zsxq45544852255854448_415248411528288_谷歌20260430

Alphabet 2026年第一季度财报电话会议开场，介绍参会者及安全声明。AI投资推动业务增长：搜索收入增19%，云收入增63%超200亿美元，积压订单翻倍至4500亿。订阅用户达3.5亿，AI模型每分钟处理160亿token。

Welcome everyone. Thank you for standing by for the alphabet first quarter 2026 earnings conference call. At this time, all participants are in the list and only mode. After the speaker presentation, there will be a question in answer session. To ask a question during the session, you will need to press star one on your telephone. I will not like to have the conference over to you speaker today. Do you have freedom, head of investor relations, please go ahead. Thank you. Good afternoon everyone. And welcome to alphabet’s first quarter 2026 earnings conference call. With us today, our Sender Pachai, Phillips-Ginler, and an Ashkenazi. Now, I’ll quickly cover the safe harbor. Some of the statements that we make today regarding our business, operations, and financial performance may be considered forward-looking. Such statements are based on turn expectations and assumptions that are subject to a number of risks and uncertainties. Actual results could differ materially. Please refer to our forms 10K and 10Q, including the risk factors. We undertake no obligation to update any forward-looking statement. During this call, we will present both gap and non-gap financial measures. A reconciliation of non-gap-to-gap measures is included in today’s earnings press release, which is distributed and available to the public through our investor relations website, located at abc.xyz forward slash investor. Our comments will be on year-to-year comparisons unless we state otherwise. And now, I’ll turn the call over to Sender. Thanks, Jim. Hi, everyone. And thanks for joining us today. It was a perfect quarter for alphabet. Our momentum was on full display at Cloud Next Last Week, and the month of May brings even more with IO, brand-cast, and GML. I hope you tune into CR progress. It’s clear that our AI investments and full-track approach are driving performance across our business. In search and other, revenue grew 19%. People love our AI experiences like AI mode and AIO views, and they’re coming back to search more. Cloud accelerated again this quarter due to strong demand for our AI products and infrastructure. Revenue grew 63% exceeding $20 billion for the first time, under backlog nearly double quarter on quarter to over $450 billion. Jim and I enterprise a seeing tremendous momentum with 40% growth, quarter over quarter in paid monthly activities. In subscriptions, this was a strongest quarter ever for our consumer AI plans, primarily driven by adoption of the Jim and I app. Overall, the number of paid subscriptions is now reached 350 million with YouTube and Google 1 being the key drivers. Our AI models have great momentum. Our first party models now process more than 16 billion tokens per minute. We are there at API use by our customers up from 10 billion last quarter. Today, I’ll share our progress across AI full stack, then search and cloud followed by YouTube and other bets. Starting with our AI infrastructure, it’s the foundation of our full stack approach to AI driving customer growth and product adoption. Our custom TPUs, axion CPUs, and the latest NVIDIA GPUs continue to form the industry’s widest variety of compute options. NVIDIA GPUs are a core part of our AI accelerator portfolio, and will be among the first to offer NVIDIA very early in NVIDIA’s 72 in addition to the Blackwell and Hopper based instances already available. At cloud next, we introduced our age generation TPUs, individually specialized for training and serving, and able to take on the most demanding age intake workloads. TPU-AT provides high performance model training with three times the processing part of AI and board and two times the performance. TPU-AT delivers cost-effective low-latency inference with 80% better performance per dollar than the prior generation. This exceptional infrastructure powers a world-class AI research that includes models and tooling which continue to progress really well. Gemini 3.1 Pro continues to push the frontier in reasoning, multimodal understanding and cost. We have quickly expanded the Gemini 3.1 series of models to offer more choices for developers, including our cost-efficient flash models. 3.1 flash live, our latest audio model, has improved precision and reasoning, making voice interactions more natural and intuitive. It’s now powering conversational features in search and the Gemini app. Speech-to-text is now available in 70 languages. And the 3.1 Pro, our D-P research agent, got a big upgrade, including MCP support and native visualizations. Our generated media models are incredibly popular, the RE3 is generated over 150 million songs since launching on the Gemini app. Nanobana 2 reached 1 billion images in nearly half the time of Nanobana 1, and VEO 3.1 light is a most cost-efficient video model today. On top of this, we launch MFO, our most intelligent open model. It’s been downloaded over 50 million times in just a few weeks. In fact, our open models have now been downloaded over 500 million times. Looking ahead, we are focused on pushing the next frontiers of foundation models, including intelligence, agents, and agentic coding. And we are using the latest technologies to transform how we work as a company. For example, with anti-gravity, we are shifting to truly agentic workflows. Our engineers are now orchestrating fully autonomous digital task forces and building it a faster velocity, much more to come here. Next, we are bringing helpful AI into the hands of billions of people every day through our products and platforms. Earlier this year, we introduced personal intelligence, which helps people get more personalized and helpful responses. It’s now in the Gemini app, AI mode, and Gemini Chrome. Early traction has been good, and this month we integrated Nanobana 2 to make personalized image creation possible in the Gemini app. Maps recently got its most significant upgrade in over a decade with Gemini. Users can now have a conversation with Maps and get more personalized suggestions and intuitive directions. And the Pixel 10A launched a positive reviews, providing the best of Google AI features like Gemini Live and AI-powered camera features. Turning to search, AI continues to drive search usage in queries are at an all time high. The continuity investment improvements to AI overviews which are driving overall search growth and we’re also seeing strong growth in both users and usage of AI