NVIDIA Corp (NVDA) — Q3 2021 Earnings Call Transcript

Thank you. Good afternoon, everyone, and welcome to NVIDIA’s conference call for the third quarter of fiscal 2021. With me on the call today from NVIDIA are Jensen Huang, President and Chief Executive Officer; and Colette Kress, Executive Vice President and Chief Financial Officer. I’d like to remind you that our call is being webcast live on NVIDIA’s Investor Relations website. The webcast will be available for replay until the conference call to discuss our financial results for the fourth quarter of fiscal 2021. The content of today’s call is NVIDIA’s property. It can’t be reproduced or transcribed without our prior written consent. During this call, we may make forward-looking statements based on current expectations. These are subject to a number of significant risks and uncertainties, and our actual results may differ materially. For a discussion of factors that could affect our future financial results and business, please refer to the disclosure in today’s earnings release, our most recent Forms 10-K and 10-Q, and the reports that we may file on Form 8-K with the Securities and Exchange Commission. All our statements are made as of today, November 18, 2020, based on information currently available to us. Except as required by law, we assume no obligation to update any such statements. During this call, we will discuss non-GAAP financial measures. You can find a reconciliation of these non-GAAP financial measures to GAAP financial measures in our CFO commentary, which is posted on our website. With that, let me turn the call over to Colette.

