NVIDIA Corporation

Good afternoon. My name is David and I will be your conference operator today. At this time, I would like to welcome everyone to NVIDIA's financial results conference call. All lines have been placed on mute to prevent any background noise. After the speaker's remarks, there will be a question and answer session. If you would like to ask a question during this time, simply press star followed by the number one on your telephone keypad. If you would like to withdraw your question, press the pound key. Thank you. Simona Jankowski, you may begin your conference.

Thank you. Good afternoon, everyone, and welcome to NVIDIA's conference call for the second quarter of fiscal 2021. With me on the call today from NVIDIA are Johnson Wang, President and Chief Executive Officer, and Colette Tress, 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 third quarter of SHISCO 2021. The content of today's call is NVIDIA's property. It can 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 Form 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, August 19, 2020, based on information currently available to us. accepted 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. Thanks, Simona.

Q2 was another extraordinary quarter. The world continued to battle the COVID-19 pandemic, and most of our employees continued to work from home. But through the team's agility and dedication, we successfully combined Mellanox into NVIDIA while also delivering a very strong quarter. Revenue was $3.87 billion, up 50% year-on-year, up 26% sequentially, and well ahead of our outlook. Starting with gaming, revenue was $1.65 billion with up 26% year-on-year and up 24% sequentially, significantly ahead of our expectations. The upside was broad-based across geographic regions, products, and channels. Gaming's growth amid the pandemic highlights the emergence of a leading form of entertainment worldwide. For example, the number of daily gamers on Steam, a leading PC game online distributor, is up 25% from pre-pandemic levels. An NPD reported that U.S. consumer spending on video games grew 30% in the second calendar quarter to a record $11 billion. NVIDIA's PCs and laptops are ideal for the millions of people who are now working, learning, and gaming at home. At the outset of the pandemic, many retail outlets were closed and demand shifted to online channels. As the quarter progressed and the stores reopened, retail demand picked up, iCafes largely reopened, and online sales continued to thrive. Gaming laptop demand is very strong as students and professionals turn to GeForce-based systems to improve how they work, learn, and game from home. We've ramped over 100 new models with our OEM partners, focused on both premium and mainstream price points. In the premium laptop segment, we delivered unparalleled performance with the GeForce RTX 2080 and the 2070 Super GPUs in thin and light form factors. We also brought ray tracing to gaming laptops for the first time at price points as low as $999 with the GeForce RTX 2060. In the mainstream segment, we brought the GeForce GTX to laptop press points as low as 699. Momentum continues for our Turing architecture, which enables stunning new visual effects in games and is driving powerful upgrade cycle among gamers. Its RTX technology adds ray tracing and AI to programmable shading and has quickly redefined the new standard for computer graphics. DLSS used the AI capabilities of Turing to boost frame rates by almost 2x while generating crisp image quality. RTX support in blockbuster games continues to grow, including MegaHit, Death Stranding, the high-anticipated Cyberpunk 2077, and the upcoming release of Watch Dogs. These games join Minecraft and other major titles that support NVIDIA, RTX ray tracing, and DLSS. We're in the midst of a 21-day countdown campaign promoting a GeForce special event on September 1st, with each day highlighting a year in the history of GeForce. We don't want to spoil the surprise, but we encourage you to tune in. We are very pleased with the traction of our GeForce Now cloud gaming service, now in its second quarter of commercially availability. DSN offers the richest content to any game streaming service through partnerships with leading digital game stores, including Valve Steam, Epic Games, and Ubisoft Uplay. GeForce Now enables users with underpowered PC, maps, or Android devices to access powerful GPUs to play their libraries of PC games in the cloud, expanding the universe of gamers that we can reach with GeForce. Just yesterday, we announced that GFN is now supported on Chromebooks, further expanding our reach into tens of millions of users. In addition to NVIDIA's own service, GFN is available or coming soon to a number of telecom partners around the world, including SoftBank and KDDI in Japan, Rokoscom and Beeline in Russia, LGU Plus in South Korea, and Taiwan Global. Moving to ProBiz, in Q2, was $203 million in revenue, down 30% year-on-year and down 34% sequentially, with declines in both mobile and desktop workstations. Sales were hurt by lower enterprise demand and the closure of many offices around the world. Industries negatively impact during the quarter include automotive, architectural engineering and construction, manufacturing, media and entertainment, and oil and gas. Initiatives by enterprises