Super Micro Computer, Inc. (SMCI.US) Q1 Earnings Call: Sequential Decline in Gross Margin Does Not Mean AI Business Lacks Profitability; Days Sales Outstanding Decreased

Super Micro Computer, Inc. (SMCI.US) reported first-quarter fiscal 2027 results after the market close on Tuesday and held an earnings conference call. Q1 revenue was $19.95 billion, up 298% year-over-year, above the FactSet consensus estimate of $17.53 billion; non-GAAP diluted earnings per share were $1.81 versus an estimate of $1.23, and GAAP diluted earnings per share were $1.75. Non-GAAP gross margin was 12.8%, above the company's prior guidance of 12.0%12.5%, but down 4.8 percentage points from 17.6% in the previous quarter, making it the most concentrated point of questioning on the call. After the earnings release, the stock rose more than 7% after hours at one point, later extending to about 10%. Chief Financial Officer Mark Long responded that the sequential decline in gross margin was "not evidence that AI platform revenue lacks profitability," but rather reflected which customers took delivery in which quarter; looking at the fourth quarter and first quarter combined, the two quarters had revenue of about $31.1 billion and non-GAAP gross margin of about 14.5%, up about 5 percentage points year-over-year. The company raised its fiscal 2027 revenue target from $65 billion$72 billion to $72 billion$82 billion, but simultaneously expects second-half gross margin to be lower than the first half. The most concentrated line of questioning on this call was the sharp quarter-to-quarter volatility in gross margin. First-quarter non-GAAP gross margin was 12.8%, down 4.8 percentage points from 17.6% in the previous quarter, while the share of AI solutions revenue rose from 59% to 71% over the same period, leading the market to focus on whether large AI orders are diluting profitability. Chief Financial Officer Mark Long rebutted this directly: "The sequential decline is not evidence that AI platform revenue lacks profitability; it reflects which customers took delivery in which quarter." He suggested looking at the two quarters combined: the fourth quarter and first quarter together had revenue of about $31.1 billion and non-GAAP gross margin of about 14.5%, versus $10.8 billion and about 9.5% in the year-ago period, meaning revenue nearly tripled and gross margin rose about 5 percentage points. He also acknowledged that the full-year gross margin range implies the second half will be lower than the first half, because the AI revenue share will move toward the upper end of the 70%80% range. JPMorgan's commentary following the pre-announcement had already noted that gross margin fell significantly from 17.6% in the prior quarter and that margin sustainability remained a focus. The stock had fallen 27% over the prior month, with market doubts about AI capital expenditure efficiency as the main backdrop. In his opening remarks, Mark Long noted that about $2.3 billion of first-quarter revenue corresponded to deployments originally scheduled for earlier periods that slipped due to customer and data center readiness progress; excluding that portion, underlying revenue was about $17.6 billion. He emphasized that the full-year revenue range does not assume a repeat of this catch-up revenue, and that the range reflects continued sequential growth in underlying demand and significantly better visibility into customer deployment timelines than 90 days ago. In the quarter, one large data center customer contributed 44% of revenue, versus 28% for full fiscal 2026; the 10-Q also shows that two customers accounted for 49% and 17% of accounts receivable at quarter-end, respectively. Mark Long explained that this concentration is a product of the current scale of AI infrastructure buildout"the scale of a single deployment today can exceed our quarterly revenue a year ago"and he expects concentration to remain high during the buildout period, declining as enterprise and sovereign business expand. He added that deferred revenue increased by about $3.1 billion during the quarter, the vast majority of which was customer prepayments, that days sales outstanding fell from 59 days to 36 days, and that no material credit losses were recorded during the quarter. Operating cash flow remained negative; cash conversion cycle shortened by 52 days First-quarter net cash used in operating activities was $434 million, capital expenditures were $47 million, and free cash flow was negative $481 million; full fiscal 2026 operating cash flow was negative $6.8 billion. The company's cash conversion cycle fell from 149 days to 97 days, a 52-day improvement in a single quarter, equivalent to about $10 billion less working capital tied up at first-quarter revenue scale. Of this, inventory days improved by 45 days to 74 days, receivables days improved by 23 days to 36 days, while payables days shortened from 29 days to 13 days, consuming about $3 billion of cash. Cash and equivalents at quarter-end were $6.9 billion, bank borrowings and convertible notes totaled $8.6 billion, net debt was $1.7 billion, and inventory was $15.05 billion. The company said it was in compliance with all debt covenants at quarter-end. More than 8,000 racks per month by December; DCBBS and software are the margin levers. Charles Liang said the company is expanding fully automated capacity in Silicon Valley and Taiwan and accelerating containerized data center production in Asia and the United States, targeting more than 8,000 racks per month, including more than 4,000 liquid-cooled racks by December of this year. He repeatedly emphasized the commercial value of DCBBS (Data Center Building Block Solutions): covering deployments from gigawatt-scale AI factories to single-container PODs, combined with the three software suites SuperCloud Composer, Supermicro Datacenter Manager and Supermicro Operations Manager, as well as the recently expanded global field service organization, forming a bundle of hardware, software and services. He sees this combination as the path to returning gross margin to the double-digit range; in the Q&A he added that DCBBS is not just hardware modules but also includes software and services, and has become a business model for the company. The company expects second-quarter revenue of $19.5 billion$21.5 billion, gross margin of 12.0%12.5%, GAAP diluted earnings per share of $1.59$1.83, and non-GAAP diluted earnings per share of $1.66$1.90. The full-year revenue target was raised from $65 billion$72 billion to $72 billion$82 billion, with the midpoint of $77 billion about 12% above the original target midpoint; the full-year gross margin guidance is 11.8%12.2%, implying the second half will be lower than the first half. Mark Long made clear that what constrains the range is not demand, nor production capacity, but the readiness speed of customer data centers to receive already-manufactured equipment and the supply of key components: "The hard constraint on AI buildout across the industry right now is land, power and data center shells." Responding to doubts about AI capital expenditure efficiency, Charles Liang said the company can directly solve customers' ROI problem In response to recent doubts from investors and market experts about AI capital expenditure efficiency and return on investment, Charles Liang responded that the company has focused for more than 30 years on U.S.-based server and storage manufacturing, with a domestic engineering and manufacturing base that competitors find hard to match, and that combined with DCBBS hardware, software and services, it can "convert customers' capital investment into revenue faster and more cost-effectively than anyone" by compressing time-to-deployment (TTD) and time-to-online (TTO) and improving system availability and energy efficiency. He also disclosed that inventory and production cycle time has fallen from about 100 days to 74 days, with a target of further reducing it to 50 days over the next several quarters. New CFO makes debut, says he will focus on financial discipline and transparency This was Mark Long's first conference call as Chief Financial Officer. He said he has long worked in finance in the technology infrastructure sector and joined Supermicro because "the hardest part has already been built"engineering advantages, leadership in liquid cooling and rack-scale integration, and positioning in the largest infrastructure cycle in history; what the company needs now is financial capabilities that match its engineering and operational capabilities. He listed his priorities as financial discipline, transparency, deeper shareholder communication, working capital management and capital structure optimization, and said he would provide updates each quarter on dilution, maturity structure and available capacity. In response to a question from Bank of America Corp, he said the company currently has no equity financing plans, and that the debt market would depend on available conditions and a desirable leverage structure. Full transcript Opening and management remarks Host: Welcome to the Super Micro Computer, Inc. first-quarter fiscal 2027 earnings conference call. Present today are Founder, Chairman and Chief Executive Officer Charles Liang, Chief Financial Officer Mark Long, former Chief Financial Officer David Weigand, and Senior Vice President of Corporate Development Michael Staiger. Michael Staiger (Senior Vice President of Corporate Development): Thank you, and good afternoon, and welcome to the Super Micro Computer, Inc. first-quarter fiscal 2027 conference call. With me are Founder, Chairman and Chief Executive Officer Charles Liang, Chief Financial Officer Mark Long, and former Chief Financial Officer David Weigand. You should have received the company's press release, which was issued after the close of regular trading today and is also available on the company's website. This call is being webcast live on the company's investor relations website, and a replay will be available until the second-quarter fiscal 2027 earnings conference call. The content of today's call is the property of Super Micro Computer, Inc. and may not be reproduced