mode globally. Personal intelligence expanded broadly in the US and we are seeing people ask more personal questions and getting responses that are uniquely relevant to them. We also shipped agentic experiences like restaurant booking to new countries and new multimodal capabilities like search live globally. We are also continuing to improve efficiency and speed. Even as we’ve brought new AI features into our research page, we’ve reduced search latency by more than 35% over the past five years. And since upgrading AI overviews and AI mode to Gemini 3, we’ve reduced the cost of core AI responses by more than 30% thanks to continued hardware and engineering breakthroughs. We are excited to share more about search at IO. Now, over to Google Cloud. Google Cloud is differentiated because we have the only provider to offer first-party solutions across the entire enterprise AI stack. Our growth in revenue, operating margin and backlog highlight this differentiation. Our enterprise AI solutions have become our primary growth driver for cloud for the first time. In Q1, revenue from products built on our Gen AI models grew nearly 800% year over year. We are winning new customers faster with new customer acquisition doubling compared to the same period last year. We are seeing strong deal momentum doubling the number of 100 million to $1 billion deals year on year and signing multiple billion-dollar plus deals. And we are deepening relationships with existing customers. Customers outpace their initial commitments by 45% accelerating over last quarter. At Cloud next last week, we introduced hundreds of new capabilities across our vertically optimized AI stack that are designed to work together for our enterprise customers. We introduced a new Gemini enterprise agent platform that empowers users to build, orchestrate, govern and optimize agents with the controls that enterprise customers need. Along with new capabilities in Gemini enterprise app, like projects, canvas, long running agents and skills, every employee can build agents. In Q1, Gemini enterprise paid monthly active users grew 40% quarter over quarter. That includes major global brands like Bosch, City Belt, Merck and Mars Incorporated. Our partner ecosystem plays an increasingly critical role in driving Gemini enterprise adoption. We saw 9x year over year growth, both in seed filled with partners and in the number of partners adopting it for internal use. This momentum is leading to accelerating usage of our model. Over the past 12 months, 330 Google Cloud customers each processor were 1 trillion tokens. 35 reached the 10 trillion token milestone. To give agents business context from enterprise data to help them reason intelligently, we introduced a new agent data cloud. It includes a cross cloud lake house, knowledge catalog and deep research agents which combine research and analytical skills. As an example using our data cloud, American Express is enabling Asian tick commerce as scale by moving an enterprise data platform, along with hundreds of productions applications to BigQuery. What a bonus proactively resolving outages, automating network planning and precisely targeting capacity. Enterprise data has become critical for agents to reason. Our strength with BigQuery and Gemini enterprise has led Gemini powered workflows and BigQuery to grow over 30x year over year. As cyber security threats from the use of AI models accelerate, our expertise in AI and cyber security is driving strong demand for our agent tick defense offerings. In March, we closed acquisition of this, a leading cloud and security AI platform, which is an incredible fit for the moment we are in. We have seen tremendous interest from customers in our unique cyber security and AI products and services to protect their ideas state, the performance of this so far has exceeded our expectations. Together with Google’s strict intelligence, security operations and AI models, the business helping organizations detect, prevent and respond to threat. We introduced new Gemini powered agents for threat detection, continuous retrieving and automated remediation to protect software code and cloud systems. Customers like Deloitte, price line and shell are using our agent tick defense to strengthen their security posture. All of this is powered by the AI infrastructure I mentioned earlier. Our TPUs continue our leadership in performance, cost and power efficiency for customers like thinking machines lab, hearts and river trading and Boston Dynamics. As TPU demand, growth from AI labs, capital markets firms and high performance computing applications will begin to deliver TPUs to a select group of customers in their own data centers in a hardware configuration to expand our addressable market opportunity. Turning to YouTube where our momentum continues in the living room, US viewers are watching over 200 million hours of YouTube content daily. And as of March, we reached a new milestone with over 10 million channels now publishing short each day. This level of daily activity is a testament to how people enjoy this content and how we made it easier for creators. And in Q1, our YouTube music and premium offering saw its largest quarterly increase in the total number of non-trial subscribers, both globally and in the US since YouTube premium launched in June 2018. I hope you’re tuning to brandcast on May 30. Moving to other bets, Weimos on a great trajectory, it launched in Nashville a few weeks ago that makes 6 new cities so far in 2026 and operations in 11 major US cities in total. Weimos also surpassed 500,000 fully autonomous rights per week, doubling in less than a year. Wind continues to expand across the US in partnership with Walmart and DoorDash and announced plans to operate in the Bay Area. In summary, a terrific start of the year with so many great opportunities ahead, we are not slowing down. Huge thanks to all of our employees and our partners. See you at Io on May 19. Thank you. Thanks on door and hello everyone. As usual, I start with the performance of Google Services and then cover the progress we’re delivering across search, YouTube and partnerships. Google Services revenues were 90 billion for the quarter, up 16% year and year primarily driven by the continued growth of search, adding some further color to our results. Search and other delivered 19% growth primarily driven by retail and finance. YouTube advertising revenues were 11% driven by direct response followed by brand and network advertising revenues were down 4% year on year. Starting