Yahoo Finance NVIDIA Corporation (NVDA) Q3 2019 Earnings Conference Call Transcript
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NVIDIA Corporation (NASDAQ: NVDA
Q3 2019 Earnings Conference Call
Nov. 15, 2018, 5:30 p.m. ET
Contents:
Prepared Remarks
Questions and Answers
Call Participants
Prepared Remarks:
Operator
Good afternoon. My name is Kelsey, and I'm your conference operator for today. Welcome to NVIDIA's financial results conference call. All lines have been placed on mute. After the speakers' remarks, there will be question-and-answer period. At this time, if you would like to ask a question, please press * then the number 1 on your telephone keypad. To withdraw your question, press the # key. Thank you. I'll now turn the call over to Simona Jankowski, Vice President of Investor Relations, to begin your conference.
Simona Jankowski -- Vice President, Investor Relations
Thank you. Good afternoon, everyone, and welcome to NVIDIA's conference call for the third quarter of fiscal 2019. With me on the call today from NVIDIA are Jen-Hsun 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. It's also being recorded. You can hear a replay by telephone until November 22, 2018. The webcast will be available for replay until the conference call to discuss our financial results for the fourth quarter of fiscal 2019. 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 15, 2018, 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, I'd like to turn the call over to Colette.
Colette Kress -- Chief Financial Officer
Thanks, Simona. Q3 revenue reached $3.18 billion, up 21% from a year earlier, with all 4 of our market platforms growing double digits. Data center, professional visualization and automotive all hit record levels. However, gaming was short of expectations as post crypto channel inventory took longer than expected to sell through. Gaming card prices, which were elevated following the sharp crypto falloff, took longer than expected to normalize.
Our Q4 outlook for gaming reflects very little shipment in the midrange Pascal segment to allow channel inventory to normalize. In Q4, we also expect minimal sales of Tegra chips for game consoles due to the normal seasonal build cycle. While channel inventory situation presents a near-term headwind, it does not change our long-term fundamentals. Our competitive position is as strong as ever, and we have expanded our addressable market with Turing and our recent software announcement. We remain excited about the growth opportunities in ray-traced gaming, rendering, high-performance computing, AI and self-driving cars.
GAAP gross margins grew 90 basis points year-on-year and non-GAAP gross margins rose 130 basis points. This reflects our continued shift toward higher-value platforms but also included a $57 million charge for prior architecture components and chips following the sharp falloff of crypto mining demand. Both GAAP and non-GAAP net income exceeded $1 million for the fourth consecutive quarter. From a reporting segment perspective, GPU revenue grew 25% from a year ago to $2.77 billion. Tegra processor revenue was down 3% to $407 million.
Let's continue with our gaming business. Revenue of $1.76 billion was up 13% year-on-year and down 2% sequentially. Year-on-year growth was driven by initial sales of our new Turing-based GPUs as well as strong notebook sales, which more than offset gaming console declines. In mid-September, we began shipping GeForce RTX series, the first gaming GPUs based on our Turing architecture. Turing RTX technology delivers up to 2x the performance of its predecessor, Pascal, and 6x more for ray-traced graphics. These are the biggest generational gems we have ever delivered in gaming GPUs.
The first two GeForce RTX gaming cards to hit the shelves were the 2080 Ti and the 2080, delivering 4K HDR gaming and 60 frames per second on even the most advanced AAA titles, a major milestone for gamers. This is quickly becoming the new performance baseline as 4K displays are now reaching affordable price points. These two high-end cards were quickly followed by the rollout of the GeForce 27D. NVIDIA RTX technology brings games to life like never before. The highly anticipated Battlefield V launched this week with the first release of RTX ray-tracing, enabling lifelike reflections on GeForce RTX GPUs. With a pipeline of upcoming games supporting NVIDIA RTX features, RTX is well on its way to establishing itself as a game-changing architecture.
Although the cryptocurrency wave has ended, the channel has taken longer than expected to normalize. Pascal high-end cards have largely sold through ahead of RTX. However, on midrange Pascal gaming cards, both channel prices and inventory levels remained higher than expected. Pascal is well positioned as the GPU of choice in the midrange for the holidays, and we expect to work down channel inventories over the next quarter or 2.
