, the analysts see no further upside for NVIDIA stock and even a risk of derating, as the stock is currently trading at 40 times next-twelve-months EPS, compared to a trough of 20 times when growth slowed to 10% in 2019.
Analysts’ Perspective on Nvidia’s Becoming the World's Most Valuable Company
Nvidia (NASDAQ:NVDA) achieved the title of the world's most valuable company, surpassing both Microsoft and Apple. Analysts at Wedbush predict that the competition to reach a $4 trillion market cap will be a major focus over the next year, particularly among these three tech giants.
Wedbush analysts highlighted Nvidia's GPU chips as crucial assets in the tech sector, likening them to the new gold or oil, given the ongoing advancements of the 4th Industrial Revolution. They emphasized that Nvidia's leading position in data center AI spending makes it a key player in the AI revolution, with generative AI applications heavily dependent on its GPUs. This dominance positions Nvidia and Microsoft as the main beneficiaries of the AI trend, with emerging secondary and tertiary impacts further supporting a bullish tech outlook for 2024 and 2025.
The investment firm forecasts that over the next three years, more than 70% of enterprises will integrate AI use cases, resulting in an estimated $1 trillion in additional AI spending over the next decade.
For Apple, the AI opportunity is significant in two key areas, according to Wedbush analysts. The introduction of its AI strategy could initiate a major iPhone upgrade cycle among its extensive user base, while developers are expected to create a multitude of apps on Apple's AI platform, potentially leading to the creation of a new AI App Store. Analysts believe this will become the primary way consumers engage with generative AI.
Despite being a latecomer to the AI space, Apple, with its vast consumer base, has a unique opportunity to capitalize on the AI market. Wedbush's team described this moment for Apple as a pivotal "1995 Moment," where the company could effectively monetize the burgeoning AI trend.
Nvidia Upgraded by Oppenheimer Signals Positive Outlook
- Oppenheimer upgraded Nvidia to Outperform and raised its price target from $110 to $150.
- Nvidia completed a 10-for-1 stock split, aiming to make shares more accessible and potentially attract more investors.
- Despite concerns over high valuation and stock-based compensation expenses, the strategic stock split and sector expansion present growth opportunities.
On Tuesday, June 11, 2024, Oppenheimer upgraded its rating on Nvidia (NASDAQ:NVDA) to Outperform, maintaining a hold position on the stock. At the time of the announcement, NVDA was trading at $121.79. This decision was highlighted in a report by TheFly, where Oppenheimer also raised its price target for Nvidia from $110 to $150, signaling a positive outlook on the company's future performance. Nvidia, a leading force in the technology sector, especially known for its contributions to the gaming industry and artificial intelligence (AI) sector, has recently completed a 10-for-1 stock split. This move aimed to make shares more accessible and affordable, potentially attracting more investors.
The stock split, executed after Nvidia's shares experienced a remarkable surge of nearly 600% over the past three years, reflects the company's strong performance and growing investor interest. Initially recognized for its powerful graphics processing units (GPUs) used in gaming, Nvidia has expanded its reach into the AI sector, where its GPUs and other AI-focused products have seen soaring demand. This strategic expansion has significantly contributed to Nvidia's earnings, which have increased in the triple digits in recent quarters.
Despite the stock split not altering Nvidia's fundamentals or valuation, it is anticipated to fuel the ongoing rally in Nvidia's stock. The more affordable share price post-split is expected to encourage both new investors and current shareholders to invest more in NVDA, possibly driving the stock's price even higher. This move comes at a time when Nvidia's market capitalization stands impressively at about $2.97 trillion, with a trading volume of roughly 306 million shares, indicating strong market interest and confidence in the company's future.
However, concerns have been raised regarding Nvidia's high valuation and the company's substantial stock-based compensation expenses, which are seen as significant risks. These financial considerations are crucial for investors to keep in mind, especially in comparison to other investment opportunities in the market. Despite these concerns, the positive outlook from Oppenheimer, coupled with the strategic stock split, presents a compelling case for potential growth in Nvidia's stock value.
Investors are advised to exercise caution due to these financial considerations, as highlighted by The Motley Fool. The strategic move to execute a 10-for-1 stock split, making Nvidia's shares more accessible, contrasts with the concerns over the company's valuation and compensation expenses. This juxtaposition of strategic growth initiatives against financial risks underscores the complexity of investment decisions in the rapidly evolving technology sector.
