Alphabet Inc. Depositary Shares representing a 1/20th Interest in a Share of Series B Mandatory Convertible Preferred Stock Q2 2026 Earnings Call

Welcome, everyone. Thank you for standing by for the Alphabet second quarter 2026 earnings conference call. At this time, all participants are in listen-only mode. After the speaker presentation, there will be a question and answer session. To ask a question during the session, you will need to press star one on your telephone. I would now like to hand the conference over to your speaker today, Jim Friedland, Head of Investor Relations. Please go ahead. Thank you.

Good afternoon, everyone, and welcome to Alphabet's second quarter 2026 earnings conference call. With us today are Sundar Pichai, Philipp Schindler, and Anat 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 current expectations and assumptions that are subject to a number of risks and uncertainties. Actual results could differ materially. Please refer to our forms 10-K and 10-Q, including the risk factors. We undertake no obligation to update any forward-looking statement. During this call, we will present both GAAP and non-GAAP financial measures. A reconciliation of non-GAAP to GAAP 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/investor. Our comments will be on year-over-year comparisons unless we state otherwise.

Now, I'll turn the call over to Sundar.

Hi, everyone. Thanks for joining us. We have exciting momentum. Alphabet revenue grew 24% year-over-year. Our AI investments are redefining what's possible across every part of our business. Our momentum starts with Search, where people are adopting one seamless Search experience across AI Overviews and AI Mode. We saw 17% revenue growth in Search and other, YouTube ads grew 13%. Cloud revenue grew 82%, powered by strong demand for AI infrastructure and AI solutions. Cloud backlog grew to $514 billion. It's great to see the wide adoption of Gemini Enterprise with nearly 90% of Fortune 100 using it. Today, I'll expand on our AI progress, our global product footprint led by Search and YouTube, Google Cloud's leadership, and our long-term bets. First, AI. Yesterday, we announced new models, Gemini 3.6 Flash and 3.5 Flash-Lite, which are cost-effective and highly efficient.

We are seeing tons of demand for our workhorse Gemini Flash series because it hits the sweet spot of performance and cost. We also launched Gemini 3.5 Flash Cyber, which I'm really excited about. Paired with our CodeMender agent, it finds and fixes vulnerabilities and delivers performance at the frontier comparable to far bigger cyber models. Gemini 3.5 Pro is currently in testing, and our team is already building the next generation of models. We have started our most ambitious pre-training run yet for Gemini 4 and are excited by the progress we are seeing at the frontier. Demand for our models is translating to strong token usage across developers and enterprise customers, and we continue to be supply constrained, a sign of momentum and rapid adoption. More than 9 million developers are building each month with our models across our APIs and key developer products.

Our model APIs are now processing approximately 22 billion tokens per minute. That's up from 16 billion just a quarter ago. This quarter, we launched Omni. It allows users to create anything from any input, starting with video. Since launching at I/O in May, there's been a 40% increase in daily active users creating videos on the Gemini app. Our Gemma family of open models, small enough to run on local devices, are hugely popular. These models have been downloaded over 900 million times, and our latest Gemma 4 models have been downloaded over 300 million times since launching in April. Our agentic development platform, Antigravity, allows anyone to build in the agent-first era. It has more than 2.4 million weekly active users. Antigravity is a powerful tool for users and enterprises, and it's completely accelerated how we build internally.

As just one example, a team in Chrome is now on track to accelerate delivery by 8 times, compressing a 2-year timeline into 3 months through model-driven refactoring. Moving on to our global product footprint, which brings AI to more people than any other company. Starting with Search, AI continues to drive an expansionary moment with new experiences resonating with users and driving growth in queries. As a big football fan, I was particularly excited to see Search usage hit an all-time high during the World Cup this year. This really highlights how much people turn to Google in moments that matter. We continue to make Search more helpful and intuitive. We recently brought together AI Overviews and AI Mode into one seamless Search experience that combines our frontier capabilities with the best of the web.

We are continuing to incorporate more frontier capabilities into Search with agents, personal intelligence, and notebooks. Our AI-powered features are driving increased Search usage. Since expanding AI Mode globally last October, we have surpassed 1 billion monthly active users. Just like AI Overviews, AI Mode is driving an incremental increase in Search queries overall, and we are now sending billions of clicks to websites every week through AI features in Search. As we serve more of these queries, we have continued to drive efficiencies. Thanks to our engineering and hardware optimizations, this quarter, we reduced the cost of AI Mode responses to its lowest level since launch, even as we have brought more advanced AI capabilities. Philipp will also talk more about how we are innovating the Ads experience.

Next, the Gemini app, which now has 950 million monthly active users with daily active users tripling in the last year. Users love new agentic features like Daily Brief and our personalized agent, Gemini Spark, which is now available in the U.S. and internationally. We've been shipping helpful new features like this at an incredible clip. On to YouTube. Month after month, when a big event happens in the world, the world turns to YouTube. It's been incredible to see that over 1.7 billion unique viewers globally watched World Cup-related videos on YouTube during the FIFA World Cup 2026. We're also bringing the power of conversational AI directly into the YouTube experience. Ask YouTube uses our Gemini models to let people ask complex questions about individual videos, get quick takeaways, and jump straight to moments in those videos. The early engagement is encouraging.