with search and other revenues which delivered 60 billion in revenue for the quarter. We are accelerating the deployment of Gemini across our entire as infrastructure to help businesses reach more customers in more places than ever before. This is driving significant improvement across all areas of marketing and continues to fuel new performance breakthroughs across three areas critical for customer success. Ask quality advertiser tools and new AI user experiences. First, ask quality. AI is boosting our ability to deeply understand user intent for given search query and to find the most relevant ad. Even when we don’t have a direct user query, we’re making significant strides and improving relevance. In Discover, new AI models and classifiers are driving higher relevance by better aligning ads with unique user interests. And maps where you think Gemini to ensure promoted pins are deeply relevant to user surroundings, location of interest, history and intent. This work is improving as a relevance by nearly 10% leading to significant increase in user engagement. We’re pairing the strength and prediction driven relevance with bottom of funnel precision. Over the past year, we’ve made over 20 improvements to search and shopping bits strategies. Smart bidding no use Gemini to match user intent to an advertiser’s product and services more accurately and further drive performance. This level of granularity was previously impossible to achieve at scale. Second, on advertiser tools, which Gemini helps advertisers drive more efficient and effective campaigns. People in the long search and fragments, they search conversational and share more context. We launched AI Max to help advertisers adapt to this new way of searching. And earlier this month, it moved out of beta with improved performance quality across targeting and creative capabilities. Take health and email. They captured one-third more clicks for a fifth of the spend. While some maintain this being increasing the average booking value by 55%. And Etsy, so a 10% search volume uplift with 15% of those queries being net new to their business. We see significant opportunity as advertisers continue to make good progress on AI readiness and the adoption of AI tools. For instance, more than 30% of our customer search spend, no users AI enable campaigns, AI Max or performance max. And these advertising are seeing more conversions for the same spend. Third, how we monetize new AI user experiences and search. We aren’t just bringing existing platforms into AI experiences. We are reinventing ads for this new era. Direct offers an AI mode, resonating with users and continue to receive positive customer feedback. Gap, laureale, and chewy are just some of the latest partners who have now signed up to test this Google ads pilot. We’re also exploring new formats for retailers. AI mode already surfaces organic product recommendations based on the user’s query. And we’re now testing a new ad format that displays retailers who sell those recommended products. In addition, the retail industry is rapidly coalescing around the open source universal commerce protocol. Or UCP, we launch in January in partnership with the ecosystem. Last week, we welcomed Amazon Midtown Microsoft sales force and stripe as new members to the UCP tech council. They join founding members Shopify, Etsy, target, wafer, and Google to further accelerate the transition towards an agentic future. Partners like Sephora and Macy have joined companies like Ulta Beauty, already rolling out UCP and can now redefine consumer journeys from discovery to checkout. Both of you did just last week on the agenda commerce within AI mode in search and the Gemini app. Shopify can now review product recommendations, compare options, and complete three-line checkout for eligible purchases directly with an AI mode and Gemini. Turning to YouTube, which now has less streaming watch time in the US for three consecutive years. We’re in an unmatched position to connect brands with the audiences they care about. In the moment they engage in, we’re applying Gemini to drive better matching and discovery between brands and creators of all sizes. Gemini now parsed YouTube creator partnerships, a centralized platform integrated directly into YouTube studio for creators and Google ads for advertisers. We’ve also made it easier to buy premium ass-bath and top-tier podcast shows by curating the most watched podcast into popular genres. For example, super-boop partnered with YouTube creator, Lisa Koshi on a multi-format short and long-form CTV campaign, resulting in a 93% lift with a low-screen product and a 55% overall brand lift. Looking at monetization across YouTube, momentum continues in short and living room, and the manager continues to drive momentum in direct response, in particular with smaller advertisers. Brandt who is benefiting from growth in a living room where we continue to scale creator brand deals. YouTube subscriptions revenue continues to grow faster than ass, particularly YouTube music and premium. By the end of Q1, YouTube premium line was fully launched in 23 countries and we plan to launch in more than dozen new countries in YouTube. As always, I’ll wrap with the progress we’re seeing across partnerships. Retellers are increasing looking to Google to support their AI transformation. This quarter, King Fisher, Target and Wafer, close significant multi-year cloud and ass deals. Combined with the implementation of UCP, these partnerships will help deliver personalized AI-driven agenda experiences from discovery to checkout. In closing, I’d like to thank Google’s everywhere for their contributions to our success, and as always, our customers and partners for their continued trust. I’m not over to you. Thank you, Philip. My comments will focus on your career comparisons for the first quarter, unless I state otherwise. I will start with results at the alphabet level and will then cover our segment results. I’ll end with some commentary on our outlook for the second quarter and full year, 2026. We had an outstanding first quarter, delivering our 11th consecutive quarter of double digit revenue growth. Consolidated revenue reached $109.9 billion, up 22%, or 19% in constant currency. Total cost of revenue was $41.3 billion, up 14%. Tech was $15.2 billion, up 11%. Other cost of revenues was $26.0 billion, up 15%. Primarily driven by increases in depreciation, content acquisition cost largely for YouTube and compensation. Total operating expenses were up 24% to $28.9 billion. Our endie