Moving to data center. We had another strong quarter with revenue of $792 million, up 58% year-on-year and up 4% sequentially. Demand remains strong for both the architecture products, including Tesla V100 and VGX systems, and our inference business continued to grow, benefiting from the launch of the Turing T4 Cloud GPU during the quarter. Just 2 months after its launch, the T4 has received the fastest adoption of any server GPU. It is integrated into 57 server designs and it is already on the Google Cloud Platform, its first cloud availability. The T4 delivers world record performance for deep learning inference and accelerates diverse cloud workloads, including high-performance computing, deep learning training and inference, machine learning, data analytics and graphics.
We also announced an updated TensorRT software stack and NVIDIA TensorRT Hyperscale Platform. This new software includes two critically important capabilities that can drive deployment of the NVIDIA inference platform at scale in hyperscale data centers. First, it enables multiple models and multiple frameworks to run on the same GPU at the same time. This can drive higher data center utilization, directly translating to significant savings. Second, it integrates with Kubernetes, the leading orchestration layer for hyperscale data centers.
Completing our inference platform, the new T4 GPU delivers 12x the peak inference performance of its P4 predecessor. All told, our inference platform delivers 40x faster performance in CPUs and with the tensor RT software stack, it is ideally suited for hyper-scale data centers. With this launch, NVIDIA is poised to take the data center inference market targeting every server node in the hyper-scale data centers Another important launch for the quarter was the NVIDIA RTX server reference architecture, which incorporates up to eight turing-based RT 8,000.
With this product, turing opens a new market to GPUs, photo-real rendering or the creation of computer-generated images that look real. Rendering is instrumental to large industries, such as media and entertainment, retail, product designs, manufacturing, and architecture. Yet prior to turing and its retracing capabilities, GPUs were not able to address this workload so most rendering up to this point has been done on CPUs. And RTX accelerated render form compared with an equivalent performance CPU render form is one-fourth the cost, one-tenth the space, and one-eleventh the power.
NVIDIA's RTX platform has garnered major industry support including from key developers such as Adobe, Ansys, Autodesk, Devo, and many others. Lastly, NVIDIA announced a GPU acceleration platform for data science and machine learning called Rapids, which enables companies to analyze massive amounts of data and make accurate business predictions at unprecedented speed. Up until now, data analytics and machine learning has been the largest [webcast cuts out].
Questions and Answers:
Jensen Huang -- Chief Executive Officer
If you look at the background of what's happening, we know that Moore's law has ended. And while demand for computing continues to grow and more and more of the data center is running machine learning algorithms, which is computationally really intensive, the only way to increase computational resource is to buy more computers, buy more CPUs. Because each one of those CPUs aren't getting much faster. And so as a result of that, the data center capex would have to go up. The alternative -- which is the alternative that we offer and was one of the reasons why the adoption of NVIDIA's accelerated computing platform is growing so fast is because the approach that we provide allows for a path forward beyond Moore's law.
There are several things that we have done this last quarter that I think is really fantastic. The first is the introduction of a new computing platform, a new accelerated platform called Rapids. And as you know very well that the vast majority of the industry today, although are super excited about deep learning -- deep learning as a method for artificial intelligence is very data intensive. And in areas where there's a lot of domain expertise, whether it's in retail or whether it's in financial services or healthcare, logistics, there's a fair amount of domain expertise.
And the amount of data that they have to fuse together to train a model is quite high. The approach of using traditional machine learning is quite successful. That has never been accelerated before and we worked with the open source community over the course of the last several years to pull together an entire stack that starts from a patchy arrow, the desk parallel distributed computing engine, and then all of our CUDA and all of our algorithms that run on top of that we now have an accelerated machine learning platform. That's a brand new platform and the excitement around that is really quite incredible.