NVIDIA Corporation's Strategic Stock Split and Market Performance
- NVIDIA Corporation announced a 1 for 10 stock split, aiming to make shares more accessible without altering the investment's overall value.
- The company's stock has seen a 36% increase over the past month, briefly surpassing Apple in market capitalization, driven by advancements in AI and data center solutions.
- Despite the stock split being a neutral event, NVIDIA's robust growth in the tech industry and its potential for future profitability keep it a significant player in the stock market.
NVIDIA Corporation (NASDAQ:NVDA) recently announced a 1 for 10 stock split, a strategic move that adjusts the number of shares for investors without altering the overall value of their investment. This decision comes at a time when NVIDIA is under the spotlight in the stock market, alongside GameStop (NYSE:GME), for experiencing significant surges in stock prices. Evercore, a Wall Street researcher, has pointed out these companies as examples of market "froth," yet NVIDIA's stock is predicted to reach $150 per share (split-adjusted) by the end of summer. This forecast is based on financial analysis rather than speculative mania, recognizing NVIDIA's potential for substantial future profits.
NVIDIA's stock has seen an impressive 36% increase over the past month, briefly surpassing Apple to become the world's second-largest stock by market capitalization. This surge in stock price reflects Wall Street's confidence in NVIDIA's future profitability, driven by its advancements in artificial intelligence (AI) and data center solutions. The company's transition from a gaming chip specialist to a leading force in AI has resulted in extraordinary stock performance, with annual returns reaching 50%, translating to an investment growth of more than 437 times over 15 years.
The recent 10-for-1 stock split marks NVIDIA's sixth such operation, with the previous one occurring in 2021. While stock splits are generally viewed as neutral events that do not directly influence a stock's buy or sell momentum, they can make shares more accessible to a broader range of investors by reducing the price per share. However, it's crucial to note that these splits do not change the company's overall market value or stock valuation. NVIDIA's history post-split could offer insights into its potential performance moving forward as the company continues to dominate the tech industry with its robust growth.
As of the latest trading data, NVIDIA's stock price stood at $1,208.88, experiencing a slight decrease of $1.1 or -0.09%. The stock has fluctuated between a low of $1,180.23 and a high of $1,216.92 throughout the trading day. Over the past year, NVIDIA's shares have reached a peak of $1,255.87 and a low of $385.67. With a market capitalization of approximately $2.97 trillion and a trading volume of about 40.05 million shares, NVIDIA continues to be a significant player in the stock market, reflecting its strong position in the tech industry and its potential for continued growth and profitability.
Nvidia Hits $3 Trillion Market Cap, Becomes World's Second Most Valuable Company Ahead of Apple
Nvidia (NASDAQ:NVDA) saw its shares inch up in pre-market trading today, suggesting the continuation of a rally from Wednesday. This surge has propelled the AI chip designer's market value beyond $3 trillion, surpassing Apple to become the second most valuable company globally.
The surge in Nvidia's value is largely attributed to the growing excitement around AI applications. Over the past year, the demand for its AI-optimized chips has increased significantly as more companies invest heavily in integrating this emerging technology into their operations.
In a surprising development earlier this week, Nvidia announced the upcoming release of its new "Rubin" chip, only a few months after its last product launch. This move comes as the company faces stiff competition from other chipmakers like Advanced Micro Devices and Intel, as well as from custom processors developed by major cloud computing companies such as Microsoft and Google.
Bank of America Boosts NVIDIA Price Target to $1,500
Bank of America analysts raised their price target for NVIDIA (NASDAQ:NVDA) to $1,500 from $1,320, while maintaining their Buy rating on the stock.
This target increase follows NVIDIA CEO's keynote speech at the Computex annual computer expo in Taiwan, highlighting new product announcements that reinforce NVIDIA's leadership in AI. Bank of America emphasized the new GB200 NVL2 platform and the MGX modular reference design platform as key developments.
The bank noted that NVIDIA is targeting the creation of large GPU clusters for major hyperscalers by 2026, which could significantly increase unit sales. Additionally, NVIDIA is focusing on mainstream and enterprise AI applications with its smaller NVL2 and modular MGX platforms.
Bank of America believes NVIDIA's clear multi-generational roadmap and extensive product portfolio are crucial growth drivers. NVIDIA remains the bank's top pick in the chipmaker sector.