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. First announced on September 1st and ranging in price from $499 to $1,499, these GPUs have generated amazing reviews and overwhelming demand. PC World called them staggeringly powerful, while Newegg cited more traffic than Black Friday. Many of our retail and e-tail partners sold out instantly; the RTX 30 series drove our biggest ever launch. While we had anticipated strong demand, it exceeded even our bullish expectations. Given industry-wide capacity constraints and long cycle times, it may take a few more months for product availability to catch up with demand. In addition to the NVIDIA Ampere GPU architecture, we announced powerful new tools for gamers as well as for tens of millions of livestreamers, broadcasters, eSports professionals, artists, and creators. NVIDIA Reflex is a new technology that improves reaction time in games, reducing system latency by up to 58%. NVIDIA Reflex is being integrated into popular eSports games, such as Apex Legends, Call of Duty: Warzone, Fortnite, and Valorant. NVIDIA Broadcast is a universal plugin for video conferencing and live streaming applications that enhances the quality of microphones, speakers, and webcams with NVIDIA AI effects such as audio noise removal, virtual background effects, and webcam audio frame. With this, remote workers and live streamers can turn any room into a broadcast studio. Blockbuster games continue to adopt NVIDIA’s RTX ray tracing and AI technology. Epic Games announced that Fortnite, which has more than 350 million players worldwide, is adding NVIDIA RTX real-time ray tracing, NVIDIA DLSS AI super-resolution, and NVIDIA Reflex, making the game more beautiful and even more responsive. Other major new titles featuring RTX this holiday season include Watch Dogs: Legion, Call of Duty: Black Ops Cold War, and the much-anticipated Cyberpunk 2077. Gaming laptop demand was also strong with double-digit year-on-year growth for the 11th quarter in a row. NVIDIA GeForce laptops support the most demanding applications for creators and designers while doubling as powerful gaming machines. We also have record gaming console revenue on strong demand for the Nintendo Switch. And we continue to grow our cloud gaming service, GeForce NOW, which has doubled in the past seven months to reach over 5 million registered users. GeForce NOW is unique as an open platform that connects to popular game stores, including Steam, Epic Games, and Ubisoft Connect, allowing gamers access to the titles they already own. 750 games are currently available on GFN, the most of any cloud gaming platforms, including 75 free-to-play games, with more games added every Thursday. GFN supports many popular clients, including PCs, Macs, and Chromebooks. Stay tuned for more devices to come in the near future. In addition, GFN’s reach continues to expand through our telco partners in a growing list of countries, including Japan, Korea, Taiwan, Russia, and Saudi Arabia. We are also providing technology that enables the cloud gaming services to an expanding number of partners. Following our earlier announcement with Tencent, Amazon and Facebook are beginning to offer cloud gaming services powered by NVIDIA. Moving to ProViz, Q3 revenue was $236 million, down 27% year-on-year and up 16% sequentially, ahead of our expectations. Sequential growth was driven by strength in notebooks, which posted record revenue, boosted by work-from-home initiatives and a shift to thin and light mobile workstations. This is particularly offset by decline in desktop workstations, which continued to be impacted by the pandemic and drove the year-on-year decline. From an industry demand perspective, stronger verticals including healthcare, public sector, higher education, research, and financial services, we continue to win new business in a number of areas. In healthcare, we added Medtronic for visual surgical applications and other major companies for medical imaging. In technology and media and entertainment, we gained wins for design, rendering and broadcast applications. During the quarter, we announced the Omniverse, the world’s first 3D collaboration and simulation platform that has entered open beta. Omniverse enables the tens of millions of designers, architects, and creators to collaborate in real-time, on-premises or remotely. Fusing the virtual and physical worlds, Omniverse brings together NVIDIA breakthroughs in graphics, simulation, and AI. It will help enterprises address evolving requirements as workforces become increasingly distributed. Initial market response from this transformative platform has been phenomenal. Over 400 individual creators and developers in diverse industries have been evaluating Omniverse, and early adopters include Ericsson, BMW, Foster and Partners, and Lucasfilm. The pandemic is accelerating development of AR, VR, and mixed reality technologies, which will have a profound impact on how we work and play. For example, our work with NASCAR to enable a variety of AR and VR services at the edge is revolutionizing the racing experience for millions of fans across the globe. With our industry-leading real-time ray tracing graphics, AI, and simulation hardware and software stacks, NVIDIA is in a unique position to enable the future of blending the physical and virtual worlds. Moving to automotive, Q3 revenue was $125 million, down 23% year-on-year and up 13% sequentially. Sequential growth was driven by a recovery in global automotive production volumes, as well as continued growth in AI cockpit revenue. The year-on-year decline was due to the expected ramp-down of legacy infotainment revenue. In September, Mercedes-Benz debuted its redesign of S-Class sedan, featuring an all-new NVIDIA powered MBUX AI cockpit system with an augmented reality heads-up display, AI voice assistant, and rich interactive graphics to enable every passenger in the vehicle to enjoy personalized, intelligent features. Also in September, Li Auto, a leading electric car brand in China, announced that it will develop its next generation of vehicles using the software-defined NVIDIA DRIVE AGX Orin platform. Orin delivers nearly 7 times the performance and 3 times the energy efficiency of our previous generation SOC, making it uniquely capable to power next-generation autonomous electric vehicles. We have excellent traction with EV startups. Finally, last week NVIDIA and Hyundai Motor Group announced that the automaker’s entire lineup of Hyundai, Kia, and Genesis models will come standard with NVIDIA DRIVE in-vehicle infotainment systems, starting in 2022. This feature-rich software-defined computing platform will allow vehicles to be perpetually upgraded with the latest AI cockpit features. Now moving to data center, revenue was a record $1.9 billion, up 162% year-over-year and up 8% sequentially, driving growth with a strong ramp of our A100-based platforms, continued growth with Mellanox, and record T4 shipments for inference. Let me give you a little bit of color on each. Our new NVIDIA Ampere architecture gained further adoption by cloud and hyperscale customers and started ramping into vertical industries. Over the past weeks, Amazon Web Services, Oracle Cloud Infrastructure, and Alibaba Cloud announced general availability of the A100, following Google Cloud platform and Microsoft Azure. A100 adoption by vertical industries drove strong growth, as we began shipments to server OEM partners whose broad enterprise channels reach a large number of end customers. We also ramped the DGX A100 server and began shipping NVIDIA DGX SuperPOD, the first turnkey AI infrastructure. These range from 20 to 140 DGX A100 systems interconnected with Mellanox’s HDR InfiniBand networking and enable customers to install incredibly powerful AI supercomputers in just a few weeks’ time. In fact, we have announced plans to build an 80-node DGX SuperPOD with 400 petaflops of AI performance, called Cambridge-1, which will be the UK’s fastest AI supercomputer. So, it will be used by NVIDIA researchers for collaborative research within the UK’s AI and healthcare community across academia, industry, and startups. It joins other systems in NVIDIA’s complex of AI supercomputers powered by our R&D and autonomous vehicles, conversational AI, robotics, graphics, HPC, and other domains. This includes Selene, now the world’s fifth fastest supercomputer and fastest commercial supercomputer and a new NVIDIA DGX SuperPOD, which ranks first on the Green500 list of the world’s most energy-efficient supercomputers. A great example of the tremendous