expenses increased by 26%, driven by compensation due to investment in AI talent as well as depreciation. Sell the marketing expenses were up 23%, driven primarily by marketing investments to support the Gemini app and search as well as compensation. In GNA expenses increased 21%, primarily due to an increase in compensation cost related to legal and other matters. Operating income increased 30%, to $39.7 billion and operating margin was 36.1%. Other income expenses was $37.7 billion, representing a meaningful increase from the prior year primarily due to unrealized gains in our non-marketable equity securities portfolio. Net income increased 81% to $62.6 billion and earnings per share increased 82% to $5.11. We generate operating cash flow of $45.8 billion in the first quarter and $174.4 billion for the trelling 12 months. CapX was $35.7 billion in the first quarter with the overwhelming majority of this spent in technical infrastructure to support the AI opportunities we see across the companies. Approximately 60% of our investment in technical infrastructure this quarter was in servers and 40% was in data centers and networking equipment. Free cash flow was $10.1 billion in the first quarter and $64.4 billion for the trelling 12 months. We end of the quarter with $126.8 billion in cash and marketable securities and $77.5 billion in long-term debt. And as we announced today, our board of directors declare the 5% increase in the quarterly dividend. According to segment results, Google services revenues increased 16% to $89.6 billion reflecting strong growth in search and subscriptions. Google services revenues also benefited from a strong FX tailwind. Google search and other advertising revenues increased by 19% to $60.4 billion driven by growth in the retail and financial services verticals. YouTube advertising revenues increased 11% to $9.9 billion driven by direct response advertising as well as brand. Network advertising revenues of $7 billion or down 4%. Subscription platforms and devices revenues increased 19% to $12.4 billion due to strong growth in both YouTube subscriptions, particularly in YouTube music and premium. And Google wants subscriptions which benefits from increased demand for AI plans. Google services operating income increased 24% to $40.6 billion and operating margin was 45.3%. The Google Cloud segment deliver outstanding results in the first quarter. Cloud revenues accelerated across all key areas and were up 63% to $20 billion. Revenue growth was driven by strong performance in GCP which continued to grow at a rate that was much higher than Cloud’s overall revenue growth rate. The largest contributor to Cloud’s growth this quarter was AI solutions driven by strong demand for industry leading models including Gemini 3. In addition, we had strong growth in AI infrastructure due to continued deployment of TPUs and JPUs and Core GCP continues to be a sizable contributor driven by demand for infrastructure and other services such as cybersecurity and data analytics. Workspace again deliver strong double-digit revenue growth driven by an increase in the number of seats in the average revenue per seat. Cloud operating income was $6.6 billion tripling year over year and operating margin increased from 17.8% in the first quarter of last year to 32.9%. Google Cloud’s backlog nearly doubles sequentially reaching $462 billion at the end of the first quarter. The increase was driven by strong demand for enterprise AI offerings and the inclusion of TPU hardware sales that’s from their reference earlier. The majority of the backlog is related to typical GCP contracts and we expect to recognize just over 50% of the backlog as revenue over the next 24 months. In other bets, revenues were $411 million and operating loss was $2.1 billion. For the past few years, we have been working to prioritize our efforts and investments in the other bets. In Q1 of this year, barely completed an external capital race that resulted in its decomposition from Alphabet. G5R announced plans to combine with the Stound Broadband, which will result in its decomposition from Alphabet when the deal closes, which would be expected to take place in Q4. And we continue to allocate significant resources to businesses where we see meaningful opportunities to create values such as WAMO. Turn into our outlook, I would like to provide some commentary and factors that will impact our business performance in the second quarter and four year, 2026. First, in terms of revenues, we’re pleased with the overall momentum of the business. At current spot rates, we would expect to see an FX tailwind of approximately one percentage point to our consolidated revenue in Q2, compared to a 3 percentage point FX tailwind and the first quarter. In Google Cloud, as Sunder mentioned, we will begin to deliver a TPU hardware to a select group of customers and their own data centers. We expect to begin recognizing a small percent of the revenues from these agreements later this year, with the vast majority of revenues to be realized in 2027. It is important to keep in mind that revenues from TPU hardware sales will fluctuate from Q4 to Q4, depending on when TPUs are shift to customers. And finally, we’re excited to welcome the West team to Google Cloud with the closing of the acquisition march and our very pleased with the performance to date. A couple of items to highlight related to the acquisition. First, which will be reported in the Google Cloud segment. And second, we expect a low single digit percentage point headwind to clouds operating margin for the remainder of 2026 related to the acquisition. Moving to investment, we are updating our full year 2026 CapEx Guidance Range to 180 to 190 billion, up from our previous estimate of 175 to 185 billion, to now include investment related to the acquisition of intersect, which flows in March. We are seeing unprecedented internal and external demands for AI compete resources. The investments we’re making in AI is delivering strong growth, as evidenced by the record revenue and backlog growth in Google Cloud and strong performance in Google Services. Looking ahead, these strong results reinforce our conviction to invest the capital required to continue to capture the AI opportunity. And the result, we expect our 2027 CapEx to significantly increase compared to 2026. In terms of expenses, as we’ve discussed previously, the significant increase in our investment to technical infrastructure will continue to put pressure on the P&L in the form of higher depreciation expense