or transcribed without the company's prior written consent. During this call, we may make forward-looking statements based on current expectations, including business plans and performance, continuing market trends and future financial results. These statements are subject to a number of significant risks and uncertainties, and actual results may differ materially. For factors that could affect future financial results and business, please refer to today's earnings announcement, our most recent 10-K and 10-Q, and the 8-K and other documents we may file with the U.S. Securities and Exchange Commission. All of our statements are made as of today, November 3, 2026, based on information currently available to us. Except as required by law, we undertake no obligation to update such statements. During this call we will discuss non-GAAP financial measures, and reconciliations are available in the presentation posted on the company's website. Our quiet period for the second quarter of fiscal 2027 begins at the close of business on Friday, December 11, 2026. I will now turn the call over to Charles Liang. Charles Liang (Founder, Chairman and Chief Executive Officer): Thank you, Michael, and thank you all for joining us today. After nearly doubling annual revenue in fiscal 2026, fiscal 2027 is off to a record start. First-quarter revenue reached $19.9 billion, exceeding the upper end of our pre-announcement and far above our initial outlook of $15 billion. This is a remarkable achievement and shows that more and more customers prefer our total AI and IT solutions. Most importantly, our Data Center Building Block Solutions (DCBBS) are at the core of this growth, bringing deep customer trust and preference, improving our profitability and creating sustainable long-term shareholder value. For more than 30 years, Super Micro Computer, Inc. has focused on delivering optimized total solution value to customers. We will continue to leverage engineering, global resources and high-yield manufacturing to accelerate customer deployments. In addition, I am pleased to see that not only large cloud service providers and neoclouds, but also companies and institutions in enterprise, storage, IoT and national and enterprise "sovereign" verticals rely on and adopt Supermicro's total solutions every day. In the first quarter we delivered on our commitment to improve bottom-line profitability. Non-GAAP gross margin rose 330 basis points year-over-year to 12.8%. This improvement came from an improved mix of enterprise AI and IT customers, a diversified product line based on system building blocks, and a higher revenue contribution from the higher-margin DCBBS moatincluding DCBBS hardware, software and unique service combinations. This is directly consistent with our strategic roadmap: building a sustainable double-digit gross margin model by delivering better technology innovation, faster time-to-market (TTM) and time-to-online (TTO), and total solution value. Validated by more than two years of real customer deployments, DCBBS delivers four core values that traditional server OEMs and overseas contract manufacturers cannot match: First, optimized time-to-deployment (TTD): delivering factory-tested, plug-and-play rack-scale systems and DCBBS modules (including complete data center management software) directly to customer sites. Second, optimized time-to-online (TTO): shortening compute online readiness from quarters to months, and further to weeks. Third, DCBBS maximizes system availability by eliminating cooling, power, software and service bottlenecks through modular design. Fourth, lower total cost of ownership (TCO): significantly cutting energy consumption and facility downtime, accelerating and improving data center profitability. Whether customers are building gigawatt-scale AI factories or deploying rapidly delivered single-container POD solutions, Supermicro's DCBBS helps customers build AI infrastructure faster, better, greener and at lower cost. Because optimized hardware alone cannot operate a high-efficiency AI data center, managing thousands of liquid-cooled GPU racks requires intelligent real-time software orchestration. SuperCloud Composer (SCM) provides seamless rack-level management and full-stack hardware-facility integration; Supermicro Datacenter Manager (SDM) provides complete power and thermal management from a single node to whole-building infrastructure, enabling end-to-end hardware lifecycle management; and our Supermicro Operations Manager (SOM) suite, including Director and Developer Console modules, makes bare metal, model and token-as-a-service easy for large language model and agentic AI workloads. Attaching SCM, SDM and SOM directly to the DCBBS portfolio eliminates software fragmentation for customers while increasing attach rates for high-value software. In addition, SCM's enhanced automated trouble-ticketing service now features AI-driven root-cause diagnostics, significantly improving data center availability and giving customers complete operational confidence. Equally critical is our recently expanded global