More than 140 million users engaged with Ask YouTube on the Watch page in June 2026. We are bringing that Ask experience to the wider search experience on YouTube. Next, Cloud. Our continued momentum is driven by our integrated AI portfolio consisting of chips, models, data, security, and agent platforms, all designed to work together. Gemini continues to be a key driver of growth and is deeply integrated across all of our cloud products, including Gemini Enterprise, data analytics, cybersecurity, and Google Workspace. We are seeing strong, diversified demand across products, customers, geographies, and industries. Our product differentiation is driving expansion in three ways. We are winning new customers, more than doubling our acquisition velocity year-over-year. We are deepening our relationships with existing customers who are expanding their usage and exceeding their commitments by more than 50%. Also, an acceleration over last quarter.

We are driving growth with partners, with transactions on Google Cloud Marketplace growing over seven times year-over-year. One of the strongest parts of our growth comes from the rapid adoption of our Gemini Enterprise platform. It's differentiated with easy-to-use tools to build agents and automate processes, connectivity to enterprise systems, cost management, and governance tools. In Q2, Agent Development Kit, our framework for building and deploying enterprise AI agents, reached nearly 70 million total downloads. As I said, nearly 90% of Fortune 100 are using Gemini Enterprise. We have customers like PepsiCo for AI and analytics solutions, Intel to streamline core processes, HSBC for wealth management, Bell Canada for customer engagement, Macy's for commerce experiences, and SIGNAL IDUNA for knowledge management.

More broadly, Gemini is transforming how millions of businesses use AI to build custom agents, automate processes, improve cybersecurity, manage customer relationships, streamline data analytics, collaborate effectively, and more. All of this momentum is driving growth in our paid token usage. Nearly 500 Cloud customers have each processed more than 1 trillion tokens in the last year, and usage is so much deeper than that. Over the last 12 months, more than 2,000 enterprises consumed over 100 billion tokens. We're also seeing strong interest in our AI-powered security platform, which is differentiated because it integrates threat intelligence, cyber response prioritization with Wiz, AI-automated scanning, code remediation, and monitoring. Today, 90% of Fortune 100 are Google Cloud security users.

Nearly 90% of VIS customers are using AI-powered security features. We have seen a more than 45% quarter-over-quarter increase in the number of AI workloads scanned and protected by our security platform. Our security tools are being used to protect critical infrastructure, including financial services organizations such as Morgan Stanley, telecommunication providers such as Telus, healthcare organizations such as Texas Children's Hospital, software companies such as Atlassian, and several government agencies. With our new Google AI Threat Defense, we are really excited to bring our new cyber model and CodeMender to help our customers defend against AI threats. All of this is powered by our leading AI infrastructure. We offer the industry's broadest range of accelerators from Google and NVIDIA, including the new NVIDIA Vera Rubin platform and TPU 8t and 8i, which delivers strong price performance. On top of this, let me mention three unique offerings.

First, our Virgo Network, which is designed to meet the needs of modern large-scale AI workloads. It allows customers to connect a million AI accelerators across multiple data center sites into a unified supercomputer. Second, our software stack has native support for JAX, PyTorch, vLLM, and SGLang, enabling workload portability across GPUs and TPUs. Third, our new agent-optimized Google Axion CPU provides 30% better performance per dollar compared to peer offerings. We are seeing strong growth and demand for our AI infrastructure offerings from leading labs such as Ineffable Intelligence, next-generation AI builders, including Kakao, financial services like Deutsche Börse Group, pharmaceutical companies such as Pfizer and Roche, and robotics and spatial intelligence companies such as World Labs. We are continuing our strategy of investing in promising companies and internal efforts that bring pioneering AI research into the real world. We have seen exciting progress from our other bets.

Waymo introduced its newest vehicle, Oasis, to public riders. This is the first vehicle powered by the sixth-generation Waymo Driver and will welcome more riders in the coming months. Wing has safely completed more than one million home deliveries. We continue to grow our presence through partnerships with Walmart, DoorDash, and Papa John's. In health and drug discovery, Isomorphic Labs raised over $2 billion to power its AI drug design engine, scale globally, and advance its drug candidate pipeline. It's truly been an extraordinary first half of 2026 with much more to come. Thanks to all of our employees and partners worldwide for their incredible work this quarter. With that, Philipp, over to you.

Thanks, Sundar, and hello, everyone. I'll start with a review of Google Services, highlighting our momentum across Search, YouTube, and partnerships. Google Services revenues were $95 billion for the quarter, up 15% year-on-year, primarily driven by Search. Search and Other delivered 17% growth, with retail and finance driving the largest contributions. YouTube advertising revenues grew 13%, driven by direct response and brand. Network advertising revenues were down 1% year-on-year. Strong performance in Search and YouTube underscores how our investments in AI translate into measurable value for our users and advertisers. Starting with Search and Other. Revenues reached over $63 billion for the quarter. Sundar highlighted the momentum we see in Search, which directly impacts our advertising business. We continue to accelerate the deployment of Gemini across our entire ads infrastructure to boost performance in three areas mentioned before: ads quality, advertiser tools, and AI user experiences. First, ads quality. At Google Marketing Live, we showcased how Gemini improves query understanding, allowing us to find relevant ads for longer searches previously difficult to monetize.