and related data center operations costs such as energy. We also expect to continue hiring in key investment areas such as AI and cloud and are investing in marketing to support our AI products. You conclude, Q1 was an outstanding core for alphabet and our team’s continued to execute with high level of discipline and velocity delivering amazing innovation. We look forward to sharing more in the coming weeks and I.o. Google Marketing Live and BrainCast. I want to take this opportunity to thank our employees for their contributions to our performance. So under fill up and I will now take your questions. Thank you. As a reminder, task a question. You will need to press star one on your telephone to prevent any background noise. We ask that you please meet your line when your question has been stated. Your first question comes from Brian Novak with Morgan Stanley. Your line is now open. Thanks to me, my questions. I have to. The first one. It’s under on a recent podcast. You talked about how you were acutely constrained and compute something you’ve focused on almost every week to sort of make sure you’re deploying capacity correctly. So let me ask you this. As you sort of look at the search business. What are the areas that you are most excited about applying next generation compute toward? The sort of generate an ROI C on that return search in the next 12 months. And then the second one is on the sale of the TPUs to third parties. Just can you help us fill us up? We understand the strategy around pricing them. Given the high ROI C of using TPUs to power multi-year Google Cloud workloads a little bit. Thanks. Thanks, Brian. I’ll take the search one first. You know, obviously you’ve seen we are taking advantage of all our investments in building the Gemini models. And both obviously applying it in search and the Gemini app. Driving innovations in AIO views in AI mode and they’re all contributing to the increased usage of the product. I do think looking ahead across across both these surfaces. There is a massive opportunity to go deeper in what we do for our users. I think bringing agent take flows, workflows to consumers in a way that is easy for them to do, including in the context of search. I see as a huge opportunity ahead. And obviously we are in very, very early innings of all that. But our investments in in in our full stack of AIO projecting puts us in a good position to bring those experiences to search. And I’m pretty excited about it. On the second question around around TPUs. You know, obviously, you know, I would we do think about it as, you know, what are we doing through Google Cloud to help our customers. And, you know, that’s the framework with which we think about it. In that context, you know, there are situations where it makes sense. For example, you take customers like capital markets where they’re running this, you know, highly performing, you know, AI workloads. They wanted, you know, TPUs in there in their data centers. So there are, you know, and and those trends are through across a diverse set of industries and in certain cases frontier AI lab too. And so we are, you know, opportunistic about it. But I do think we step back and think about it over all as the opportunity for Google Cloud. A lot of it is providing infrastructure through Cloud. At times it is direct sales of TPU hardware as to a select group of customers. But again, you know, we we do take our OIC approach. And some of it helps us get more economies of scale scale in our overall computer environment as well. And so helps us in messing the cutting edge, which we need to do the next generation as well. Thanks, mother. Your next question comes from Duggenuts with JP Morgan. Your line is now open. Thanks much for taking questions. One for not and one for Philip. Uh, not you talked about 2027 cat bags that it’ll increase significantly. And I know you didn’t quantify, but how do you think about the current cat bags, trajectories, ability to service this massive backlog that you’ve built up in just the last quarter and what will no doubt increase going forward. And then Philip, you just talked more about the drivers of search queries at an all-time high. And then how are you how you’re thinking about how much room there may be to increase coverage of search queries. Just the ability to show ads against the higher percentage of queries than the 20% you’ve been at historically. Thanks. Thanks, that’s for the question. Let me start with your first question on the cat bags and how we think about cat bags increase. Going into 2027. So you’ve seen us over the past several years, increased cat bags every year. And we have done it very thoughtfully to meet the demand that we are seeing, both the external customers as well as demands across the organization. And you’re seeing the proof point. They are all I see on that in terms of just the growth rate we’re seeing, whether it’s growth rate within search or certainly the cloud business. And the opportunity we have within the cloud backlog. So as we’re seeing that robust demand across the business, we are looking at what can we do to support that growing demand. And the opportunity ahead of us. And increasing cat bags to meet that demand will provide more clarity in future earnings call about what that number will be. But that’s the opportunity we’re seeing ahead of us. It’s quite meaningful. And we want to make sure we capitalize that and we do it in a way that’s responsible as we’ve done today. So on the second part of your question, first of all, just to do one of our second. I mean, we’re very pleased with the performance of our as business here. And as I’m not sure, Google Services benefited from a strong FX tailwind that’s important to keep in mind. The strength we saw in search was not due to a single driver, but it was really the result of many parts of our business showing strength and working very well together. If I just deep that for signal to the vertical perspective, retail finance, I talked about it in health, drove the greatest contribution, although all major verticals actually contributed. And we make hundreds of changes every quarter to improve the user experience, the advertising experience. And so that’s really contributing to our performance here. And we’ve also been able to generate very strong as performance while significantly. Involving the search results page here. The queries continue to grow. And as Sundar mentioned, they were at an all-time high. We see a overviews and AI mode continue to drive greater search usage. And