to enable remote workers drove demand for virtual and cloud-based graphic solutions. Accordingly, our Q2V GPU bookings accelerated, increasing 60% year-on-year. Despite near-term challenges, we are winning new business in areas such as healthcare, including Siemens, Volks, and General Electric, and the public sector. We continue to expand our market opportunity with over 50 leading design and creative applications that are NVIDIA RTX enabled, including the latest release from Foundry, Chaos Group, and Maxon. These applications provide faster ray tracing and accelerated performance, improving creators' design work tools. The pandemic will have a lasting impact on how we work. Our revenue mix going forward will likely reflect this evolution in enterprise workforce trends with a greater focus on technologies such as NVIDIA laptops and virtual workstations that enable remote work and virtual collaboration. Moving to automotive, automotive revenue was 111 million, down 47% year on year and down 28% sequentially. This was slightly better than our outlook of a 40% sequential decline, as the impact of the pandemic was less pronounced than expected, with auto production volumes starting to recover after bottoming in April. Some of the decline was also due to the roll-off of legacy infotainment revenue, which will remain a headwind in future quarters. In June, we announced a landmark partnership with Mercedes-Benz, which starting in 2024, will launch software-defined intelligent vehicles across an entire fleet in using end-to-end NVIDIA technology. Mercedes will utilize NVIDIA's full technology stack, including the Drive AGX computer, Drive AV autonomous driving software, and NVIDIA's AI infrastructure, spanning from the car to the cloud. Centralizing and unifying computing in the car will make it easier to integrate and upgrade advanced software features as they are developed. With over-the-air updates, vehicles can receive the latest autonomous driving and intelligent cockpit features, increasing value and extending the joy of ownership with each software upgrade. This is a transformative announcement for the automotive industry, making the turning point of traditional vehicles becoming high-performance, updatable data centers on wheels. It's also a transformative announcement for NVIDIA's evolving business model as the software content of our platforms grows, positioning us to build a recurring revenue stream. Moving to data centers. Data Center is a diverse, consists of cloud service providers, public cloud providers, supercomputing centers, enterprises, telco, and industrial edge. Future revenue was a record, 1.75 billion, up 167% year on year, and up 54% sequentially. In Q2, we incorporated a full quarter of contribution from the Mellanox acquisition, which closed on April 27th, the first day of our quarter. Mellanox contributed approximately 14% of company revenue and just over 30% of data center revenue. Both compute and networking within data center set a record with accelerating year-on-year growth. The biggest news in data center this quarter was the launch of our Ampere architecture. We are very proud of the team's execution and launching and wrapping this technological marvel, especially amid the pandemic. The A100 is the largest chip ever made, with 54 billion transistors. It runs our full software stack for accelerating the most compute-intensive workloads. Our software releases include CUDA 11, the new versions of over 50 CUDAx libraries, and a new application framework for major AI workloads, such as JAGAS for conversational AI and Merlin for deep recommendator systems. The A100 delivers NVIDIA's greatest generational leap ever, boosting AI performance by 20x over its predecessor. It is also our first universal accelerator, unifying AI training and inference and powering workloads such as data analytics, scientific computing, genomics, edge video analytics, 5G services, and graphics. The first Ampere GPU, A100, has been widely adopted by all major server vendors and cloud service providers. Google Cloud Platform was the first cloud customer to bring it to market, making it the fastest GPU to come to the cloud in our history. And just this morning, Microsoft Azure announced the availability of massively scalable AI clusters, which are based on the A100 and interconnected with 200 gigabyte per second Mellanox and Cinevan networking. A100 is also getting incorporated into offerings from AWS, Alibaba Cloud, Baidu Cloud, and Tencent Cloud. And we announced that the A100 is going to market with more than 50 servers from leading vendors around the world, including Cisco, Dell, Hewlett Packard Enterprise, and Lenovo. Adoption of the A100 into leading server makers offerings is faster than any prior launch, with 30 systems expected this summer and over 20 more by the end of the year. The A100 is already winning industry recognition. In the latest A100 training benchmark, MLPerf 0.7, NVIDIA set 16 records, sweeping all categories for commercially available solutions in both per chip and at scale performance. Based on the A100, MLPerf offers the industry's first and only objective AI benchmark. Since the benchmark was introduced two years ago, NVIDIA has consistently delivered leading results and record performance for both training and infants. NVIDIA also topped the