opportunities for AI in healthcare is our new partnership with GSK for applying computational methods to the drug and vaccine discovery process. GSK’s London-based AI hub will utilize biomedical data, AI methods, and advanced computing platforms to unlock genetic and clinical data with increased precision and scale. In addition to this investment in NVIDIA’s DGX A100 system, GSK will have access to NVIDIA’s Cambridge-1, the NVIDIA drug discovery software, and NVIDIA scientists. In Q3, the A100 swept the industry standard MLPerf benchmark for AI inference performance, following our success in the prior quarter’s MLPerf benchmark for AI training. Notably, our performance in AI inference actually extended compared with last year’s benchmark. For example, in the ResNet-50 test for image recognition, our A100 GPU beat CPU-only systems by 30 times this year versus 6 times last year. Additionally, A100 outperformed CPUs by up to 237 times in the newly added recommendation data test, which represents some of the most complex and widely used AI models on the internet. Our winning performance in AI inference is translating to continued strong revenue growth. Alongside the continued ramp of the A100, T4 sales set a record as the NVIDIA AI inference adoption is in full throttle. We estimate that NVIDIA installed GPU capacity for inference across the seven largest public clouds now exceeds that of the aggregate CPU capacity in the cloud, a testament to the tremendous performance and TCO advantage of our GPUs. Hundreds of companies now operate AI-enabled services on NVIDIA’s inference platforms, including the A100 or T4 GPU, and our Triton inference serving software. For example, Tencent uses NVIDIA AI inference to recommend video, music, news, and apps, supporting billions of queries per day. Microsoft uses NVIDIA AI inference for grammar correction in Microsoft Office, supporting 0.5 trillion queries a year. And American Express uses it for real-time fraud detection. We also gained tremendous traction in supercomputing. We announced that NVIDIA technology, including Ampere architecture GPUs and HDR InfiniBand networking, will power five systems awarded by EuroHPC, a European initiative to build extra scale supercomputing. This includes CINECA, a university consortium in Italy and one of the world’s most important supercomputing centers, which will use NVIDIA’s accelerated computing platform to build the world’s fastest AI supercomputer. CINECA supercomputer named Leonardo advances the age of exascale AI, delivering 10 exaflops of AI performance to enable AI and high-performance computing convergence applications use cases. It is built with nearly 14,000 NVIDIA Ampere architecture-based GPUs and Mellanox HDR 200 gigabit per second InfiniBand networking. And just released top 500 list of supercomputers shows that NVIDIA GPUs or network empower nearly 70% and eight of the ten top supercomputers on the list. Mellanox had another record quarter with double-digit sequential growth well ahead of our expectations, contributing 13% of overall company revenue. The upside reflected sales to China OEM that will not recur in Q4. As a result, we expect a meaningful sequential revenue decline from Mellanox in Q4, but still growing 30% from last year. Mellanox reached record revenue in both InfiniBand and Ethernet, driven by cloud, enterprise, and supercomputing customers. Strong demand for high-performance interconnects, where Mellanox is a leader, is being fueled by AI increasingly complex applications, which demand faster, smarter, more scalable networks. As the data center becomes the new unit of computing in the age of AI, Mellanox networking is foundational to modern scalable architectures. At GTC in October, we unveiled the BlueField-2 DPU, or data processing unit, a new kind of processor, which offloads critical networking, storage, and security tasks from the CPU. A single BlueField-2 DPU can deliver the same data center services that consume up to 125 CPU cores. This frees up valuable CPU cores to run a wide range of other enterprise applications. In addition, it enables zero-trust security features to prevent data breaches and cyberattacks and accelerates overall performance. VMware announced that it will offload, accelerate, and isolate its industry-leading ESXi hypervisor with NVIDIA’s BlueField-2 DPU, boosting vSphere and data center performance and efficiency. We also unveiled our three-year DPU roadmap, unifying Mellanox’s leading network capabilities with NVIDIA’s GPUs and the new NVIDIA DOCA architecture, a software development kit for building DPU-accelerated applications. We believe that over time DPUs will ship in millions of servers, unlocking a $10 billion total addressable market. BlueField-2 is sampling now with major hyperscale customers and will be integrated into the enterprise server offerings of major OEMs. This was our busy period for product launches. Earlier this week at Supercomputing 2020, we announced the new double capacity A100 80 gigabyte GPUs and DGX systems for organizations to build, train, and deploy massive AI models. We also announced the new DGX Station A100, a powerful workgroup server with four A100 GPUs and a massive 320 gigabyte GPU memory for data scientists and AI researchers working in offices, research facilities, labs, or at home. All these additions to the NVIDIA Ampere architecture family of products will be available early next year. At SC20, we also announced the next generation NVIDIA Mellanox 400 gigabit per second InfiniBand architecture, giving AI developers and scientific researchers the fastest available networking performance. This doubles data throughput and adds a new in-network computing engine to provide additional acceleration. Solutions based on this new architecture are expected to sample in the second quarter of calendar 2021. Moving to the rest of the P&L, Q3 GAAP gross margin was 62.6% and non-GAAP gross margin was 65.5%. GAAP gross margin declined year-on-year, primarily due to charges related to the Mellanox acquisition, partially offset by product mix. The sequential increase was driven by the absence of non-recurring inventory step-up expense related to the Mellanox acquisition. Non-GAAP gross margins increased by 140 basis points year-on-year, reflecting a shift in product mix with higher data center sales, including the contribution from Mellanox. Non-GAAP gross margin was down 50 basis points sequentially, in line with our expectations, driven by product mix. Q3 GAAP operating expenses were $1.56 billion and non-GAAP operating expenses were $1.1 billion, up 6% and 42% from a year ago, respectively. Q3 GAAP EPS was $2.12, up 46% from a year earlier, and non-GAAP EPS was $2.91, up 63% from a year ago. Q3 cash flow from operations was $1.28 billion. With that, let me turn to the outlook for the fourth quarter of fiscal 2021. As a reminder, Q4 includes a 14th week, which we expect to be incrementally positive to revenue and operating expenses. We expect gaming to be up sequentially in what is typically a seasonally down quarter, as we continue to ramp up our new RTX 30 Series products. We expect data center to be down slightly versus Q3. With that, we expect computing products to grow in the mid-single digits sequentially, more than offset by a sequential decline in Mellanox. We expect continued sequential growth in auto and ProViz but not yet returning to year-on-year growth. And we expect a seasonal decline in OEM. Revenue is expected to be $4.8 billion, plus or minus 2%. GAAP and non-GAAP gross margins are expected to be 62.8% and 65.5%, respectively, plus or minus 50 basis points. GAAP and non-GAAP operating expenses are expected to be approximately $1.64 billion and $1.18 billion, respectively. GAAP and non-GAAP other income and expenses are both expected to be an expense of approximately $55 million. GAAP and non-GAAP tax rates are both expected to be 8%, plus or minus 1%, excluding discrete items. Capital expenditures are expected to be approximately $300 million to $325 million. Further financial details are included in the CFO commentary and other information available on our IR website. In closing, let me highlight upcoming events for the financial community. We’ll be virtually attending the Credit Suisse Technology Conference on November 30th, Wells Fargo TMT Summit December 1st, and the UBS TMT Conference on December 7th. Our earnings call to discuss the fourth quarter and full-year results is scheduled for Wednesday, February 24th. We will now open the call for questions. Operator, would you please poll for questions?