growth and overall queries, including in commercial queries, you specifically ask about the 20% on the coverage side. And as I said before, I think with the ability of AI to better understand intent and a lot of other vectors around it. I think there is an update in that coverage number. And overall, just the understanding that we have the Gemini on intent has just significantly expanded or ability to deliver ads on longer, more complex searches that were previously really difficult to monetize. And so, and I shared earlier, we are deploying our Gemini model to now across all of our as infrastructure. And it’s really driving improvements across the big three areas that are highlighted in my prepared remarks. Thank you both. Our next question comes from Eric Sheridan with Goldman Sachs. Your line is out open. Thanks so much for taking the questions. Maybe two of I could. The first one, just building on the answer so far, when you look at the backlog, you disclosed today. So now we’d love to know if you can come back to your comments on AI infrastructure. And your unique approach and how the position you’d either build capacity, scale, compute, and do it in a way that it is. As a not said, sort of effective from a margin standpoint, as well as a compute standpoint. Just understand where you sit competitively in your mind relative to others. That’d be one. And then Philip to bring you into the conversation. You referenced UCP and there’s been a lot of industry inertia around UCP very quickly. Talk to us a little bit about what UCP means for the services business as a agenda commerce scale in the years ahead. Thanks so much. Thanks, Eric. Okay, I do think part of, I do think we are genuinely differentiated. We are unique in the market because of our vertically optimized AI stack. And the way we co-develop the components from our infrastructure and models to platforms and the tools to applications and agents. And the fact that we, in our own frontier models, on the silicon, really helps us stay ahead of the curve. And on top of it all, just to put extra point on it, the deep investment in our security layers to keep everything safe. And I think we are the only provider in the market that offers all of these vertical stack. And so overall, again, to my earlier comments to Brian, I think about it all as Google Cloud. We can, we have many different ways to serve our customers. So we can meet them in a way suited to their needs. I think better than other players here. And I do think, you know, I do think, you know, looking ahead, our ability to invest in this moment and stay at the frontier. You know, I think put this in a strong position. And I think we are doing it based on tangible demand signals we are seeing. And it’s not just on the revenue side, but, you know, I’m talking from our ROIC framework. And, you know, that’s what is helping us navigate this moment responsibly. And to the second part of your question, look, and we’re in the early stages of the authentic era. The authentic is more than just completing the transactions. We all know this. We see a genetic experience as an editist. And it will really transform how we shop from discovery to decisions while helping obviously brands differentiate themselves. We’ve been very intentional about creating an identity experience that works for users or partners for the entire ecosystem. And our goal is really to remove the current work of shopping. So consumers can focus on the enjoyable part. For decades, you could either shop fast or smart. And I think with the agenda commerce, you no longer have to actually choose between speed and certainty here. And the vision is to make commercial experiences across the board. It’s just a more personal, more fluid. And we’re carefully designing space and agenda work flows for users to really see valuable components of their shopping journey. Beyond just price, such as customer service, brand loyalty, and more while removing the friction of the process. And I just talked about it. And this is exactly what a part of your question kicks in. The Universal Commerce Protocol. A new open standard for agenda commerce that works actually across the entire shopping journey from the discovery to the buying and the post-purchase support that we just talked about. And it was really a code developed with the industry leaders. Including, I mentioned that I’m Shopify, Etsy, Walmart and so on. And we’ve received tremendous feedback so far from hundreds of top tech companies, payments partners. A retailer is really interested in integrating. And it will help power a new checkout experience in AI mode and search and the Gemini app and allowing shoppers to actually check out from select merchants right at their researching on Google and going through this journey. So we’re very, very excited about it. Our next question comes from Ross Sanzer with Barclays. Your line is now open. Yeah, just following up on the last question on a gentic shopping. So it seems like we’re at the point in time where this is actually going to start happening finally. So fill up just to elaborate a little bit. As you, as you look at carrying the AdWords business from kind of the old way of doing things to this new agentic friction was shopping way. How do you see that the price and volume kind of growth trends for core average evolving as you start implementing more agentic workflows and search? Look, our number one focuses obviously on the user experience here. And I think the most important part in this is what I mentioned before. We’re carefully designing this space, indigentic workflows for the users to actually see the valuable components within that shopping journey. And the second you have the space, you obviously have the ability for interesting advertising models. I think it’s also worth noting that beyond just the traditional agents, there’s a lot of additional ways we can actually use AI to improve the shopping experience. And you can think about it like our apparel try on tools that is now available in the US. You can think about Google lens. So there’s a lot more to do here, but I think the key part is actually what I said before. We focus on the user experience here and then think I think all else will follow if we pay attention to the points I mentioned. Your next question comes from Michael Nathanson with Muffet Nathanson. Your line is now open. Thanks. One percent or one percent. If I can connect Brian’s question or question and go a little bit higher. I want to understand how you’re deciding how you’re