Ambarella (NASDAQ:AMBA) held its second-quarter earnings conference call on Thursday. Below is the complete transcript from the call.
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Summary
Ambarella Inc reported fiscal Q2 revenue of $108.1 million, slightly above guidance, with non-GAAP EPS of $0.18. The company experienced growth in IoT and automotive sectors, driven by commercial vehicle adoption.
The company is expanding its AGI platform leadership with new high-value SoCs and go-to-market strategies, including partnerships with Capgemini and Magnica to develop indirect sales channels.
Ambarella Inc increased its five-year serviceable market forecast, projecting a CAGR of about 20% from fiscal year 2027 to 2032, driven by edge infrastructure and operational efficiency in AI applications.
Q3 revenue is expected to be between $115 to $124 million, with a focus on physical AI demand from the IoT market. The company maintains its gross margin target of 59% to 62% despite supply chain cost pressures.
Notable operational highlights include the development of new AI accelerators like the X7 and significant customer wins in robotics, automotive, and AI-based enterprise video intercoms.
Full Transcript
OPERATOR
Thank you for standing by and welcome to Ambarella Inc's second quarter fiscal year 2027 earnings call. At this time, all participants are in listen-only mode. After the speakers' presentations, there will be a question-and-answer session. To ask a question during the session, you'll need to press star 11 on your telephone. If your question has been answered and you'd like to remove yourself from the queue, simply press star 11 again. As a reminder, today's program is being recorded.
And now I'd like to introduce your host for today's program, Luis Gehardi, Vice President, Corporate Development. Please go ahead, sir.
Louis G., Corporate Development, VP
Thank you, Jonathan, and good afternoon. Thank you for joining our second quarter fiscal year 2027 financial results conference call. On the call with me today is Dr. Fermi Wong, President and CEO, and John Young, CFO. The primary purpose of today's call is to provide you with information regarding the results for our second quarter of fiscal year 2027. The discussion today and the responses to your questions will contain forward-looking statements regarding our projected financial results, financial prospects, market growth and demand for our solutions, among other things.
These statements are based on currently available information and subject to risks, uncertainties and assumptions. Should any of these risks or uncertainties materialize, or should our assumptions prove to be incorrect, our actual results could differ materially from these forward-looking statements. We're under no obligation to update these statements. These risks, uncertainties and assumptions, as well as other information on potential risk factors that could affect our financial results, are more fully described in the documents we file with the SEC.
Access to our second quarter fiscal year 2027 results, press release, transcripts, historical results, SEC filings and a replay of today's call can be found on the Investor Relations page of our website. The content of today's call, as well as the materials posted on our website, are Ambarella Inc's property and cannot be reproduced or transcribed without our prior written consent. Before starting the call, we hope to see you at one of the following investor events that we have scheduled in our third quarter.
First, on September 8th we'll host a D and B bus tour at our offices in Santa Clara. September 9th we'll be at Citi's 2026 Global TMT Conference in New York. September 15th we'll participate in Piper Sandler's Growth Frontier Conference in Nashville. September 16th we will host Sanford Bernstein's 8th Annual West Coast Semiconductor Bus Tour. And during the week of October 4th, we will have a European NDR with cities to be determined, also available to investors.
During the third fiscal quarter will be our booth and presentations at the AI Infrastructure Summit in Santa Clara on September 15 to 17. We hope to see you there where we will lead the physical AI track with a number of edge AI and robotics demos in our exhibit area. Fermi is now going to provide a business update for the quarter. Don will review the financial results and outlook, and then the three of us are available for your questions.
Fermi Wong, President and CEO
Thank you, Louis, and good afternoon. Thank you for joining our call today. Driven by a new record level of AGI revenue, we reported fiscal Q2 revenue slightly above the midpoint of our guidance with non-GAAP EPS of $0.18 and with guidance for seasonal fiscal Q3. By product, we are in the midst of a very steep revenue ramp with our 5 nanometer CV75 and CV72 AI SoCs, and by market we have sequential growth in both IoT and auto with automotive revenue driven by commercial vehicles.