charts in the latest top 500 list of the fastest supercomputers. The ranking, released in June, shows that eight of the world's top 10 supercomputers use NVIDIA GPUs, NVIDIA's networking or both. They include the most powerful systems in the US and Europe. NVIDIA, now combined with Mellanox, powers 2 thirds of the top 500 systems on the list, compared with just less than a half for the two companies in total two years ago. In energy efficiency, systems using NVIDIA GPUs are pulling away from the pack. On average, they're nearly 2.8x more powerful efficient than systems without NVIDIA GPUs, measured by gigaflops per watt. The incredible performance and efficiency of the A100 GPU is best amplified by NVIDIA's own new Selene supercomputer, which debuted as number seven on the top 500 list and is the only top 100 system to crack the 20 gigaflops per watt barrier. Our engineers were able to assemble Selene in less than four weeks using NVIDIA's open modular DGX superpod reference architecture instead of the typical build time of months or even years. This is the system that we used to win the MLPerf benchmarks. And it is a reference design. It's available for our customers to quickly build a world-class supercomputer. We also brought GPU acceleration to data analytics, one of the largest and fastest growing enterprise workloads. We enabled end-to-end acceleration of the entire data analytics workload pipeline for the first time with NVIDIA's GPUs and software stack in the latest version of Apache Spark. released in June. Spark is the world's leading data analytics platform used by more than 500,000 data scientists and 16,000 enterprises worldwide. And we have two major milestones to share. We have now shipped a cumulative total of 1 billion CUDA GPUs. And the total number of developers in the NVIDIA ecosystem just reached 2 million. It took over a decade to reach the first million and less than two years to reach the second million. Mellanox has fantastic results across the board in its first quarter as part of NVIDIA. Mellanox revenue growth accelerated with strength across Ethernet and InfiniBand products. Our Ethernet shipments reached a new record. Major hyperscale builds drove the upside in the quarter as growth in cloud computing and AI is fueling increased demand for high performance networking. Mellanox networking was a critical part of several of our major new product introductions this quarter. These include the DGX AI system, the DGX super product clusters for Selene supercomputer, and the EGX Edge AI platform. We also launched the Mellanox ConnectX 6 Ethernet NIC, the 11th generation product of the ConnectX family, and it's designed to meet the needs of modern cloud and hyperscale data centers, where 25, 50, and 100 gigabytes per second is becoming the standard. We expanded our switch networking capabilities with the addition of QMOS Networks, a privately held network software company that we purchased in June. QMOS augments our Mellanox acquisition in building out open modern data center. The combination of NVIDIA accelerated computing, Mellanox networking, and QMOS software enables data centers that are accelerated, disaggregated, and software defined to meet the exponential growth in AI, cloud, and high-performance computing. Moving to the rest of the P&L. Q2 GAAP gross margin was 58.8%, and non-GAAP gross margin was 66%. GAAP gross margin declined year-on-year and sequentially due to costs associated with the Mellanox acquisition. Non-GAAP gross margins increased by almost six points year-on-year, reflecting a shift in product niche, with higher data center sales and lower automotive sales. Q2 GAAP operating expenses were $1.62 billion, and non-GAAP operating expenses were $1.04 billion, up 67% and 38% from a year ago, respectively. Q2 GAAP EPS was $0.99, up 10% from a year earlier. Non-GAAP EPS was $2.18, up 76% from a year ago. Q2 cash flow from operations was 1.57 billion. With that, let me turn to the outlook for the third quarter of fiscal 2021. We expect revenue to be 4.4 billion, plus or minus 2%. With that, we expect gaming to be up just over 25% sequentially, with data center to be up in the low to mid single digits sequentially. We expect both provis and auto to be at similar levels out in Q2. GAAP and non-GAAP gross margins are expected to be 62.5% and 65.5%, respectively, plus or minus 50 basis points. GAAP and non-GAAP operating expenses are expected to be approximately $1.54 billion and $1.09 billion, respectively. Full-year GAAP and non-GAAP OpEx is tracking in line with our outlook of $5.7 billion and $4.1 billion, respectively. GAAP and non-GAAP OINE are both expected to be 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 $225 to $250 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 will be at the BMO Virtual Technology Summit on August 25th, Citi's 2020 Global Technology Conference on September 9th, Deutsche Bank's Technology Conference on September 14th, and the Evercore's Virtual Menlo Forum, The Future of Mobility on September 21st. We will also host a financial analyst Q&A with Jensen on October 5th as part of our next virtual GTC. Our earnings call to discuss our third quarter's results is scheduled for Wednesday, November 18th. We will now open the call for questions. Operator, would you please call for questions? Thank you.