allocating which divisions and projects get access capacity, even that you’re constrained. So how do you decide between all the internal projects you have and external projects, right? So what types of screens you’re running to decide who gets the investment capacity. And then to fill up, I noticed that you said it’s on the Gemini app. There’s more and more images that come to you in the shopping journey. You can talk to me and get thoughts about adding advertising on that app and what’s gotten your decision making here on adding ads on Gemini. Thanks. Thanks Michael, I think great question and an ongoing basis. I’m looking forward to Gemini helping me more and more if I’m thinking that through. Look, I do think that the foundation where we start with that is what do we need from a R&D standpoint to develop models of the front here. So what do you need for training these models? And so effectively the compute needed for JDM because it’s a foundation for everything we do. And so that’s a core principle that which we operate. And then obviously, you know, we, the ability to plan ahead. We are, we do, you know, we do long range plans on our core areas. Be it search, be it YouTube. And so on as well as what we see in Google Cloud. And obviously in Google Cloud, you know, we have the providing enterprise AI solutions, which, you know, which, you know, that year on year increase from the prior year. So we’re seeing strong demand for Gemini enterprise or AI solutions there. We see strong demand for infrastructure in Google Cloud. And as I said earlier, in flood cases, we are seeing demand for TPU hardware. TPU hardware and others data centers as well. So, you know, we are, we are modeling these out and working to allocate across across these areas. Obviously, we are compute constraint in the near term. And as an example, our cloud revenue would have been higher if we were able to meet that demand. So we are working through that moment and, you know, we are investing, but we have a robust, you know, long range planning framework. And, you know, we see extraordinary opportunities ahead. And, you know, we are allocating with that framework in mind. And to the second part of your question, as I said in my previous answer, we are all be the focused on the youth or first, and creating a really great user experience with all of our product, especially on your product. And specifically on monetization in the Gemini AI app, all focused right now is on AI mode. But it’s fair to say that we really believe a format that works well on AI mode would transfer successfully to Gemini app. And so, today, in the Gemini app, we are focused on the free tier and subscriptions and our AI plans were a sizable contributor to our Google One revenue growth. But let’s also be clear at, have always been a big part of getting products to reach billions of people. And if done well, as can be really valuable and really helpful commercial information. And at the right moment, we’ll share any plans as we have said, but we’re not rushing anything here. Thank you. Your next question comes from Mark Schmollek with Alliance for Insting. Your line is now open. Yes, thanks for taking the question. Phil, what more on search performances again? Yeah, you talked a few times about kind of optimizing for the consumer experience. And I guess the size higher query volume is a fair to conclude that consumers are using these AI tools, Google’s or otherwise. And it’s shrinking their purchasing journeys, converting it higher rates. And so, is there a way to dimensionize how much of the strength and search is being driven by that behavioral change? Against perhaps some of the newer advertiser AI tools that you’ve been launching it rolling out. Thank you. I think the way to think about it is really to think about the expansionary moment we see here for search. This is the key part. AI is fundamentally changing how the world searches for and how it accesses information. Of course, are in all time high as to understand this. Traditional search really started with 10 blue links. And now we have a overviews and a remote and they have made search more intelligent than ever. And they let you ask former complex questions. And we have lens or circle to search and we have search live. Search live is not available to all countries and languages that support AI mode. Again, shows you the expansionary nature of it. And we have our AI driven search campaigns. And we have no SMBs that can reach customers at a scale that really wasn’t possible even a few years ago. And you can add in Google translate and so on. So I feel if you’ve sector all of this in, we’re in a pretty good place in our quite excited about where this is going. Your next question comes from Ron Josie Wood City. Your line is now open. Great thanks for taking the question. Maybe this one is for or not. You know, we can keep with margins continue to expand here. I want to understand maybe if you could break down a cost drivers or really the drivers of margin expansion, particularly amongst the cloud. There’s a piece out there that AI revenues are a lower margin in general, but we are seeing margins improve. So more insights on just the cloud business and what’s driving that margin expansion. Obviously demand maybe pricing, but that would be helpful. Thank you. Sure, let me help unpack the margin expansion. Obviously we’re pleased to see that there are pushes and pulls across the business including the listing cloud specifically. And I would start with a top line when we see this robust, strong revenue growth, both in cloud and Google services. It does provide leverage all the way down to the bottom line within the income statement. And you know, we’ve been working hard to ensure we have, we’re running a productive and efficient organization. And it’s not just how we operate the business, but even in areas such as our technical infrastructure, where we are investing these significant context investments in data centers and servers. We are looking at how we drive scientific process innovation within that organization. And that is reflected both in cloud and Google services. We allocate cost based on consumption. In the past, I did talk about the depreciation associated with these investments that is hitting both Google cloud and Google services. Google cloud expanded margin quite significantly from a year ago, as you’ve seen in our numbers, that we just previewed. And a lot of it is the top line growth that Google cloud is providing and producing. As well as an incredibly efficient