The market is increasingly recognizing the strategic value of AGI, as well as our AGI and the physical AI platform leadership. We continue to make significant progress with the expansion of our AG platform leadership, including new go-to-market strategies and the engineering and market development for a number of new higher-value SoCs, some of which extend our reach into entirely new markets. We remain optimistic about the long-term secular growth opportunities in the AGI market and our R&D priorities are aligned with both the physical AI markets that represent a vast majority of total revenue today, as well as the robotic and edge infrastructure markets that are in the early stages of developing altogether. Our technology, product and new go-to-markets combined with the significant secular growth in AGI are increasing our five-year serviceable market forecast today. Before I review our new market forecast, I would like to step back and discuss the market environment we are in. Demand signals for the application of AGI remain strong. At the same time, it is obvious that memory vendors and the entire supply chains are prioritizing AI data center demand, which is resulting in rising supply chain costs for everyone.
Surging memory price and the scarcity of supply are impacting the entire industry. Related to this, we are providing significant assistance to customers who are attempting to create a wide variety of workarounds to the memory situation. Ambarella Inc itself is also facing rising supply chain costs, and we plan to pass this cost to our customer to maintain our long-term gross margin target of 59% to 62%. Returning to our rolling five-year serviceable market update, I would like to remind you of our methodology.
Our SAM for any given year is based on the products we expect to have available for production in that year overlaid on the total available market projections from a number of third-party research firms. So our five-year SAM captures any revenue-generating products, announced or unannounced, on our roadmap in the next five years. Our prior five-year rolling SAM was announced in May 2025 and projected five-year fiscal year 26 to fiscal year 31 compounded annual growth rate of about 18%, with auto representing a slightly higher proportion over the terminal year.
Our new five-year rolling SAM, from $8.5 billion in fiscal year 2027 to $22.9 billion in fiscal year 2032, represents a CAGR of about 20%, with IoT markets now representing about 70% of the terminal year. While there are several factors behind the strong growth and the underlying mix change, I will focus on the most important change. In the last year it has become clear that operational efficiency, or the ability of an enterprise to generate more revenue and/or to reduce expenses, is likely to be a key driver of our emerging edge infrastructure business.
Operational efficiency at the edge refers to the use of open-weight and distilled models running on on-premise inferencing hardware in contrast to the large frontier models that run in the cloud. Benefits of this approach include reduced latency, data protection, privacy, lower bandwidth cost and high reliability. Target markets include security, retail, lodging, logistics, healthcare and more. The on-premise operational efficiency use case has emerged with growing expectations for sustainable high-volume inferencing and, increasingly, for agentic AI and physical AI applications that can perceive, reason and ultimately act in the physical world.
The key question has become who can help the enterprise lower the cost per useful AI inferencing outcome. This is where Ambarella Inc's superior performance-per-watt portfolio kicks in, providing the efficient edge intelligence needed to enable this next-generation agentic and physical AI workload at scale. With this perspective, in the last year we have several new products in development targeting on-premise hardware, or what is commonly called AI infrastructure.
As you know, we already have our N1655AI SoC in the market, and we have additional unannounced AI SoCs in development. We also are implementing a standalone AI accelerator product line targeting the edge infrastructure market. Together, these new edge infrastructure products—both AI SoCs and standalone AI accelerators—represent the single most important reason for the upward revisions in our SAM. Before I introduce our first standalone AI accelerator, allow me to be clear about our terminology.
We define AI SoC as one integrating all of the accelerated computing functions into a single chip—camera perception, AI accelerators, CPUs, encoding, and so on. We define an AI accelerator as an AI processor that is not camera-specific and targets a wide variety of digital or physical modalities. We believe this type of multi-modality is critical for edge infrastructure applications like target operational efficiency. While not formally announced, I would like to preview one of the new AI accelerators that will anchor this new product category for us, with another well-defined, well-performing product already behind it.
We refer to this new AI accelerator as X7. This SoC is sampling now and expected to land initial design wins in edge infrastructure applications where it can serve as an AI coprocessor for host processors such as ARM or x86. Together with our new product thrust, expanded market reach and SAM, we expect our revenue growth to be supported with two incremental go-to-market strategies. First is the multi-step establishment of indirect sales channels, and the second is a semi-custom chip strategy, both of which will augment our existing direct sales efforts.