Certainly. At this time, I would like to remind everyone, in order to ask a question, press star then the number one on your telephone keypad. We'll pause for just a moment to compile the Q&A roster. Your first question comes from the line of Vivek Arya with Bank of America. Your line is open.

Thanks for taking my question, and congratulations on the strong growth and execution. Jensen, I'm wondering how much of the strength that you're seeing in gaming and data centers is um you know maybe more temporary because of covid or you know some customer pull-ins in the data center or so forth and how much of it is more structural and more secular that can continue uh even once we get into hopefully you know sooner rather than later into a more normalized uh period for the industry yeah thank you um

So first of all, we didn't see pull-ins. And we're in the beginning of our brand new product cycle with Ampere. And so the vast majority of the data center growth came from that. The gaming industry, with all that's happening around the world, and it's really unfortunate, but it's made gaming the largest entertainment medium in the world. More than ever, people are spending time digitally, spending their time in video games. The thing that people haven't realized about video games is that it's not just the game itself anymore. The variety of different ways that you can play, whether you can hang out with your friends in Fortnite, go to a concert in Fortnite, building virtual worlds in Minecraft, you're spending time with your friends, you're using it to create, to realize your imaginations. People are using it for broadcast, for sharing ideas and techniques with other people. And then, of course, it's just an incredibly fun way to spend time, even by consumption of the video of a video game. And so there's just so much that you could do with video games now. And I think that this way of enjoying entertainment digitally has been accelerated as a result of the pandemic. But I don't think it's going to return. Video game adoption has been going up over time and pretty steadily. PC is now the single largest entertainment platform. It's the largest gaming platform in GeForce is now the largest gaming platform in the world. And as I mentioned, it's not just about gaming. There's just so many different ways that you can enjoy games. With data center, the structural change that's happening in data center are a couple of different dynamics that are happening at the same time. The first dynamic, of course, is the movement to the cloud. The way that a cloud data center is built in a way that an enterprise data center or a cluster is built is fundamentally different. And it's really, really beneficial to have the ability to accelerate applications that cloud service providers would like to offer, which is basically everything. And we know that one of the most important applications of today is artificial intelligence. It's a type of software that really wants acceleration, and NVIDIA's GPU acceleration is the perfect medium, perfect platform for it. And then the last reason about the data center is the architectural change from hosting applications to hosting services that's driving this new type of architecture called disaggregation versus hyperconverged. And the original name of hyperscalers is a large data center of a whole bunch of hyper-converged computers. But the computers of today are really disaggregated. A single application service could be running on multiple servers at the same time, which generates a ton of east-west traffic. And a lot of it is artificial intelligence neural network models. And so because of this type of architecture, two components Two types of technologies are really important to the future of cloud. One of them, as I mentioned, is acceleration and our GPU is ideal for it. And the other one is high-speed networking. And the reason for that is because the server is now disaggregated. The application is fractionalized and broken up into a bunch of small pieces that are running across the data center. And whenever an application needs to send parts of the answer to another server for the microservice to run, that transmission is called east-west traffic. And the most important thing you could possibly do for yourself is to buy really high-speed, low-latency networking, and that's what Mellanox is fantastic at. And so we find ourselves really in this perfect condition where the future is going to be more virtual, more digital, and that's the reason why GeForce is so successful. And then we find ourselves in a world where the future is going to be more autonomous and more AI-driven, and that's the benefit of our GPUs. And then lastly, cloud microservice transactions really benefit high-speed networking, and that's where Nonox comes in. So I think that this is the dynamics that I'm describing are permanent. And it's just been accelerated to the present, you know, because of everything that's happening to us. But this is the future. And it's not, there's no going back. And, you know, we just found everything accelerated.