way of running the business. I will give Thomas and a team a lot of credit for running a very productive organization. And making sure that we are supporting our customers and providing the services and products that they want and benefit from. Continue to drive top line growth and doing this well within the middle of the income statement. All the way from a very efficient technical infrastructure thinking through how do we leverage AI across our business. As Sundar mentioned, the use of coding internally or how Gemini helps us there optimize in our real estate footprint. And we are going to continue to do this. This is not we are not going to stop here. We are going to continue to push for more efficiency knowing that we are going to have the headwind associated with the depreciation coming with higher. Capics level. Thank you very helpful. Our next question comes from Ken Garalski with Wells Fargo. Your line is now open. Thank you very much. Two of them I made please. First on the cloud and capacity. Pretty to think about how your verticalized capabilities enable you to navigate complicated supply chain, especially one experiencing inflation and constraints. Are you factoring any supply chain price inflation into 26. And 27 Capics commentary. And as part of that maybe not could you talk. Could you update us on the allocation of compute capacity internal versus external cloud and then one more please. When you think about search query volume growth, we are closing expanding use cases historically. You know, it’s it’s always been free to the consumer with and completely ad supported. You see future use cases where we’re a certain consumer use cases are more effectively monetized via subscriptions. And maybe a different mix of the consumer quote unquote search the new search opportunity. Thank you. All right. Can maybe there are a few parts to it. Maybe I’ll I’ll touch on it. And you know, on on overall compute, you know, I think I spoke earlier on how we think about allocation of compute across our. Our our businesses and you know, I think. Again, the long range planning and our OIC frameworks. You know, give us a good way to plan ahead. I do think we may obviously. We are. You know, working through a complicated supply chain environment as you point out and we’re factoring that into any commentary we give. But I think the scale of which we are operating and and our ability to work across all layers both. You know, our supply chain partners see the strength of our diversified businesses and the demand we drive and our frontier technology and and the investments all through this pack. I think I think they help us get into deeper partnerships all across the supply chain. I think that and I mentioned early the economies of scale point as well. So all of that factors in in a positive way there, I think. In terms of in terms of search. Look, I think we have we have proud that we build models at all. You know, we are at the frontier across the period of frontier. We do think about capability and the cost frontier deeply. So that we can serve users at scale. But at the same time, we can bring in the most powerful models for the most demanding queries. But, you know, the future as you are right that, you know, you know, in a valuable. As we serve more and more valuable use cases, there, there are going to be use cases where people will want. Want to use the most powerful model. And, you know, there may be different ways to accomplish that. So we are going to put the user first and support them in the way they want to use the product. And we are already, you know, provide, you know, various peers of our subscription plans in which you can get access to more powerful models. And that applies across your Google user experience. And including, including in search and, you know, you’ve seen the momentum. You know, we saw a very robust quarter in terms of our AI subscription scroll. You know, you know, driven by interest in getting access to better Gemini models. And so, I think that sets us up well to serve the breadth of use cases. People who want in all basis, including in search. Thank you. And our last question comes from Justin Postwip. Thank you. Thank you for taking my question. I expect a lot of interest in your TPU sales. So can you help us think about how you’re thinking about the opportunity there. And then maybe how much breakdown the backlog growth a little bit between TPUs and cloud. And then second question. Just think about the margins on these big gener of AI cloud deals. How do you think about, you know, these hundred billion dollar deals coming in and the margins associated with those. You can maybe similar to your cloud cloud business as it is. Thank you. So, you know, overall, I would say, look, we see tremendous interest in the tremendous demand for both AI solutions. As well as AI infrastructure, including, you know, massive interest in our, you know, GPU offerings. As well as TPUs. And so we are, you know, we are, you know, proud that we can provide customers with a very diverse, you know, with the breadth of our offerings. And, you know, let them, you can meet them in terms of whether needs are. And maybe I’ll pass it or not to give some color on the backlog growth. Yeah, so the backlog, the, the TPU hardware agreements that fund the reference in as prepared remarks are reflected in our cloud backlog of the $462 billion. Although the majority of the black backlog is still GCP agreements. Now, as you think about the total backlog, just over half of it will convert to revenue in the next 24 months. And the TPU hardware sales more specifically, we expect a small percent of them to see coming through as revenue later this year. And then the majority to be realized as revenue in 2027. And then anything on the big AI deal margins with the generative AI companies. So, I think nothing to comment on any specific contract, but overall earlier there was a lot of questions about how do we allocate and remember in a constraint environment. And we are choosing the allocate across all these opportunities. We are working off a robust RRC framework. Thank you. Thank you, and that concludes our question and answer session for today. I’d like to share the conference back over to Jim Friedland for any further remarks. Thanks everyone for joining us today. We look forward to speaking with you again on our second quarter 2026 call. Thank you, and have a good evening. Thank you, everyone. This concludes today’s conference call. Thank you for participating. You may now disconnect.