data center services organization. Our field deployment teams, supported by R&D engineers and trained post-delivery service personnel, work directly with customer teams through tiered services to efficiently maximize cluster availability. Using automated telemetry, our service teams continuously monitor cooling, power and node health in real time, resolving potential issues before they cause downtime; dedicated field engineers handle deployment validation and immediate hardware maintenance. This proactive, high-touch service model builds deep customer trust, generates high-value recurring service revenue, and fulfills our highest commitment: delivering a completely worry-free experience with high-quality infrastructure total solutions. To efficiently deliver this unmatched breadth of solutions, our global manufacturing footprint and scale are ramping rapidly. We are actively expanding physical capacity, with major projects underway in Silicon Valley and Taiwan that will add millions of square feet of fully automated production space and proactive service capability. In addition, we are accelerating containerized data center production in Asia and the United States. Combined, our global manufacturing and service network positions us to produce more than 8,000 of the world's most powerful racks per month, including more than 4,000 liquid-cooled (DLC) racks by December of this year. On the technology front, Supermicro continues to lead the market across major chip platforms: We are among the first to ship NVIDIA Corporation Vera Rubin NVL-72 racks with DCBBS and the DLC-2 liquid cooling stack. We also recently introduced NVIDIA Corporation Rubin and Vera CPU racks, with optimized DSX-POD solutions coming soon. On the AMD side, demand momentum for the MI350 and MI355X platforms is strong, and we are advancing to Helios and MI-450 total solutions. In addition, we are advancing the Intel Corporation Xeon 6+ platform and new solutions based on ARM AGI CPUs optimized for the agentic AI market. At the same time, we continue to expand our comprehensive edge and IoT portfolio and to broaden our storage line, bringing real-time, complete inference capabilities directly to the intelligent edge. These new products accelerate our strategic focus on enterprise customersas enterprises scale to agentic models, enterprise data governance and high-throughput inference workloads. We recently announced several major strategic collaborations combining Supermicro's DCBBS with the world's leading technology companies, including Cisco Systems, Inc., NetApp, Nutanix and others. More tier-one partners will be announced soon as we embed Supermicro DCBBS deeply into the world's most trusted enterprises. I know some investors and market experts have recently raised questions about the efficiency and return on investment of AI capital expenditure. Let me be clear: Supermicro is uniquely positioned in this environment. For more than 30 years, we have focused on the U.S. server and storage industry, longer than almost any competitor, building a mature, complete domestic manufacturing and engineering base that competitors find hard to match. This deep U.S. foundation, combined with our unique DCBBS hardware, software and services total solution, directly solves customers' ROI challenge by optimizing time-to-deployment (TTD), time-to-online (TTO), system availability and energy efficiency. Whether customers are building hyperscale tier-one AI factories or deploying enterprise agentic AI workloads, Supermicro can convert their capital investment into revenue faster and more cost-effectively than anyone we know. We drive rigorous internal discipline through continuous operational optimization, factory automation, and skills upgrading from technology and process improvements and training. Over the past two quarters, we have successfully reduced inventory cycle time from about 100 days to 74 days. Looking ahead, we aim to further compress inventory and production cycles to 50 days over the next several quarters. This continuous efficiency optimization will continue to strengthen Supermicro's cash flow and working capital cycle and drive higher bottom-line profitability. No matter how intense the market competition, more customers will prefer Supermicro DCBBSincluding end-to-end data center hardware, management software and end-to-end data center services. Now for the fiscal 2027 outlook: Although overall demand and growth momentum are very strong across the board, we must also recognize that key component shortages are still affecting delivery times across the IT industry, including even GPUs. New customer projects and strategic ecosystem collaborations are ramping strongly, but we want to remain prudent about the availability and volatile prices of some key components. Based on what we see today, we expect fiscal 2027 revenue of $72 billion$82 billion, about 12% above the target set a quarter ago. Before I hand over the call, I want to highlight a few important personnel changes: First, we are pleased to welcome veteran industry technology leader Shesha