As a reminder, virtually all our revenue is generated by our direct sales teams, and today I'm excited to announce two material partnership agreements to develop our indirect sales channel. Combined, these two partnerships plan to drive a significant amount of incremental revenue over the next seven years through customers who have largely been unserved by us so far. First, today we announced Ambarella Inc's strategy partner with Capgemini, designed to help enterprises adopt AGI and physical AI solutions faster by reducing the complexity of moving from evaluation to scalable deployment.
By combining Ambarella Inc's power-efficient AI software and platforms with Capgemini's global engineering, system integration and industry expertise, the partnership aims to help customers improve operational efficiency, enhance real-time decision making and deploy intelligent systems in physical world environments with greater speed, scalability and confidence. In our second partnership to develop our indirect channel, today we also announced a seven-year agreement with Magnica, a leading global technical distributor.
Magnica will support both Ambarella Inc's physical AI and the new edge infrastructure products by developing and supporting an independent software vendor ecosystem, including onboarding, technical integration support and joint go-to-market programs. With this ecosystem in place, Ambarella Inc solutions can be offered as individual components or as a complete bundle for multiple edge AI vertical markets including video analytics, smart city, edge computing platforms, robotics, industrial IoT, intelligent transportation systems, retail analytics, security and surveillance.
I want to emphasize the importance of the indirect channel to serve small and mid-sized customers in highly fragmented markets like robotics. However, the indirect channel is also critical to support our more complex AI SoCs targeting the edge infrastructure, where a broad network of partners is vital for our long-term success. Meaningful revenue is expected in two to three years and will grow as we introduce new products for the market. Our second incremental go-to-market is our semi-custom opportunity, which can enable us to gain more share in existing markets and reach into new markets.
We have our first semi-custom project underway, the 2 nanometer CVA SoC, which is expected to generate first production revenue in fiscal 2028, and we are in discussion with other companies for additional semi-custom chip projects. Our representative customer engagement this quarter once again demonstrates Ambarella Inc's expanding traction across a broad set of applications. Robotics, automotive security trail cameras, and smart video intercoms with a CV72-based quadruped robot validate Ambarella Inc's high-resolution, multi-camera AI capabilities in robotics. A major S&P 100 communication equipment company announced an AI-based enterprise video intercom, further extending our reach in the emerging access control market. We landed another win with Moltree for AI trail cameras and a win with Canon, Suprema, IDIS, and CPRO.
We further strengthened our AI monitoring pipeline with CV75, CV72, and CV5 wins using our own AI SP software through Tier 1s. We had two in-cabin vehicle wins with Tier 1s in China, one for driver monitors and the other for a more complex camera monitor system used in Audi and VW vehicles. The breadth of these wins and the wide variety of corresponding AI workloads highlight the programmability and the flexibility in both our AI SoCs and our Cooper development platform.
This ease of use is facilitating the onboarding and expansion of our indirect sales channels. Very few competitors can offer this type of proven platform with more than 15 million AI SoCs shipped. In conclusion, I remain very excited about the overall growth opportunity of the AI market and our company's specific growth drivers put us in a unique position to benefit. Ambarella Inc is expanding beyond low-power AI SoC to deliver the complete foundation for physical AI, and we are becoming a full-stack physical AI platform provider.
With that I will now turn it to John.
John Young — Chief Financial Officer
Thank you, Fermi. I'll now review the financial highlights for the second quarter fiscal year 2027 ending July 31, 2026. I will also provide a financial outlook for our third quarter of fiscal year 2027 ending October 31, 2026. I'll be discussing non-GAAP results and ask that you refer to today's press release for a detailed reconciliation of GAAP to non-GAAP results. For non-GAAP reporting, we have eliminated stock-based compensation and acquisition-related expenses, adjusted for the impact of taxes.
In addition, this quarter, as described in our Q1 fiscal 2027 10-Q filing, as a subsequent event, we recognized a $9 million reduction in our GAAP research and development expense due to the cancellation of a customer's development project. We do not expect any impact on our non-GAAP outlook from this development. For fiscal Q2, revenue was $108.1 million, slightly above the midpoint of our prior guidance range of $105 to $111 million, up 7.7% from the prior quarter and up 13.2% year over year.