The second thing is the turing architecture allows us to do film rendering at a much more affordable way than Moore's law would've allowed. And then the third, which we just announced recently, is our first turing based T4 cloud GPU. And along with all of the software stack that we've put on top of it, Kubernetes, the docker, the TRT inference engine, our second-generation tensor core, AI accelerator. All of that together has created a lot of excitement in data centers. I'm expecting our data center business to continue to do quite well.
Harlan Sur -- JPMorgan Chase & Co. -- Analyst
Great, thanks for that. And then just on the high-end turing products that the team started rolling out in October. Early demand actually seems to be quite strong and I think part of it is just the line-up of triple-A rated gains, e-sports continues strong as well. Obviously, a big motivator for your enthusiast class gamers. I know the team is near-term kind of working down mid-range Pascal cards, but do you anticipate your turing based RTX product families to drive sequential growth into January quarter? Just what appears to be pretty strong demand-pull for these products?
Jensen Huang -- Chief Executive Officer
Not much happened toward the end of the quarter and it's the biggest generational leap we've ever had. It introduced real-time retracing, it's the first gaming GPU to include artificial intelligence. At every single price point it serves, it is substantially higher performance than the last and is the highest performing GPU in the world. And all the great content are coming. Yesterday I think it was the Battlefield 5 was released with real-time retracing, the world's first application to support real-time retracing. So we expect to do really well. As we go on, surely we'll bring turing deeper into the mainstream. We don't have anything to announce today but as usual, we want to bring a brand new architecture to as many gamers as possible.
Operator
Your next question is from Toshiya Hari with Goldman Sachs.
Toshiya Hari -- Goldman Sachs -- Analyst
Great. Thank you so much. I had a question on the gaming outlook and as it relates to channel inventory. Collette, you mentioned that typically the midrange is about a third of gaming. How much was it in the October quarter?
Jensen Huang -- Chief Executive Officer
So RTX is the world's first accelerated retracing GPU. And the enthusiasm from the digital content creation market is really great. I surely expect that -- and as I was mentioning earlier -- that it's been close to a decade that the workstation industry has not had a fundamental platform architecture change. And so RTX is the first one. So I'm expecting our progress to do really well.
Operator
Your next question is from Vivek Arya with Merrill Lynch.
Vivek Arya -- Merrill Lynch -- Analyst
Thanks for taking my question. I'm curious, Jensen, what needs to happen to work down this midrange Pascal inventory? Is it pricing, is it something else? Because the thinking was that this could be cleared within the October quarter but it hasn't. Do you think people who are waiting for turing to come out so maybe that created some pause? And then as part of part B of that question, maybe Colette, how should we think about seasonality in the April quarter given that you mention it could take one or two quarters to work down this inventory? Thank you.
Jensen Huang -- Chief Executive Officer
We came into Q3 with excess channel inventory post the crypto hangover. We expected the pricing in the marketplace to decline. It declined slower than we expected. But while it was declining, we were expecting sales volume to grow, demand to grow. And for volume to be elastic with pricing. I think it just took longer than we expected and the volume increase took longer than we expected. At this point, most of the pricing has come down to its -- and slightly below -- its pre-launch levels. And so I'm hopeful that now that pricing has stabilized that customers will come back and buy.
I guess when pricing it is volatile in the channel, it probably freezes some people waiting for prices to stabilize. That took longer than we expected, frankly. But now that it's at the right levels our expectation is that the market will return to normal. 1060 is the number one selling graphics card in the world. And we decided not to sell anymore into the channel for the upcoming quarter to give the channel an opportunity to sell through the inventory it has. So we'll keep our eyes on it but our expectation is that inventory levels will come back to the normal by the end of the quarter.
Colette Kress -- Chief Financial Officer
Okay Vivek, to answer your question also regarding Q1 in terms of what we're gonna see in terms of the expectation. As the channel inventory normalizes at the end of Q4, we do believe going into Q1 we will be probably up from where we end in terms of Q4. So we won't follow that normal seasonality between Q1 and Q4. We do expect to be up as we go into Q1.
Operator
You have a question from CJ Muse with Evercore.