Krishnapura to the board; his deep experience in data center operations will support our scaling. Second, I want to sincerely thank David Weigand for his leadership as Chief Financial Officer over the past six years, during our high-growth period, and we look forward to his continued support and contributions as we optimize operations at a larger scale. Finally, I am pleased to introduce Mark Long as our new Chief Financial Officer; his decades of leadership experience in technology and finance will strongly support our next phase of growth. I will now turn the call over to Mark. Mark Long (Chief Financial Officer): Thank you, Charles, and good afternoon, everyone. This is my first call, so please allow me two minutes before I get into the numbers. I have spent most of my career in finance roles in the technology infrastructure sector, including as Chief Financial Officer of a public company in this industry. What attracted me to Supermicro is that the hardest part has already been builtdeep engineering advantages, a real lead in liquid cooling and rack-scale integration, and critical positioning in the largest infrastructure buildout we have seen in our careers. What the company needs now is financial capabilities that match its engineering and operational capabilities. I am excited to join Supermicro at this critical juncture and look forward to helping Charles and the team continue delivering an expanding portfolio of innovative solutions to a growing global customer base, including some of the largest and most demanding customers shaping the future of the AI era. Doing so requires sustained financial discipline, transparency, deeper communication with stakeholders, working capital management and capital structure optimization, which will be my priorities. Now to the quarter. Total revenue was $19.9 billion, up 298% year-over-year and up 79% sequentially. This was above our guidance range of $14.5 billion$15.5 billion and above our October 20 pre-announcement range of $18.5 billion$19.5 billion. As Charles said, about $2.3 billion of this corresponded to deployments originally scheduled for earlier periods that slipped due to customer and data center readiness progress. Excluding that portion, underlying revenue was about $17.6 billion. AI solutions contributed about 71% of revenue, versus 59% in the previous quarter. Based on the current backlog, we expect AI-related solutions to account for about 70%80% of revenue in fiscal 2027. Enterprise and channel revenue was $4.9 billion, or 25% of revenue, up 229% year-over-year and down 12% sequentially. OEM equipment and large data center revenue was $14.7 billion, or 74%, up 321% year-over-year and up 167% sequentially, driven by volume ramps from multiple large AI data center design wins. 5G, telecom and edge grew significantly both year-over-year and sequentially, though from a relatively small base. By geography, the United States accounted for 80% of revenue, Europe 11%, Asia 6% and other regions 3%. The United States grew 771% year-over-year and 103% sequentially. Although the U.S. remains the largest market for large-scale AI data centers, we are also seeing momentum build in other regionslarge customers are expanding globally, and governments and enterprises are planning and investing in large AI data centers in Europe, Asia and the Middle East. In the quarter, one large data center customer accounted for 44% of revenue, versus 28% for full fiscal 2026. In the 10-Q you will also see that two customers accounted for 49% and 17% of accounts receivable at quarter-end, respectively. I want to provide more context on this. This level of concentration is an inevitable result of the current scale of AI infrastructure buildout. The scale of a single deployment today can exceed our quarterly revenue a year ago. We expect concentration to remain high while these projects are under construction and to decline as enterprise and sovereign business scale. As important as concentration is the quality of the exposure, and let me give you that. Deferred revenue increased by about $3.1 billion in the quarter, the vast majority of which was customer payments before delivery. Days sales outstanding improved from 59 days to 36 days. We recorded no material credit losses in the quarter. In large deployments, we often require deposits and typically invoice against delivery milestones; we assess counterparty credit before committing manufacturing capacity and key components; and we have an $1.8 billion accounts receivable purchase facility, providing flexibility on both cash timing and credit exposure. In this market, we have declined business whose terms we were not comfortable with, and in the current environment I expect we will continue to make such choices. Non-GAAP gross margin was 12.8%, 200 to 240 basis points above our guidance range of 10.4%10.8% and 330 basis points above the year-ago period. On a GAAP basis, gross margin was 12.7%. It was also 480 basis points below the 17.6% we reported in the fourth quarter, and I want to unpack that, because explaining it with a single