Automotive revenue established a new revenue record on continued strength as the commercial vehicle adoption of AI remains strong, and auto revenue slightly outpaced the growth in our IoT business where our enterprise-driven businesses outperformed our consumer-led businesses. Non-GAAP gross margin for fiscal Q2 was 59.3%, below the midpoint of our prior guidance range of 59% to 60.5%. Non-GAAP operating expense in Q2 was $57.4 million, slightly below the midpoint of our prior guidance range of $56 to $59 million.
Q2 net interest and other income was $1.8 million. Q2 non-GAAP tax provision was approximately $344,000. We reported Q2 non-GAAP net profit of $8.2 million, or $0.18 per diluted share. Now I'll turn to our balance sheet and cash flow. Fiscal Q2 cash and marketable securities were $272.3 million, decreasing $5.5 million from the prior quarter but increasing $11.1 million from the same quarter a year ago. The sequential decrease in cash and marketable securities was primarily due to higher payments for IP licenses receivables.
Days sales outstanding decreased from 35 to 32 days, while inventory dollars declined 4%. Sequentially, the days of inventory increased from 145 days to 157 days. Operating cash outflow was $260,000 for the quarter. Capital expenditures for tangible and intangible assets were $6.8 million for the quarter. Free cash outflow was $7.1 million for the quarter. During the second quarter of fiscal year 2027, we did not repurchase shares of our stock. During the second fiscal quarter, Ambarella Inc's Board of Directors authorized a new $50 million repurchase program valid through June 30, 2027.
The repurchase program does not obligate the company to acquire any particular amount of ordinary shares, and it may be suspended at any time at the company's discretion. WT Microelectronics, a logistics partner in Taiwan that ships to multiple customers in Asia, was 60.2% of revenue for the second quarter. Acuto, a logistics and distribution partner in Japan, was 11% of revenue in the quarter. I'll now discuss the outlook for the third quarter of fiscal year 2027.
We are anticipating favorable seasonality in our fiscal third quarter with revenue in the range of $115 to $124 million, or $119.5 million at the midpoint. At the midpoint, we expect our growth to be led by physical AI demand from the IoT market. We expect fiscal Q3 non-GAAP gross margins to be in the range of 59% to 60%. We expect non-GAAP OpEx in the third quarter to be in the range of $56.5 to $59.5 million. We estimate net interest and other income to be approximately $1.9 million, our non-GAAP tax expense to be approximately $700,000, and our diluted share count is expected to be approximately 44.9 million shares.
Thank you for joining our call today. And with that, I'll turn the call over to the operator for questions.
OPERATOR
Certainly. And ladies and gentlemen, we ask that you please limit yourselves to one question and one follow-up. And our first question for today comes in the line of Christopher Rowland from Susquehanna. Your question please.
Dylan Olivier, Analyst at Susquehanna
Hi, this is Dylan Olivier on for Christopher Rowland. Thanks for taking my question. So it's nice to see your roadmap sort of expanding. And I know that you announced this X7 accelerator. I was hoping to hear a little bit more about this new chip. Is this a chip that you can bundle with your existing N1 portfolio or does this address a different part of the stack? Thank you.
Fermi Wong, President and CEO
So yes, Chris, for the X7, this chip is an accelerator which can be bundled with any host, including our own chip. In fact, some of our customers using a certain part number, when they feel they need to have more AI performance for certain workloads, the X7 gives them the flexibility to upgrade the product without redesigning the board. So this accelerator definitely is a way to design that. In addition to supporting our own SoCs, any other CPU like ARM or Intel CPUs, we can also bundle X7 with that as an accelerator.
Dylan Olivier, Analyst at Susquehanna
Great, thanks. Appreciate this. And for my second question, I wanted to ask about sort of the physical AI and humanoid opportunity. Is this responsible at all for this increase in SAM? Are there any new engagements or new designs that you can point us to? Thank you.