Your next question comes from the line of Timothy Akuri with UVS. Your line is open.

Thanks a lot. Jensen, I guess I had a question on both architecture and also manufacturing. And I think on the manufacturing side, you've been, you know, You know, you've been asked in the past about, you know, moving to more of a tiled or, you know, tripled approach. You sort of made, you know, light of that. But the CPU guys are, you know, clearly taking that approach. So I guess the question is, why do you think you won't have to make a similar move? And then on the side of, you know, architecture, the, you know, theme of Hot Chips this week was really how compute demand is far outstripping computing power. And then we see this, you know, talk about you in ARM. So I guess... Can you talk about whether GPU is the future and maybe the broader opportunity to integrate CPU and GPU? Thanks.

Yeah. We push architecture really hard. And the way we push architecture is we start from the system. We believe that the future computer company is a data center scale company. The computing unit is no longer a microprocessor, or even a server, or even a cluster. The computing unit is an entire data center now. And as I was explaining to Vivek just now, that a microservice that we're enjoying hundreds of billions of transactions a day, those are broken up into a whole bunch of microservices that are running across the entire data center. And so the data center is running, the entire data center is running an application. I mean, that's a pretty remarkable thing, and that's happened in the last several years. We were ahead of this trend, and we recognized that, you know, as a computing company, we had to be a data center-scale company, and we architect from that starting point. If you look at our architecture, we were the first in the world to create the concept of an NVLink with eight processors being fully synchronized across a computing node. and we created the DGX. We recognize the importance of high-speed networking and low-latency networking, and that's why we bought Mellonaut. And the amount of software that we invented along the way to make it possible for low-latency communications, whether it's GPU direct or recently the invention of GPU direct storage, all of that technology was inspired by the idea that you have to think about the data center all in one holistic way. And then in this current generation with Ampere, we invented the world's first multi-instance GPU. We invented the world's first multi-instance GPU. That our Ampere GPU could simultaneously be one GPU or with NVLink, eight GPUs combined working together So you could think of them as being tiled. So those eight GPUs are working harmoniously together. Or each one of the GPUs could fractionalize itself. If you don't need that much GPU working on your workload, fractionalize into a multi-GPU instance we call a MIG, a little tiny instance. And each one of those tiny instances are more powerful and more performant than our entire voltage GPU last time. And so whether you like to fractionalize a GPU, which happens oftentimes, create a larger GPU using MVLink, or create an even larger GPU the size of DGX pod connected together with high-speed, low-latency networking with Mellanox, we could architect it any way you like. You made the comment about, you asked the question about ARM. We've been a long-term partner of ARM. And we use Arm in a whole bunch of applications. And whether it's autonomous driving or a robotics application, the Nintendo Switch, console business that we're in. And then recently, we brought CUDA to Arm and to bring accelerated computing to Arm. And so we work with the Arm team very closely. They're really great guys. And one of the specials about the ARM architecture that you know very well is that it's incredibly energy efficient. And because it's energy efficient, it has the headroom to scale into very high performance levels over time. And so anyways, we love working with you guys.

Your next question comes from the line of Aaron Rakers with Wells Fargo. Your line is open.

Yeah, thanks for taking the question and congratulations on the quarter. Just building on some prior questions, the first one, I was just curious if you could help us appreciate kind of the installed base of the gaming GPU business, you know, relative to where we're at in the Turing upgrade cycle. You know, what do we see still on prior generations via Pascal or before? And then secondly, I was wondering, you know, Colette, could you just give me any kind of updated commentary or views on visibility?