CJ Muse -- Evercore -- Analyst
Hi, thanks for taking the question. I guess a follow-up question on the channel inventory side. It looks like it's roughly $600 million kind of a draw down here. I'm just curious; does that sound right number one? Number two, does that fit with what you are hearing from your channel partners in terms of what's excess? And then as part of that, are you drawing down inventory in the current quarter ahead of turing architecture launch into the mainstream?
Jensen Huang -- Chief Executive Officer
The last question I'm not sure I understand. I think the answer to your first question is yes. You framed it nicely and the answer is yes. The last question was what again?
Colette Kress -- Chief Financial Officer
The last question was regarding our midrange. Is there any statement about future turing products that were taken into account?
Jensen Huang -- Chief Executive Officer
We haven't announced our future turing product but it would be expected for us to create a turing GPU that serves the mainstream parts of the marketplace. And so we're not announcing anything but it would be conventional of us to do that.
CJ Muse -- Evercore -- Analyst
The question was whether you were drawing down inventory perhaps below normalized levels in the current quarter?
Jensen Huang -- Chief Executive Officer
No, we're really not shipping into the midrange segment of Pascal so that we give the channel an opportunity to sell through the product at house. And we would like to see channel inventory get normalized by the end of Q4. And then get back to doing our work.
Operator
Your next question is from Stacy Rasgon with Bernstein Research.
Stacy Rasgon -- Bernstein Research -- Analyst
Thanks for taking my questions. My first one is for Colette. I wanted to be a little more explicit. If I think about your business split into a sort of gaming and non-gaming, are you looking for the non-gaming pieces in aggregate to grow sequentially into Q4?
Colette Kress -- Chief Financial Officer
Yes. I think the answer to that is yes. In aggregate, yes, we do believe the rest of the business will grow sequentially.
Stacy Rasgon -- Bernstein Research -- Analyst
I guess that fits with the one-third you were talking about because that implies the gaming down 30% plus so that is what your kind of magnitude that you're thinking about at this point?
Colette Kress -- Chief Financial Officer
That is correct.
Stacy Rasgon -- Bernstein Research -- Analyst
Got it. Thank you. For my second question, for the last several quarters the idea of the channel could be getting full is not necessarily a new worry. And yet the last several quarters you've been saying on this call that you guys felt like you had a really good handle on the channel and yet it seems like maybe that wasn't exactly the case.
Can you give us a feeling for what changed and when you saw it in the quarter? Was this something that happened late in the quarter that you realized it or did you go into the quarter knowing the inventories needed to be corrected? Like, what happened? Because this tone is a little different from what we've heard over the last few earnings calls from you.
Jensen Huang -- Chief Executive Officer
We were surprised, obviously. We're surprised by it as anybody else. The crypto hangover lasted longer than we expected. Prices started to drift down and we expected to come down much more quickly than it did. When it went down, we expected demand to come up much more quickly than it did. And so I think the channel wanted to protect its price. People were uncertain about crypto.
And demand was uncertain about when the price would be stabilized. And so all of that uncertainty I think froze the market a little longer than we expected. Pricing is now down to below pre-launch normal levels and so I'm hopeful that we're gonna see demand come back and the sell-through will happen through the holidays. And we're seeing that. We didn't expect it either and we didn't realize the magnitude of it until toward the end of the quarter. What was the other question? was there another question? I think that was it.
Operator
Your next question is from Joe Moore with Morgan Stanley.
Joe Moore -- Morgan Stanley -- Analyst
Great. Thank you. So question to the turing ramp -- I guess -- how is that going relative to your expectations? It seems like availability is quite a bit better now and where do you stand with the LSS support? I know you've announced a number of games that will have the LSS support but year-end how many of those are already supporting that technology?
Jensen Huang -- Chief Executive Officer
The ramp is going great. I think this is the biggest generational leap we've ever had. This is the most substantial new technology that computer graphics have seen in a decade. Real-time retracing is something that everybody had dreamed about for a long time, has never seen before. And today with Battlefield 5, people are enjoying real-time retracing for the very first time. And the images are beautiful. So the ramp is great. Of course, turing ramped into -- toward the end of the quarter and into a much different situation than any GPU of the past. But nonetheless, the demand on the high-end products are fantastic. The 28 TIs are largely sold out. I think are still sold out everywhere.