Fermi Wong, President and CEO
Yeah, so definitely that's a big part of that. And in the last earning call we talked about 15 design wins for the robots including for roughly $100 million. Although we didn't give you another breakdown, I can say that we added more design wins to live pipeline and the higher revenue target. So from that point of view we'll continue to make progress. But in addition to robots, I also think that edge infrastructure and also enterprise security as well as portable video are all the reasons that we are increasing our SAM number.
Louis G., Corporate Development, VP
Yeah Dylan, we did. Fermi mentioned a quadruped robotic dog with a CV72 chip this quarter. So we continue to add onto the robotics wins we've described before.
Dylan Olivier, Analyst at Susquehanna
Thank you.
OPERATOR
And our next question comes from the line of Joe Moore from Morgan Stanley. Your question please.
Joe Moore, Analyst at Morgan Stanley
Yeah, thank you. I wonder first, in terms of the broader ecosystem, you talked about some of the challenges of memory. What is that meaning for your business, do you think? Is there a risk of pull-forwards or things like that because people are trying to get ahead of memory price increases? Is there pressure on you? Just, you know, what are you seeing from that memory impact from your customers?
Fermi Wong, President and CEO
We continue to monitor this situation very closely, talking to customers all the time. For Q3, we are comfortable with the guidance we provided today. In Q4, we continue to tell the customer to make sure our customers will have—we can secure—enough memory for Q4 business. That's definitely the uncertainty that we are dealing with.
Joe Moore, Analyst at Morgan Stanley
Okay, that's helpful, thank you. And then in terms of opening up to a broader ecosystem, distribution partners, things like that, I think you made the comment about that would take a couple of years to inflect. I guess I would sort of think that those customers would act a lot more quickly and that pipeline could build a lot more quickly than what you had seen previously in automotive. Just what was the comment that I maybe misunderstand there? And then what is the timeline to start to see traction from that kind of broader ecosystem?
Fermi Wong, President and CEO
When I say two to three years, we talk about meaningful revenues. And I agree with you that, in fact, we already start seeing a small amount of design wins which can generate revenue next year. But when we talk about meaningful revenue that will have an impact to our revenue forecast, I think that will take two to three years. In fact, when we talk to both Capgemini and Macnica, the range of revenue we are expecting from this collaboration is a half a billion dollars with each one of them.
So from that point of view, we definitely look forward to gradually ramping up the revenue for the next couple years and start seeing meaningful revenue behind that.
Joe Moore, Analyst at Morgan Stanley
Great, thank you.
OPERATOR
Thank you. And our next question comes from the line of Tore Svanberg from Stifel, your question please.
Tore Svanberg, Analyst at Stifel
Yes, thank you, and congratulations indeed. Macnica and Capgemini partnerships. I'm curious on those, Fermi, what are some of the early use cases that those two partners are going to be helping you with? Maybe you can call out some markets or applications. And how should I think about that in the context of your Cooper platform? Are they going to be working with you on Cooper? Are they going to be providing some of their own software? Just curious how that's going to play out.
Thank you.
Fermi Wong, President and CEO
Right, so let me answer the second question first. Yes, both of them will use Cooper. In fact, that's a key driver for them to select working with us, because they see a very mature software platform they can immediately tackle on and start building around it, generating infrastructure for their own product line. So our mature AI SoC as well as a mature Cooper software platform is the probably most critical engineering aspect that we offer to our partners.
Go back to the potential market that we are talking about. In fact there are multiple of them, and in fact when I talked to Macnica's CEO in that meeting, they highlighted that they are already winning design wins with our solution on drones, on retail channels, and also manufacturing. So you can see that it's a really large market; however, most of the design wins are small and segmented at the beginning, but if they can ramp up to larger volume of business, that will take time.
But we already start seeing our partners start talking about different applications.
Louis G., Corporate Development, VP
Tore, it's Louis. They can work together as well. As Fermi said, Macnica can serve small to mid-sized markets that oftentimes are very fragmented. But really for Capgemini it's large enterprise customers, and you can look at who they talked about before. Those are the type of customers we'd really go after with them. So they're very complementary to each other.