factor would be misleading. The key factor affecting gross margin was the rise in AI revenue share to 71% in the first quarter from 59% in the fourth quarter. The customer and product mix in our first-quarter business skewed toward large-scale AI deployments, which carry lower gross margins than the more diversified enterprise and channel business. The benefit from tariff relief and lower inventory provisions in the quarter was largely offset by some low-margin deferred revenue recognized during the quarter. One point I want to be precise about, because I know how the structural data may be interpreted. The sequential decline is not evidence that AI platform revenue lacks profitability; it reflects which customers took delivery in which quarter. The clearest way to look at the underlying trend is to combine the last two quarters, which removes the timing effects of deferrals. The fourth quarter and first quarter combined had revenue of about $31.1 billion and non-GAAP gross margin of about 14.5%. In the year-ago two quarters, revenue was about $10.8 billion and gross margin about 9.5%. On this normalized basis, revenue nearly tripled and gross margin rose about 500 basis points. We continue to demonstrate significant operating leverage. Revenue grew 298% year-over-year, while non-GAAP operating expenses grew 89%. GAAP operating expenses were $477 million, up 67% year-over-year and up 5% sequentially. Non-GAAP operating expenses were $384 million, up 89% year-over-year and up 8% sequentially. The sequential increase reflects higher personnel costs and R&D investment in multiple new platforms for AI data centers and enterprise applications. Non-GAAP operating margin was 10.9%, versus 14.3% in the fourth quarter. Here too the two-quarter view is more useful. The fourth quarter and first quarter combined had non-GAAP operating expenses of about $741 million, or about 2.4% of revenue, and non-GAAP operating margin of about 12.1%, versus about 5.4% in the year-ago two quarters. We intend to continue investing in R&D, field service and global footprint, and we expect operating expense growth to continue to be significantly below revenue growth. Other income and expense was a net expense of $34 million, including $49 million of interest income and other income, offset by $83 million of interest expense on our convertible notes and revolving credit facility. The tax provision was $435 million on a GAAP basis and $455 million on a non-GAAP basis, both reflecting an effective tax rate of 21.4%. I want to add a few points on earnings per share from last call, because our capital structure now has an additional variable that I believe is not yet fully understood. We use the two-class method to calculate earnings per share, reflecting the mandatory convertible preferred stock we issued in the fourth quarter. The instrument pays a fixed dividend of about $75 million per quarter and will convert into common stock in June 2029. During this period, the dividend and the allocation of earnings to this participating security reduce the profit available to common shareholdersby a combined total of about $312 million this quarter. GAAP diluted earnings per share were $1.75, versus guidance of $0.89$0.98. Non-GAAP diluted earnings per share were $1.81, versus guidance of $1.01$1.10. GAAP basic earnings per share were $1.92. GAAP diluted shares rose from 705 million to 749 million, and non-GAAP diluted shares rose from 721 million to 764 million. Now to working capital, which I think helps explain the key elements of how we run the business. Our cash conversion cycle improved from 149 days to 97 days, a 52-day improvement in a single quarter. At first-quarter revenue scale, that difference equates to about $10 billion of working capital the company would otherwise have had to finance. The cash flow statement reflects this. We used $434 million of cash in operating activities on $19.9 billion of revenue. For full fiscal 2026, we used $6.8 billion of cash on $39.1 billion of revenue. Capital expenditures were $47 million this quarter, so free cash flow was negative $481 million, versus negative $7.0 billion in fiscal 2026. Let me break down the 52 days, including both the improvements and where there is still room to improve. Inventory days improved by 45 days to 74 days. Receivables days improved by 23 days to 36 days, helped by faster collections and customer prepayments. Payables days moved against us, falling from 29 days to 13 days and consuming about $3 billion of cash, reflecting the timing of payments to suppliers in a supply-constrained environment. The largest single driver was customer prepayments. Deferred revenue increased by about $3.1 billion in the quarter. Accounts receivable increased by $3.6 billion and inventory by $2.5 billion to support revenue ahead of us, with prepayments funding most of it. We expect the cash conversion cycle this quarter to be within plus or minus 10% of the first quarter, which allows us to manage working capital well while capturing attractive market opportunities. At quarter-end we held $6.9 billion of