And so I think that the demand is great. I'm expecting it to be just a fantastic new generation. In terms of the content, you sell the first one. Final Fantasy is also out and we have a pipeline of about 30 of them. We're working hard on that. And so when these games get released, RTX will be enabled. I will say one last thing, which is content aside, RTX is high performing at the same price point than any graphics card on the planet. So at every single price point, it is the highest performing graphics card. It's unambiguously the highest performance GPU in the world and of course, all of these great new features will be coming.
Operator
Your next question is from Pierre Ferragu with New Street Research.
Pierre Ferragu -- New Street Research -- Analyst
Hey, thank you for taking my questions. I'm still trying to get my head around the magnitude of this China inventory drawdown because if you don't change like the midrange or full quarter that means your inventory is more than a quarter, 12 weeks of sales. And so my first question would be, am I right thinking that? Are you bringing those full quarter sale in inventories? And then my second question is, while you are going down these inventories, are we expected to see maturing high-end car for 2018 and the 20 ATI ramping in Q4? Excluding inventory, the rights of the business, the rest of the distributing that's been gaining would be more like flattish sequentially?
Jensen Huang -- Chief Executive Officer
I'm trying to figure out what the first part of the question was.
Colette Kress -- Chief Financial Officer
The first question was whether the midrange of Pascal had more than 12 weeks of inventory -- if it's gonna take more than a quarter to bring it down?
Jensen Huang -- Chief Executive Officer
I think the channel has more than 12 weeks of inventory between us and the other brand. One of the things that is hard to estimate is how much inventory the other brands have. Our quarter is one month later and so whatever action we take, whatever we see in the channel, is one month after their end of the quarter.
The amount of inventory is not just us it's also the other brands. and our ability to see the other brands' inventory is just much harder. We try our best to estimate it but obviously, we didn't estimate it well enough. And so the answer to your question is yes. I think there's about -- from our perspective -- about 12 weeks of our inventory to sell through at this point.
Operator
Your next question is from Mark Lipacis with Jefferies.
Mark Lipacis -- Jefferies -- Analyst
Thanks for taking my question. I was hoping you could contrast this product cycle transition to turing to the product transition you had to Pascal. Is the main difference the crypto hangover? Is there something else impacting the transition do you think? You've described turing as the greatest generational leap and I'm wondering if that larger delta has an impact onto the transition as well? Thanks.
Jensen Huang -- Chief Executive Officer
Turing is the highest performance GPU at every single price point. It played no role in this transition. It's all about crypto hangover. This is the new experience as we made this transition. If you look at turing, it had a great launch. We ramped it at the end of the quarter as we expected, it was backend loaded as we expected, and the ramp was great. Everybody did a great job. The performance is fantastic. And the excitement is great. And so I think turing's ramp was a big success. Underneath turing was choppy as we're talking about. we really didn't see that until toward the end of the quarter. And as we looked out into this quarter, we came to the conclusion that the best thing to do was just not to ship any more products into this segment of the marketplace.
Because there's a fair amount of inventory. And let the channel sell through the midrange Pascals and then a quarter's time, we'll get back to business. So I think this is surely a setback and I wish we had seen it earlier. In the final analysis, can't exactly sure of what we would've done differently. Between the unexpected and unanticipated slow decline of pricing in the channel and even after the prices came down it took a little longer than we expected for volume to kick up. And the other brands' inventory in the marketplace -- those factors kind of compounded and made it a lot worse than we expected.
Operator
You have a question from Aaron Rakers with Wells Fargo.
Aaron Rakers -- Wells Fargo -- Analyst
Thanks for taking the questions. Maybe I can ask the question a little bit differently on the gaming business. If I look back over the past several quarters. Let's say you've been running at roughly a 1.6-1.8 billion-revenue level since the October 17 quarter. Prior to that, you were at 1.1-1.2 billion. We look like we're now going back to that level. The question is; do we build off of that level, do we bring back half of the inventory burn?