Can you hear me?

Yes.

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 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 into ‘20, but you’re still growing significantly year-over-year, or how would you characterize the macro backdrop?

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 meaningfully 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 to Jensen to see if he has more that he would like to add.

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 has proven to be really hard. The models are diverse when you count vision, language, and 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, 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, which 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.

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?

Yes, John, you make an excellent point. It's evident that the inability to work on-site is hindering the adoption of new technologies in some sectors. However, we are observing swift adoption in certain areas, such as the use of AI in healthcare for rapid vaccine discovery and early outbreak detection, as well as robotic applications. In sectors like warehouses, digital retail, and last-mile delivery, there is substantial enthusiasm for implementing new AI and robotics technologies. Conversely, more traditional industries are experiencing delays in deploying new capabilities and technologies. I’m particularly excited about our work in enabling remote collaboration through our Omniverse platform, which is currently in early beta. The marketplace feedback has been very positive, and I anticipate sharing more updates about Omniverse in the coming months. I strongly believe that as the industry bounces back, our primary goal as a company will remain to tackle the significant challenges that cannot be solved by standard computing. These challenges pertain to major applications in the sectors we focus on, which are not merely commodity applications but rather impactful and transformative. I have full confidence that, with the recovery of industries, we will see the design of cars, planes, ships, and buildings, along with a surge in design, simulation, and robotics applications.