cash and cash equivalents. Bank borrowings and convertible notes totaled $8.6 billion, and net debt was $1.7 billion, versus $1.2 billion at the end of the fourth quarter. Inventory was $15.1 billion, up from $12.9 billion, built to support expected revenue over the next several quarters. We were in compliance with all covenants at quarter-end. More broadly on the capital structure: our starting point is solid. The $5.6 billion we raised in June was precisely to support the working capital behind the orders we are now delivering. As we identify high-quality growth opportunities, we will optimize the capital structure to support them, in a way that strengthens the balance sheet without incurring unnecessary costs. That means matching the tenor and form of financing to the working capital and assets it supports, and being prudent about when and whether to access the capital markets. I will keep you informed each quarter on dilution, maturity structure and available capacity. We ended the quarter with a record backlog, giving us greater visibility for this quarter and the remainder of the fiscal year. Turning to guidance. For the second quarter of fiscal 2027, we expect net sales of $19.5 billion$21.5 billion and gross margin of 12.0%12.5%. We expect GAAP diluted earnings per share of $1.59$1.83 and non-GAAP diluted earnings per share of $1.66$1.90. This guidance assumes GAAP operating expenses of about $455 million, including about $102 million of stock-based compensation, which is excluded from non-GAAP. We expect other income and expense (including interest expense) to be a net expense of about $58 million, a GAAP and non-GAAP tax rate of about 21%, GAAP diluted shares of about 753 million, non-GAAP diluted shares of about 769 million, preferred dividends of about $75 million, and capital expenditures of $70 million$80 million. For the full fiscal year, we are raising our revenue outlook from $65 billion$72 billion to $72 billion$82 billion. We expect full-year gross margin of 11.8%12.2%. Let me connect this to the quarter just reported. The first quarter included about $2.3 billion of catch-up revenue from deployments in prior periods, so underlying revenue was about $17.6 billion. The full-year range does not assume a repeat of this catch-up revenue. It assumes continued sequential growth in underlying demand and reflects significantly improved visibility into customer deployment schedules compared with 90 days ago. Our business continues to strengthen, and momentum is building for fiscal 2027, although we are constrained by supply and data center readiness; we are focused on disciplined execution, creditworthy counterparties and expanding higher-margin revenue streams. On gross margin, I want to be candid about what the full-year range implies. The first quarter was 12.8%, second-quarter guidance is 12.0%12.5%, and the midpoint of the full-year range implies second-half gross margin below the first half. This is a structural effect: as large deployments in the backlog ship, we expect AI solutions to move toward the upper end of the 70%80% range, and that business carries lower gross margins than the enterprise and channel verticals. Within each category, we expect gross margins to hold or improve. What determines this range is not demand, nor our ability to build, but the speed at which customer facilities are ready to receive our manufactured products, and the availability of key components. The hard constraint on AI buildout across the industry right now is land, power and data center shells. We have better visibility into this than in the past and will continue to update during the year. Let me return to the judgment I made at the outset. This was a quarter of strong growth with high-quality customers. Revenue nearly tripled year-over-year, gross margin was well above our guidance, and customer prepayments funded most of the working capital needed for delivery. Behind these results is a broad and innovative portfoliofrom DCBBS rack-scale and liquid-cooled systems to enterprise, storage, edge and softwarethat positions us to address the most demanding workloads and the widest range of use cases in AI buildout. My focus going forward is what I described at the outset: financial discipline, so that growth is profitable growth; transparency, so you can see how this business operates quarter by quarter, including the timing effects that affect our numbers; deeper communication with all stakeholders; continued working capital management building on this quarter's improvement in the cash conversion cycle; and capital structure optimization that supports high-quality growth on a solid foundation. I look forward to meeting many of you in the months ahead. Michael, we can open the call for questions. Q&A session Host: Thank you. We will now begin the question-and-answer session. Our first question comes from Katherine Murphy of Goldman Sachs Group, Inc. Research. Please go ahead. Katherine Murphy (Goldman Sachs Group, Inc. Research): Thank you for the question, and good to speak with everyone. I first want to ask about