How do you think about the return of your growth in that gaming piece of the business as we start to look into fiscal 2020? And a quick second question. Over the past three years, you've had really strong seasonal sequential growth in the data center business in Q4, about 20% sequentially. I'm just curious, how is your guide factoring in the sequential growth in that piece of the business into this current quarter?
Jensen Huang -- Chief Executive Officer
Let me take the second one first. Our data center business is doing great. The fundamental dynamics of accelerated computing is spot on. And with Moore's law coming to an end, it's the path forward. Take a look at a number of systems in the top 500, 127 systems this year. a growth of nearly 50% year-over-year with the number one system in the United States, in the world, in Europe and Japan. We're 22 out of the top 25 most energy-efficient computers in the world. In this quarter, we announced three new initiatives that's going to expand us into a broader part of the high-performance computing market with machine learning, which as we know is the largest part of artificial intelligence today, which has not been accelerated and now it is.
The second is the ability to do rendering for film and photorealistic rendering for the first time. And then the third is a brand new cloud GPU we call T4 that the enthusiasm around it is just incredible. And from the time that we went to production to the time that Google put it in their cloud was literally 30 days. It's just an incredible speed of adoption. And so I expect T4 to do quite well. So I think our data center business dynamics are really quite great. In terms of forecast, we'll just see how it turns out. But I think the fundamental dynamics are great. Back to your question about gaming.
Colette Kress -- Chief Financial Officer
The statement came in regarding -- bumped up the overall gaming somewhere in mid of the year to about a $1.7 billion gaming business where maybe if you look back two years you're at about 1.1. At this stage, when you come out of the setback that we have here to get through the overall channel inventory, where will you come out after that and what type of growth could we expect?
Jensen Huang -- Chief Executive Officer
I'm gonna let you guys do the modeling but let me just tell you this. There's nothing fundamentally different about the gaming market that we know. Cryptocurrency is an extraordinary factor that we all have to just internalize that it is. We thought we had done a better job managing the cryptocurrency dynamics but when the prices came down, started to come down, and we hoped the demand would start to reflect the declining price. It just took longer than we expected. That's what we're experiencing. In terms of the gaming marketplace, if you take a look at some of the dynamics -- our notebook gaming, which is not affected by crypto, grew 50% year-over-year in China.
And so the gaming market seems quite robust. RTX is going to unquestionably redefine gaming computer graphics. And so I think the dynamics are good. We have to work through the channel inventories. This quarter, of course, we had the simultaneous decision of not shipping any more midrange products into the channel as well as seasonal console build plans. They tend to build out a quarter before the holiday season. So you have these two simultaneous effects. But there's nothing about the gaming marketplace or the gaming business that we see that is fundamentally different.
Colette Kress -- Chief Financial Officer
To kind of add to that, think about our gaming business in several pieces that we talked about in terms of the tremendous strength that is also continuing in terms of our success in terms of turing, our notebooks for gaming are growing extremely strong, and our overall console business is also extremely healthy as well. So to think about all of the different components, we just have a piece of channel inventory at the midrange but overall as you can see, gaming is also growing quite well.
Operator
Your next question is from Chris Caso with Raymond James.
Chris Caso -- Raymond James -- Analyst
Yes, thanks, good evening. Thanks for taking the question. A question with regard to inferencing and what we can expect from that for both Q4 and going forward. Perhaps, I don't know if it's a valid comparison to compare what we might expect from inferencing after the new Quadro launches to what happened in training after the Volta launches. Is there any comparison there in terms of magnitude or how the ramp goes?
Jensen Huang -- Chief Executive Officer
The ramp of T4 is completely related to customers porting their model on top of our platform. And the inference model is really complicated. This is one of the things that I've talked about in the past. That on the one hand, people think that inference appears to be simple because there's so many ASICs built being talked about. the vast majority of the complexity of inference is actually in the optimizing compiler on top. The tensor RT fifth generation optimizing compiler that we announced just recently took three or four years to build.