uh in the data center business how that you know has that changed over the last three months um you know what does that look like as you look through the back half the calendar year thank you yeah thanks a lot aaron um we are we're still in the ramping of the rtx generation touring uh touring the current generation that we're in uh is the world's first ray tracing gpu and it fuses the rt the rtx technology fuses three fundamental technologies. The programmable shader that we introduced a long time ago that revolutionized computer graphics. And we added two new technologies. One technology is a ray tracing acceleration core that makes the tracing of rays and looking for intersections between the ray and the objects in the scene super, super fast. And it's a complicated problem. It's a super complicated problem, and we wanted to be running concurrently to shading so that the ray traversal and the shading of the pixels could be done independently and concurrently. The second thing is we invented this technology to bring AI, artificial intelligence, using this new type of algorithm called deep learning to computer graphics. And one example of its capability is the algorithm we introduced called DLSS, Deep Learning Super Sample, which allows us to essentially synthesize by learning from previous examples, essentially learning from previous examples of images and remembering it, remembering what beautiful images look like, so that when you take a low resolution image and you run it through the steep neural network, it synthesizes a high-resolution image that's really, really beautiful. And people have commented that it's even more beautiful than native rendered images at the native resolution. And the benefit is not only is it beautiful, it's also super fast. We essentially nearly doubled the performance of of RTX as a result of doing that. So you can have the benefit of ray tracing as well as very high resolution and very high speed. And so that's called RTX. And Turing is probably not even close, not even one third of the total installed base. of all of our GeForce GPUs, which is, as you know, the single largest install base of gaming platforms in the world. And so we support this large install base, and we're in the process of bringing them to the future with RTX. And now with the new console generation coming, every single game developer on the planet is going to be doing ray tracing, and they're going to be creating much, much richer content And because of multi-platform, cross-platform play, and because of the size of the gaming platform, PC gaming platform, you know, it's really important that these game developers bring the latest generation content to PCs, which is great for us.

And then on a data center visibility?

Yeah, let me see if I can answer this one for you. Yes, we have been talking about our visibility of data center. And if you've seen in our Q2 results, you can see that our overall adoption of the NVIDIA computing portfolio has accelerated quite nicely. But keep in mind, we're still really early in the product cycle. A100 is ramping. It's ramping very strong into our existing installed bases, but also into new markets. Right now, A100 probably represents less than a quarter of our data center revenues, so we still have a lot to grow. We have good visibility looking into Q3 with our hyperscales. We have a little bit more of a mixed outlook in terms of our vertical industries, given a lot of the uncertainty in the market and in terms of the overall economy. On-premises are challenged because of the overall COVID, but remember, industries are quickly and continuing to adopt and move to the overall cloud. But overall, we do expect a very strong Q3.

Your next question comes from the line of CJ Muse with Evercore ISI. Your line is open.

Yeah, hi. Thank you for taking the question. I guess two questions. If I look at your outstanding inventory purchase obligations grew, I think, 17% sequentially. Is that, you know, as you prepare for, you know, the September 1 launch, can you kind of comment on that? you know, gaining visibility into the back half of the year. And then the second question, Judson, you know, I know you're very focused on platforms and driving recurring revenues. I would love to hear if there's any, you know, particular platforms over the last three months where you've made real headway or gets you excited, you know, whether Jarvis, Marlin, Sparks, or whatever. Thank you.

Yeah, thank you very much. Thanks a lot, CJ. We're expecting a really strong second half for gaming. I think this may very well be one of the best gaming seasons ever. And the reason for that is because PC gaming has become such a large format. The combination of amazing games like Fortnite and Minecraft and Because of the way people game now, they're gaming and they're e-sporting. Even F1 is an e-sport now. They're hanging out with friends. They're using it to create other content. They're using game captures to create art. They're sharing it with the community. It's a broadcast medium. The number of different ways you can game it has just really, really exploded. And it works on PCs because all the things that I described, you know, require cameras or keyboards or streaming systems, but it requires an open system that is multitasking. And so the PC has just become such a large platform for gaming. And the second thing is RTX. It's a home run. You know, we really raised the bar with computer graphics, and the games are so beautiful, and it's really, really the next level. You know, it's not been this amazing since we introduced programmable shaders about 15 years ago. And so for the last 15 years, we've been making programmable shaders better and better and better, and it has been getting better, but there's never been a giant leap like this. And RTX brought both artificial intelligence as well as ray tracing technology. to PC gaming. And then the third factor is the console launch. People are really, the game developers are really gearing up for a big leap. And because of the gaming, because how vibrant the gaming market is right now and how many people around the world is depending on gaming at home, I think it's going to be the most amazing season ever. We're already seeing amazing numbers from our console partner, Nintendo. The Switch has about to sell more than Super Nintendo, more than all the Fandicons, which was one of the best-selling consoles of all time. I mean, they're on their way to... to make Switch the most successful gaming platform of all time. And so I'm super excited for them. And so I think it's going to be quite a huge second half of gaming.