the raised revenue outlook. I understand land, power and data center shells are the current hard constraints, but I want to understand, in your full-year outlook and pipeline, what proportion of projects do you have visibility into the offtaker and committed volumes? I have a follow-up after that. Charles Liang: Yes, as you know, there are shortages of power and even some components like GPUs. But because our solutions are better than the industry's, especially with DCBBSDCBBS provides not only data center hardware modules but also software and services, helping customers build data centers faster and keep compute at better availability. Indeed, we continue to gain more customers and more share. We are quite optimistic about continued market share gains. Katherine Murphy (Goldman Sachs Group, Inc. Research): As a follow-up, could you talk more about customer prepayments this quarter and how we should think about them continuing to support your working capital efficiency? Is this a change we can expect, related to DCBBS and the market share gain strategy you discussed? Charles Liang: Yes, as you know, many companies are somewhat tight on cash flow. But at Supermicro, because we have better total solutionsagain DCBBSwe attract a lot of customers. Basically we see good signs. Most of our customers pay on time, and we feel very solid about continuing to grow the business. Mark, you can add some. Mark Long: Yes. I think the advantage, as Charles pointed out, is really the quality of the customer base. Very large, creditworthy customers pay very quickly, providing us with very strong cash flow. And the broader customer base is providing more prepayments, and that discipline allows us to fund more working capital. I think you should expect this to continue. So we feel we are in a very good position. Since the company's financing in the summer, and since the improvement in the cash conversion cycle, the company has done a lot, and working capital efficiency has improved substantially. Charles Liang: Yes. As we just shared, we improved our cash flow performance in two ways. First, we improved inventory and production cycle time from about 100 days to 70 days now, and we believe we can continue to improve production and inventory cycle time. Second, as Mark said, our customer quality is improving, and these customers pay on time or even quickly. So we are very solid on that front. Host: The next question comes from Ananda Baruah of Loop Capital. Please go ahead. Ananda Baruah (Loop Capital): Thank you for taking the questions. Congratulations on the progress, and welcome, Mark. I have two questions. The first is on gross margin and how we should think about its evolution over the remainder of the fiscal year. Correct me if I am wrong: to hit the midpoint of your guidance, although down year-over-year in the second half, the next three quarters are roughly flat at around 12%. Please correct me if that is wrong. The real question is, you mentioned the rising AI mix as one factor; could you talk about what the variables are for gross margin within the AI customer base? I recall Charles talked in the past about improving AI gross margins, and I want to understand the dynamics within AI gross margin over the remainder of the fiscal year. I have a brief follow-up after that. Thank you. Charles Liang: Yes, as I just shared, over the past three or four quarters, our production time as well as production quality and yields have improved substantially, which makes our cycle time faster and customers more satisfied, because better TTM and better TTO help customers go online faster. So customers recognize this. Combined with our DCBBS software and services, it further helps customers. And with higher-quality customers, we continue to gain more customers, especially enterprise agentic AI customers. So these all have a positive impact on our business. Mark Long: Yes, I want to add a point to what Charles said. On the full-year guidance, what you see is that we have good visibility, the business is now stabilizing and building a base in this roughly 12% gross margin range, with room to expand gross margin further as we continue to diversify the customer base and product mix. So, in terms of precise modeling, the judgment in your initial question is relatively close. But for us, visibility is very strong. As Charles pointed out, gross margins are improving across all our customer categories. That is what really matters. It is the result of the excellent engineering, excellent product portfolio and team execution Charles described. So we feel we are in a very good position at this scale and see a huge opportunity ahead. Charles Liang: Yes, like our DCBBS, we provide not only the hardware components of data center modular solutions but also software, and we help customers maintain availability. So these have almost become a business model for us. Customers like our products, and more and more customers like our solutions. Ananda Baruah (Loop Capital): That is very helpful context. A brief follow-up: given all the structural tailwinds this fiscal