And then on top of that, in order to get it to scale as quickly as what people saw in Google's cloud requires us to build something called a TRT server, an inference server that allows multiple models to run on top of Kubernetes in the cloud. That piece of software is also super complicated to write. And so the pieces of technology that we're putting together have come together. And now we're engaged with companies around the world to port their most heavy workload applications on top or models on top of T4. So we're working hard on that and when that happens it comes down to their decision of how many they would like to buy and that tells us about our adoption rate. I think from a high-level perspective, if we step back for a second, the high-level way to look at it is this.
We know for a fact that Moore's law has come to an end. And at the same time, we also know that more and more data centers are deploying deep learning models and machine learning models into their data center. And it's computationally really intensive. At this time, and as we look out into the horizon, the T4 cloud GPU is just unquestionably the most effective. It can run models whether it's an image model or a recommendation model or a speech synthesis model. It is the highest throughput processor in the world at 70 watts, which fits into a hyper-scale data center OCP server. It is also the lowest latency of any processor at inferencing in the world at less than one millisecond.
And so between the architecture, all of the software technology and all of the software capabilities we put in place and the fact that the conditions would suggest that internet companies need an accelerated path forward, I think T4 is really well positioned. And I look forward to coming back and telling you guys about success.
Operator
You have a question from Will Stein with SunTrust.
Will Stein -- SunTrust -- Analyst
Good evening. Thank you for taking my questions. First, Jensen, I appreciate all the details on the T4 for inference in the data center. Could you likewise highlight the current traction you're seeing and the long-term growth expectations for the Jetson product that's designed for really I think a different market, it's inference at the edge, right?
Jensen Huang -- Chief Executive Officer
Jetson is designed for edge AI. One version of Jetson, which is an AV functional save, high performance with loads of complicated software. One version of that you could say is self-driving cars. This quarter we announced winning our first mass-market level two. We've been really successful in robot taxis and level fours and trucks and shuttles and high-end systems where the number of processors, the number of sensors, the combination of lidars and surround cameras require a lot of computation. We've never been successful until now. We're taking the drive platform all the way down to level two mass-market cars. Volvo is our first announcement, our first win in high-volume early 2020s production ramp.
I'm expecting many more. I think we've positioned and created a solution that is both highly useful and easy to use as well as could deliver level two capability in a single chip for the very first time. And, Xavier is in production. It is the only single-chip autonomous processor in production today. Now, you take that same platform and you could apply to all kinds of other edge AI devices. It could be manufacturing picking robots, it could be autonomous retail, basically AI retail, autonomous warehouses. Or medical instruments, medical imaging instruments that in the device itself recognizes and identifies anomalies. All of these types of applications are leaning toward AI and that's the reason why we built Jetson.
Operator
Your next question is from Craig Ellis with B. Riley.
Craig Ellis -- B. Riley -- Analyst
Thanks for taking the question. I'll ask a clarification and then a question. The clarification is just on the inventory issue and thanks for all the color but one, are Pascal 1070s and 1080s in TI flavors still selling and if so, could they present any kind of inventory risk either later this year or in early fiscal '20? The question really, Jensen, is trying to get a better understanding of how you see the intermediate term growth rate of the data center business. You had a spectacular high performance compute top 500-accelerator penetration performance up 50+%. That about matches the growth in the data center business.
Those may be somewhat coincidental but can you just talk about where you see penetration across key end markets like HPC, like cloud and hyper-scale, and like enterprise. Which offers you the best growth from here? and where do you feel like your penetration may be more mature? I'm just trying to get a sense if there's an acceleration coming off of the 50% year-on-year growth that we're seeing now or if consistent with the recent trend we might be moderating potentially down into the 40% or 30% range as we go into the next calendar year? thank you so much.
Jensen Huang -- Chief Executive Officer
Our high-end Pascal GPUs are largely sold. And we did a fairly good job making sure that with that transition before we ramped up the high-end turing products. Our data center business; I would say the Q3 inventory set back aside, I actually have to say it was one of the best quarters we ever experienced. The reason for that is because of our data center position, our accelerated computing position as a company, which is the foundation of this company. The accelerated computing focus of our company expanded in really several ways. For the first part of our journey into a celebrated computing was really following scientific computing, simulating first principle laws of physics for scientific computing and high-performance computing codes.