Tore Svanberg, Analyst at Stifel
Very good. And as my follow-up on the edge infrastructure market, this is obviously a completely new area. It sounds like that's the sort of biggest contributor to your increased SAM. I'm just curious, who are going to be some of your partners there? I mean, are these going to be your end customers sort of building their own infrastructure, or is there going to be an intermediary company that's building it? Is it going to be the traditional server guys?
Just curious how that's all going to play out. Thank you.
Louis G., Corporate Development, VP
Well, I think obviously we're going to continue to talk to some of the
Fermi Wong, President and CEO
Larger customers directly, but at the same time we're counting on Capgemini and Macnica to help us to penetrate because they're already in that market. They're already selling solutions to existing AI customers with their existing solution. So working with them will help us to ramp up our revenue much faster than just us talking to customers directly. Thank you.
OPERATOR
And our next question comes from the line of Quinn Bolton from Needham and Company. Your question please.
Quinn Bolton, Analyst at Needham & Company
Hey guys, thanks for taking my question. I just wanted to ask, longer term on the Macnica and Capgemini partnerships, does that change the long-term gross margin target? I assume that there's probably some allocation of revenue that would be attributed to those partners, and so wondering if that has any gross margin implications as that indirect channel ramps.
John Young — Chief Financial Officer
Right. So today I think our long-term gross margin is still 59 to 62%. We are definitely trying to continue to watch because we just started ramping up this business. If there's any change, we'll definitely inform our investors. But today, after we talked to Capgemini and Macnica, we don't feel there's any need to change that target today.
Quinn Bolton, Analyst at Needham & Company
Thanks. For me. And then I guess just a clarification on the $9 million charge for the project that was canceled. Was that a semi-custom project that was canceled, and does that have any impact on your expected revenue timeline for the semi-custom business?
John Young — Chief Financial Officer
Yeah. Thanks, Quinn. It is not one of the semi-custom opportunities that we've talked about. It was a development project with, I guess you could say, an automotive autonomy customer. And we've been negotiating the termination of that for quite some time, and in Q2 we finalized the agreement.
Quinn Bolton, Analyst at Needham & Company
Understood. Thank you.
OPERATOR
Thank you. And our next question comes from the line of Kevin Cassidy from Rosenblatt Securities. Your question please.
Kevin Cassidy, Analyst at Rosenblatt Securities
Yeah, thanks for taking that question. Going back to the shortage on the memory side, you've got near-term visibility, but I'm wondering on the designs — I know a lot of your customers, or the market out there, is probably dominated by a GPU-based embedded product that uses much more DRAM than yours would. Are you seeing any additional interest because you're more efficient with DRAM content?
Fermi Wong, President and CEO
Well, yes. First of all, the memory situation is dire for everybody but some of our competitors who have more money to buy multiple memories. However, any customer who comes to us for the edge AI or physical AI, they probably only used GPUs for their first-generation product and they understand. So the memory cost is just one reason, but more importantly it's power efficiency and other reasons. But the memory cost definitely is a driver for people to start considering what's the more efficient way to do the product.
So I agree with you that, in fact, almost all the customers who come to talk to us do so because of our power-efficient solution and the lower-cost solution than what they're using.
Kevin Cassidy, Analyst at Rosenblatt Securities
Okay, thanks. And maybe along the same lines, as with the AI accelerator you'd be competing against a GPU that uses a lot of memory. Also, what is the memory architecture inside your X7?
Fermi Wong, President and CEO
Well, in fact we need a much smaller footprint. For example, we only need 4 megabytes of memory for the accelerator running large language models. And more importantly, as an accelerator, the power envelope you have to fit in is anywhere between 4 to 5 watts in the current design. So all of the power efficiency, memory size, and also cost is really helping us to penetrate this market right now.
Kevin Cassidy, Analyst at Rosenblatt Securities
Okay, great, thank you,
OPERATOR
Thank you. And our next question comes from the line of Suji Dasilva from Roth Capital. Your question please.
Suji Desilva, Analyst at Roth Capital
Hi, Fermi, John Lewis. Just a clarification, Fermi, on the X7 chip — is that competing really only with edge GPUs, or is it other AI specialty chips? Or how should we think about the competitive landscape for this new offering right now?