Our next question comes from the line by Tasha Harry. Your line is open.

Collette, I felt like I missed CJ's second question. Can we jump on and answer it?

I think the question was regarding our inventory purchases on that piece. Is that the part you're referring to? Yeah, keep in mind, CJ, that when you think about the complexity of the products that we are building, we have extremely long lead times, both in terms of what we produce for the data center, our full systems that we need to do, as well as what you are seeing now between the sequential growth between Q2 and Q3 for overall gaming. So all of that is in preparation for the second half. Nothing unusual about it other than, yep, we've got to hit those revenue numbers that are in our Q3 guidance.

Okay. Your next question comes from the line of Tasha Hari with Goldman Sachs. Your line is open.

Hi, good afternoon, and thank you so much for taking the question. I had one for Jensen and another one for Colette. Jensen, just following up on the data center business, as you probably know, quite a few of your peers have been talking about potential digestion of capacity on the part of your hyperscale customers over the next, call it, six to 12 months. Curious, is that something that you think about or worry about in your data center business, or do you have enough idiosyncratic growth drivers like the A100 ramp, and I guess the breadth that you've built within your data center business across compute and networking, are those enough for you to buck the trend within data center over the next six or 12 months. And then the second one, just on gross margins, you're guiding October quarter gross margins down 50 basis points sequentially. Based on the color that you provided for the individual segments, it looks like mix remains pretty positive. So just curious what's driving the marginal decline in gross margins in the October quarter. Thank you.

Yeah, thank you. So thanks for the question. Our data center trend is really tied to a few factors. One is the proliferation of using deep learning and artificial intelligence and all the services that are by the cloud service providers. And I think it's fair to say that over the last several years, the number of breakthroughs in artificial intelligence has been really terrific. And we're seeing anywhere from 10 times, 10x more computational requirements each year to more than that. And so in the last three years, we've seen somewhere between 1,000 to 3,000 times increase in the size of model, the computational requirement necessary to create these AI models and to deploy these AI models. And so the number one trend that we're probably indexed to is the breakthroughs of AI and the usefulness of AI and how people are using it. And I remember the CJ question now, and I'll answer this along with that. One of the things that we look for and you should look for is what kind of breakthroughs are based on deep learning and based on AI that these services all demand. And there are three big ones, just gigantic ones. Of course, one of them is natural language understanding. The ability to take very complicated text and use deep learning to create essentially a dimension reduction called deep embedding, dimension reduction on that body of text so that you could use that vector as a way to teach a recommender system, which is the second major breakthrough, the recommender system, How to predict and make a recommendation to somebody. Recommendation on ads and videos. There are trillions of videos on the web. You need ways to recommend that. Books and news and just the amount of information that is in true dynamic form require these recommenders to be instantaneous. And so the first one is natural language understanding. The second one is the recommender system. Gigantic breakthroughs in the last several years. And the third is conversational AI. And we're going to have conversational agents that are just super clever and they can predict what you're about to ask. They're going to predict the right answer for you, make recommendations to you based on the three pillars that I just described. And I haven't even started talking about robotics. the breakthroughs that are happening there with all the factories that need to automate, and the breakthroughs that we're seeing in self-driving cars. The models there are really improving fast. And so the answer to, you know, because I and CJ are kind of similar, that on the first one, we're indexed to AI. The second, we're indexed to breakthroughs of AI. so that it can continue to consume more and more capability and more technology. And then the third thing that we're indexed to is the movement of workloads to the cloud. It is now possible to do rendering in the cloud, remote graphics workstations in the cloud, and NVIDIA Virtual Workstations is in every single cloud. You could do big data analytics in the cloud. And these applications, I've just given you a few applications where you can do scientific computing in the cloud. These applications all have fundamentally different computing architectures. NVIDIA is the only accelerated architecture that allows you to do microservices for conversational AI and other types of AI applications to scale up applications like high-performance computing, training, big data analytics, to virtualized applications like Workstation. Our platform is universal, and these three stacks that I just described are supremely complex, virtualized, microservices-based, and scale-up-based. And so these bare metal scale-ups, and these are complicated, and it's one of the reasons why we bought Melanots, because they're at the core and at the intersection of all of that. The storage, the networking, the security, the virtualization, they're at the intersection of all of that. And I just described three dynamics that are very, very powerful and are at the early stages yet. And so those are the things that we're really indexed to. And then lastly, when somebody adopts, when we introduce a new platform, like Ampere, and we're in the beginning of a multi-year product cycle. Ampere is such a gigantic breakthrough. It's the first universal GPU we've ever created. It is both able to scale up as well as scale out. Scale up as in multi-GPUs, scale out as in fractionalization, multi-instance GPUs. And it saves money, tremendous amount of money for people who use it. It speeds up their application. It reduces their TCO. Their TCO value just goes through the roof. And so we're in the beginning of this multi-year cycle, and the enthusiasm has been fantastic. This is the fastest ramp we've ever had, and so we're going to keep on racing through the second half.