About five years ago, deep learning came into the fore and we were alert and agile and invested a great deal and mobilized the company to go help the world put deep learning into software developers' hands all over the world. The area where I'm super excited about right now is the three that I've mentioned that we've opened up in this last quarter with the launch of turing and with the launch of Rapids. The first is our film rendering opportunity is -- we think that there are about 10 million CPU notes around the world that are used for film rendering. They can now benefit from accelerated computing as Moore's law comes to an end. The second is opening up inference. The hyper-scale data center marketplace is something along the lines of 15 million CPUs sold this year and it was growing -- let's call it growing at about 15% per year. The number of CPUs.
We know for a fact that Moore's law has come to an end and those servers are gonna have to be accelerated going forward. And so I think that T4 is just ideal for that. It was designed from the ground up to deliver computing in a very compressed and very condensed power sensitive environment, which these hyper-scale data centers tend to be. And the software stack from Kubernetes to containers to TRT compiler to the TRT inference server and our NGC cloud with all of the stacks fully accelerated and then containerized in the cloud certifying all of the major cloud providers around the world for our containers. That process took us several years and it's put us in a really great place. So T4 is really fantastic. And so that's the second segment of high-performance computing, is deep learning.
The third and potentially the largest currently is machine learning. This is where Hadoop goes. This is where Spark goes, this is where Scikit-learn, Python, Pandas. All of the data scientists around the world in retail and transportation and logistics and healthcare and financial services that are using algorithms like Random Forest and XGBoost and K-nearest and K-means and PCA and all of these different buzzwords have never had the opportunity to have accelerated computing until now. And this took a couple two or three years for us to pull together. Rapids has been open sourced. You can go into the NGC cloud, download it, IBM is gonna integrate it into their machine learning platform. SASS, SAP, Oracle, the cloud providers are all integrating the Rapids open source SDK into their machine learning platform. And so this is a new segment for us.
The answer about our growth rate is I believe that our accelerated computing, our data center opportunity, has significantly expanded during the quarter. Between the T4 hyper-scale cloud GPU and Rapids machine learning platform, it has shortened our RTX server film rendering. We surely have expanded our data center opportunity. And so I fully expect us to continue to do well in accelerated computing for data centers.
Operator
Unfortunately, we have run out of time. I will now turn the call back over to Jensen for any closing remarks.
Jensen Huang -- Chief Executive Officer
Thanks, everyone. To sum up: the crypto hangover has left the industry with excess China inventory. It will take one or two quarters to work through it. This is an unexpected near-term setback and it doesn't change the fundamental dynamics of our company. The end of Moore's law has cleared away for NVIDIA accelerated computing as a great path forward. Turing opens up three exciting markets for us with retracing games, film rendering, and hyper-scale inference. And with our first win in mainstream level two self-driving cars with Volvo, our drive AV platform is gearing up for the mass market. And our competitive position has never been stronger. We look forward to updating you on our progress. Thank you.
Operator
Thank you for joining you may now disconnect.
Duration: 50 minutes
Call participants:
Colette Kress -- Chief Financial Officer
Jensen Huang -- Chief Executive Officer
Harlan Sur -- JPMorgan Chase & Co. -- Analyst
Toshiya Hari -- Goldman Sachs -- Analyst
Vivek Arya -- Merrill Lynch -- Analyst
CJ Muse -- Evercore -- Analyst
Stacy Rasgon -- Bernstein Research -- Analyst
Joe Moore -- Morgan Stanley -- Analyst
Pierre Ferragu -- New Street Research -- Analyst
Mark Lipacis -- Jefferies -- Analyst
Aaron Rakers -- Wells Fargo -- Analyst
Chris Caso -- Raymond James -- Analyst
Will Stein -- SunTrust -- Analyst
Craig Ellis -- B. Riley -- Analyst
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