Fermi Wong, President and CEO
Well, in addition to Nvidia and Qualcomm having similar products in this market space, there are probably 50 startup companies doing similar chips. So it's a crowded space. However, at the end it's really about power efficiency, because to run a certain workload you have to have not only a power-efficient solution, but mature hardware and software, which I think we are one of the very few that can do that today.
Suji Desilva, Analyst at Roth Capital
Okay, that's helpful, Fermi. And then my other question is, you're talking about customization now, projects. I'm just wondering what's precipitated the demand from the customers or your push to provide customization. What's newer versus your standard product history that's driving the need for that, or your desire to do that.
Fermi Wong, President and CEO
I think you are talking about the optimization for the memory situation, is that correct?
Suji Desilva, Analyst at Roth Capital
Semi-custom. I apologize.
Fermi Wong, President and CEO
Yeah, yeah. For semi-custom. In fact, we basically allow our customer to give us a spec and we build on the spec. However, when we negotiate a spec with a customer, we need to make sure that we can sell the spec to somebody else. So for the semi-custom chip, we pretty much build a purpose chip for the one customer, which they benefit from, but at the same time we can sell the chip to others that are not competing with the key customer. That's the business model and how it works on the engineering side.
But of course we'll try to offer as much of our own IP in those semi-custom chips as possible. For example, we have our own IP for the AI accelerator, the NPU for all the perception capabilities, including the ISP and encoder, the CPUs — all of those functional blocks are available for a customer to develop a semi-custom or custom chip with.
Suji Desilva, Analyst at Roth Capital
Okay, great. Thanks guys.
OPERATOR
Thank you. And our next question comes from the line of Liam Farr from BofA. Your question please.
Liam Farr, Analyst at BofA
Hi, yes, thank you for taking my question. Is there a way to frame how much memory cost inflation you're absorbing this quarter, either in basis points or maybe what gross margin would have been without any memory cost inflation? And is a passback above 60% feasible while memory prices stay elevated, or does that require pricing to come down? Thank you.
John Young — Chief Financial Officer
Right, so first of all the memory price doesn't impact our gross margin. It really only has a potential to impact how many chips our customers can buy. Because we don't buy memory and we don't resell memory, the memory price has no impact to our gross margin. So I think that answers your question. But the real question for us is how that memory cost can cause our customers to need to increase their price, whether that will reduce the total volume they can sell and therefore reduce the total ordering to us.
That's something we need to continue to observe. In Q2 and Q3 we see little impact on our revenue because of the memory situation. We continue to watch for Q4.
Liam Farr, Analyst at BofA
Thank you. And then I guess for my follow-up, Q3 is guided up, you know, 10.5% roughly sequential versus, you know, 13.5% last year. How much of, you know, this next quarter is normal seasonality versus, you know, underlying end-demand strength? And given you flagged Q4 memory supply, you know, obviously changing the demand picture, how should we think about Q4 seasonality and whether the full-year 10 to 15% is still reasonable for the guide? Thank you.
John Young — Chief Financial Officer
Right, so I think the outcomes here are still a little uncertain because of the memory constraint that you talk about. And like I said, we continue to talk to our customers to monitor how that impacts our performance in Q4. Barring any memory impact to our revenue, I think that you should expect Q4 with regular seasonality.
Liam Farr, Analyst at BofA
Thank you.
OPERATOR
And our next question comes from the line of Gus Richard from Northland. Your question please.
Gus Richard, Analyst at Northland
Yes, thanks for taking the question. Robotics architecture is looking an awful lot like an autonomous car in terms of what it needs to do. And I'm just wondering, you know, you have a domain controller for autos and you have the CD products — are you seeing any traction in domain controllers and, you know, any clarification on where you're seeing the strength? Is some of this coming out of China?
Fermi Wong, President and CEO
You know, first of all, you're 100% right that a lot of robot designs — the architecture looks just like a driving car, which I totally agree. However, I think the robotic market situation really reminds me of autonomous driving seven years ago, when at that time all of the automotive customers were trying to use individual modules and put a solution together and start demoing and selling the first-generation product. I think this is how we act with the current robots.