Okay. And Tashia, you asked a question regarding our guidance going forward regarding gross margin. And within our Q3 guidance, we have just a small decline in our gross margin from Q2. Most of that is really associated with mix, but also a little bit in terms of the ramping of our new and pure architecture products that we have. So keep in mind, our data center will likely be a lower percentage of total revenue, given the strong overall gaming growth that we expect between Q2 and Q3. Within that gaming growth, keep in mind consoles are also included. which will continue to be below our company totals average gross margin, and that is expected to be up strongly quarter over quarter for our overall console shipments. We're going to be ramping those new architectures. Over time, we have the ability to expand our gross margin as Ampere GPUs mature, too.

Your next question comes from the line of Stacy Raskin with Bernstein Research. Your line is open.

Hi, guys. Thanks for taking my question. I wanted to dig into data center a little bit. This is a question for Colette. So in the quarter, X and O and X data center was up, you know, core data center maybe 6%, 7%. The guide looks to be roughly similar to that in the Q3. Can you talk to us a little bit about what's driving the trajectory? Are you more demand or more supply limited at this point? What does your supply situation look like? And what do the lead times, especially on the A100 products for data center, look like at this point? Like if you had more capacity available, do you think you'd have like a stronger trajectory than you have right now?

Yeah, Stacey, so thanks for the question. Let me first start on our Q3 outlook and what we're seeing. And when we think about our demand and our supply, we're very comfortable with the supply that we have. Keep in mind, our products are quite complex. And a lot of our time is spent in terms of procuring every aspect of that supply over multiple quarters previously. So that's how we work. But we are very confident with the overall supply that we have across the board in data center. Keep in mind that's not just A100. We are continuing to sell our V100, our T4, and we're also bringing new versions of the A100 coming to overall market. So I hope that helps you understand our statements on where we have in terms of the Q3 guidance. Let's see if Jensen wants to add a little bit more to that.

Well, you know, when we're ramping, we sure love to have more and sooner. But, you know, this is our plan, and we're executing to the plan. It is a very complicated product, as Colette mentioned. It is the most complicated. Got it. Got it. Um, and just a quick follow up, um, within the data center guidance, how do you think about like the core data center sequential growth versus melanocytes?

Yeah, so in terms of moving from Q2 to Q3, we believe that most of the actual growth that we will receive in those single digits to mid-single-digit growth will likely stem from NVIDIA compute. We'll be the largest driver of that.

Your next question comes from the line of Joseph Moore with Morgan Stanley. Your line is open.

Great. Thank you. I wonder if I could ask a longer-term question about how you guys see the importance of process technology. There's been a lot of discussion around that in the CPU domain, but you guys haven't really felt the need to be first on 7 nanometer, and you've done very well. How important do you think it is to be early in a new process node, and how does that factor into the cycle of innovation at NVIDIA?

Yeah, first of all, thanks, Joe. The process technology is a lot more complex than a number. I think people have simplified it down to almost a ridiculous level. And so process technology, we have a really awesome process engineering team, world-class. Everybody will recognize it as absolutely world-class. And we work with the foundries, we work with TSMC really closely to make sure that we engineer transistors that are ideal for us, that we engineer metallization systems that's ideal for us. It's a complicated thing, and we do it at high art. Then the second part of it is where the process technology and the rest of the