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?

Yes. Colette, do you want me to take that real quick and maybe you can help me out?

Yes, absolutely.

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 are 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. This is kind of expected; it’s been a decade since we’ve invented a new type of computer graphics. I mean, two years ago, we invented a new standard 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. We invented NVIDIA RTX to do that. 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. At this point, it’s defined the next-generation content. 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 expects. Now, the demand is just overwhelming. We’re going to continue to ramp fast. This is going to be one of our most successful ramps ever. It gives our installed base of some 200 million-plus GeForce gamers the best reason to upgrade in over a decade. This is going to be a very large generation for us, is my guess. Regarding data centers, we are increasing our deployment of A100. A100 represents our first generation of GPUs capable of performing multiple tasks simultaneously. We refer to it as universal because it can handle all the applications that previously required several GPUs. It excels at training, performs exceptionally well in inference, high-performance computing, and data analytics. The Ampere architecture allows for simultaneous execution of all these functions. The efficiency and effectiveness for data centers are impressive, and the response has been very positive. We are expanding into all major cloud providers globally. As of this quarter, we are now present with every significant cloud provider, including Alibaba, Amazon, Azure, and Google Clouds. We will continue to expand in this area. We are also beginning to enter the enterprise sector, which I believe will offer the most significant growth opportunity for us in the long run, transforming every industry through AI and creating an impactful moment similar to the introduction of the iPhone for major industries worldwide. We are moving forward with this initiative and are witnessing a lot of excitement.

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 gaming and data center? And then, how should we think about it impacting seasonality into Q1 as that extra week rolls off?

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 impacts on revenue, although it is tough to quantify. Our outlook also reflects incremental OpEx for Q4 in primarily two different areas in terms of compensation and depreciation. Given that our employees comprise such a material part of our OpEx, 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 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 flat as we move from Q4 to Q1.

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. 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.

Thanks, Vivek. I believe that nearly all cloud vendors utilize similar infrastructures for their internal and external clouds. The competition is quite strong, which indicates that acceleration is the ideal approach for training and inference. Most training models are rapidly increasing in size, which drives high demand for our solutions. Regarding inference, a significant portion is not being handled by CPUs, and it’s clear that using accelerators for inference is the best path forward. When this shift occurs, our accelerator stands out as the most versatile and high-performing option, allowing us to innovate quickly. We’re deeply committed to this area and have the largest dedicated team globally. Our technology is highly advanced, offering great versatility and performance. We have seen announcements from our largest customers, and we are making solid progress with companies like Google, Amazon, Microsoft, Alibaba, Oracle, and others. The main point is that a large volume of AI workloads still rely on CPUs, which positions us well for accelerated workloads. We believe we are the leading accelerator globally, and this presents a significant growth opportunity for us in the short term, perhaps our largest one. We are just beginning to tap into this potential.

Good afternoon. Thanks for taking my question, and great job on the quarterly execution. The Mellanox networking connectivity business was up 80% year-on-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-on-year last quarter, and you’re still expecting 30% year-on-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? 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?

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 supercomputing; and then hyperscale and enterprise, which is about 50-50. Of the data center business, the accelerated computing part is not very much associated with digestion. 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 those workloads we’ve completed, the porting to our accelerators, and getting them ready for deployment. Those are the factors associated with accelerated computing. It’s really about the apps, it’s really about the workloads, and it’s really driven by AI. On the other hand, the networking part of our business is more connected to the CPU business because they’re much more broad-based. The networking part of our business is driven by this idea of a new hyperscale data center architecture called disaggregation. It’s software disaggregation, not necessarily hardware disaggregation. Software disaggregation, where this type of software called Kubernetes orchestrates microservices that are deployed across the data center. 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 in the data center. This disaggregation has caused the networking between the compute nodes to be of all vital importance. Because Mellanox is the lowest-latency, highest-performance, highest-bandwidth network, you can get the TCO benefit at the data center scale is really fantastic. When they’re building out data centers, Mellanox is going to be much more connected to that. On the enterprise side, 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, pulling back by a quarter. So, those are kind of the dynamics of it. The net is that it’s 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. That drives our computing business. The networking business has everything to do with the architecture of cloud data centers, which is architected with microservices now. 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.