We see a lot of customers rushing out their first-generation product by putting individual components together to demo their capabilities. However, we do believe that the integration path of robotics will be very similar to what happened to the autonomous driving car. There will be people going to buy perception systems, but down the road people want to buy domain controllers. We do see both opportunities today. But I will say the majority of our customers today are asking for perception modules, perception solutions, but on their roadmap they want to have a way to buy a domain controller in the long run.
So I think we have a complete roadmap: we can sell just perception systems to a customer today. In fact, if people want to buy a domain controller for the brain of the robots, we have the solution too. Our plan is we're going to continue to develop solutions for both so that we can cover the total space of robotics.
Gus Richard, Analyst at Northland
Got it. And then just, you know, if I think about, again, robots — you know, cars are 2D and robots are 3D — and I'm just wondering, is one of the limitations of penetration training, and can you help your customers train robots, thinking about humanoid. But go ahead. Sorry.
Fermi Wong, President and CEO
Right. So in terms of training, it's really about how to collect data. One thing we help our customers with is we build a platform for people to collect data easily. And also we provide a platform that can provide a service to help people to label those data automatically, so people can use our system — the reference design — to collect data. In fact, some of the people doing mapping, generating the map — city mapping — are using our system to collect data, and also we are providing service to some of the automotive customers that we can use our tools to auto-label all of the data they generated.
Those are two things we can help to provide assistance on the training side.
Gus Richard, Analyst at Northland
Got it. Thanks so much.
OPERATOR
Thank you. Thank you. And our final question for today comes from the line of Martin Yang from OpCo. Your question please.
Martin Yang, Analyst at Oppenheimer
Hi, thank you for taking the question. Fermi, you sized the potential revenue from Capgemini and Macnica pretty similarly, but they face different varieties of customers. Can you maybe talk about the methodology you arrived at for those dollar figures? Is it similar methodology or a very different approach to size those potential markets?
Muneeb
Hi, I'm just Muneeb, just jumping in there. I think both Fermi and Louis were commenting earlier about how complementary they were. Right. So I think on the Magnica side, I think Lewis has commented it's large-scale, medium-large kind of customers we haven't addressed in the past. So think of them as a large-volume play, where we typically directly engage with high-volume customers. These will start aggregating a whole bunch of small, mid-sized customers that we did not have access to in the past. So it's a volume play, and I think Fermi already indicated that we're starting to see some small design wins come through with these distribution.
And then if you think about Capgemini, it's more of a value play, and I think Lewis indicated before these are large enterprises and customers who will bring complex solutions, deploy at scale to enterprises. So the modeling is on both slightly different: one is distribution channels, reseller scaling with small design wins, so building up small volume. The other ones are large customers and logos which have much larger opportunity deals but complex opportunities.
So on both sides the modeling is done on value versus volume, and I think the earlier question was also you should see different timelines on this. So we do expect faster timelines on the distribution side and more longer timelines on the more larger complex opportunities. But the modeling has been built out over seven years of how this will come to fruition. And of course some of them are new to our products, so initial ramp-up, market-making, pilot opportunities is what we are allowing for.
But we will keep you updated as we start winning some large deals and meaningful revenue, as Rami pointed out, in future quarters.
Martin Yang, Analyst at Oppenheimer
Great, thank you, Muneeb. I have a follow-up on X7. Is that accelerator chip primarily targeted as a channel product, or is there no distinction between for channel or for direct?
Fermi Wong, President and CEO
There's no distinction, and in fact I expect that both Capgemini and Magnica will do product reference design for that and target different customers.
Martin Yang, Analyst at Oppenheimer
Thank you, Fermi. That's it for me.
Fermi Wong, President and CEO
Thank you.
OPERATOR
Thank you. This does conclude the question-and-answer session of today's program. I'd like to hand the program back to Dr. Fermi Wong for any further remarks.
Fermi Wong, President and CEO
And thank all of you for joining our call today, and I hope to see you and talk to you next time.
OPERATOR
Thank you, ladies and gentlemen, for your participation in today's conference. This does conclude the program. You may now disconnect. Good day.
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