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 seem to be some offsetting factors. I wonder if you feel like your core data center revenue is still being constrained right now by some market digestion, and how you sort of balance or handicap these two factors? Thanks.

Our near-term growth is primarily influenced by the manufacturing cycle time and supply flexibility. We are in a solid position, and all our supply contributes to our guidance. However, we would benefit from shorter cycle times and more agile supply chains. The current global situation presents some constraints, but we are determined to optimize our circumstances. Despite these challenges, everything is aligning with our guidance, and we anticipate growth.

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%. The simple question is how do you think about the growth rate for Mellanox going forward? 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.

Long term, every computer in the world will be built like a data center. Every node of a data center is going to be a data center in itself. The reason for that is we want the attack surface to be basically zero. Today, most of the data centers are only protected as a periphery. But in the future, if you’d like cloud computing to be the architecture for everything, then every data center needs to be multi-tenant, every data center needs to be secure. You’re going to have to secure every single node. Each of those nodes are going to be software-defined networking, software-defined storage, and it’s going to have per-application security. The processing load to offload the CPUs is significant. We believe that somewhere between 20% to 40% of today’s cloud data centers’ capacity and computational load is consumed running the infrastructure overhead. That’s what the DPUs were designed to do. We’re going to offload that; and, number two, we’re going to make every single application secure. Confidential computing, zero-trust computing will become a reality. The importance of this initiative is tremendous. Therefore, I believe every single server in the world will have a DPU inside someday, just because we care so much about security and throughput and TCO. I expect our DPU business to be quite large. That’s the reason why we’re putting so much energy into it. It’s a programmable data center on a chip, think of it that way, and data center infrastructure on a chip. That’s 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, and bringing it on BlueField. This is a very important initiative for us. I’m very excited about it, as you can imagine.

Yes. Thank you very much, Colette, and I apologize if I missed it, but for Mellanox, do you expect it to return to a growth trajectory on a sequential basis in the April quarter? I’m assuming that the shortfall in the current quarter is due to a pull-in from Huawei?

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. 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.

At the highest level, Colette, it’s safe to say that high-speed networking will be one of the most crucial aspects of cloud data centers moving forward. Most of the world’s data centers are still designed for traditional hyper-converged architecture, but there is a shift happening towards software-defined disaggregated architectures. This transformation is still in its early stages. I fully expect that all future cloud data centers will be connected through high-speed networking. This is known as east-west traffic. All traffic will be secured. Imagine having firewalls integrated into every server and every internal transmission within the data center operating at high speed and being fully encrypted. A significant amount of computation will need to be incorporated into future data centers. Our networking business, Mellanox, is just beginning its growth journey.

Great, thanks for taking my question. You’ve given us some pieces of this puzzle. 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 a sort of this refresh, it sounds like, with double the memory on the A100. Is the T4 going to be refreshed? 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?

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. The way that you could think through it, you could reverse engineer it; you know what our gaming lineup looks like for desktops. Traditionally, we try to have a new architecture in every single segment. We’ve not gone below $499 yet, so there’s a very big part of the marketplace that we’re still processing. Then the second thing is laptops; none of the Ampere architecture has launched for laptops. There’s workstations. Do the same thing with desktops and workstations and laptops workstations. None of those have gone out yet. Then, there’s data center. Our data center business for cloud, you’ve seen some of the early versions of it, A100. Then, there’s cloud computing for graphics, for cloud gaming. For those enterprise applications, enterprise data analytics applications. There are a fair number of exciting new products we still have in front of us.

Actually, that will be for Jensen.

Okay. Thank you. This was a terrific quarter. NVIDIA is firing on all cylinders. The RTX has reinvented graphics and has made real-time ray tracing the standard of the next-generation content, creating the best-ever reason to upgrade for hundreds of millions of NVIDIA gamers. AI, where software writes software no human 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. 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. Please stay safe, and I look forward to seeing you guys next time.