The core engine of our Search Ads relies on a dual prediction, delivering immediate utility for the user while maximizing measurable value for the advertiser. Gemini completely supercharges this capability. We use Gemini's advanced reasoning to decode the nuances of longer, more detailed queries. With shopping ads, for instance, we drove a 20% improvement in showing highly relevant ads, helping shoppers immediately find the best match. Second, advertiser tools. Take AI Max. It's out of beta, and half a million advertisers have already adopted it.

Those who adopt our AI-powered campaigns like AI Max or Performance Max, see an average of 15% more conversions or value on Search at a similar ROAS. AAA Auto Club Enterprises used AI Max to personalize creative assets and capture growth from increasingly detailed insurance searches. This led to a 17% improvement in conversion volume and an 11% decrease in cost per lead. We see strong adoption of our generative AI creative tools, which makes creative development easier, especially for SMBs. In fact, over half of our SMB customers globally use AI to create or optimize their creatives. Third, new AI user experiences. At I/O, we showed how Search, including AI Overviews and AI Mode, works as one connected experience. As you saw from our results, our performance across this holistic system is robust.

We continue to be encouraged with monetization performance on queries that show AI Overviews, even as we've expanded AI Overviews to more commercial queries. Across AI Overviews and AI Mode, people are asking more specific and detailed questions, providing opportunities for more relevant ads. Within AI Mode, we continue to test and deploy a range of new ad formats. For text ads, we improve performance by adding contextual site links based on the conversation. Direct Offers is gaining momentum, with partners like IHG Hotels & Resorts soon surfacing special offers during trip planning. In Highlighted Answers, our latest experience, placing clearly marked sponsored links inside list responses is showing early user traction. Looking at commerce. In collaboration with the retail industry, we established the open-source Universal Commerce Protocol, UCP, as the new standard for agentic commerce.

Merchants are rapidly adopting UCP, with Target and Steve Madden now live, while new members have joined the UCP Shopping and Food Tech Councils to help steer its vision. We also announced Universal Cart, allowing shoppers to add items from different retailers across Google Services and buy in a single checkout. Now on to YouTube. As a FIFA preferred platform partner, we helped fans around the world tune into the games. As Sundar mentioned, over 1.7 billion unique viewers watched World Cup-related videos, and over 550 million watched them on their televisions. This made the FIFA World Cup 2026 the most viewed World Cup in YouTube history. Advertisers connected with fans through FIFA channel takeovers, Gemini-powered soccer-themed sponsorships, and game day mastheads. Of course, a huge congratulations to Spain for taking home the trophy.

More broadly, on YouTube, we introduced an exclusive slate of creator shows making it easier for brands to tap into the fandom of creators. We launched custom sponsorships to put brands at the heart of the world's biggest moments as they unfold on YouTube, using AI to dynamically surface videos tailored to a brand's desired moment. Brands continue to partner with YouTube creators to engage new audiences. Kate Spade reached Gen Z through a first-of-its-kind YouTube creator campaign and partnered with creators Ellie Thumann and Hannah Meloche. By leveraging multiple format videos on YouTube, the brand drove a 3.25% brand lift in purchase intent. This unique convergence of brand equity and commercial action makes YouTube a powerful full-funnel platform. SMBs continue to fuel our direct response growth through campaigns like Demand Gen. They leverage our AI to scale visual storytelling across YouTube, Shorts, and now Google Maps.

To attract high-value shoppers across North America and Europe, outdoor brand Arc'teryx used Demand Gen to achieve a 70% better return on their ad spend compared to other paid channels. Looking at monetization across YouTube, we're driving sustained growth across our key priorities. In the living room, we see continued momentum across both brand and direct response. With the launch of Buy with Google Pay, viewers can complete purchases directly on their CTV, turning the TV screen into a stronger performance surface. Shorts continues to deliver high-performing opportunities for social and video buyers alike. Beyond advertising, YouTube subscription business, which thrives across living room screens, is growing faster than ads, particularly driven by YouTube Music and Premium. Internally, we leverage Gemini to transform how we work and how we serve our customers.

83% of our sales team uses Gemini-assisted tools weekly, driving up to a 20% higher win rate when using customized pitch narratives. Our ads customer support teams use Gemini-powered agentic solutions that now autonomously address 75% of support queries, freeing them to solve our customers' most complex challenges. Similarly, our new agentic solutions for SMBs have expanded our reach by hundreds of thousands of new customers year to date. As always, ending with partnerships. We're seeing more businesses benefit from the unified strength of Google's AI stack. Booking Holdings expanded a multi-year cloud commitment and are partnering closely to advance our AI-powered ad formats. It's also deploying Google's AI technology to enable new customer experiences like agentic dining reservations on OpenTable, helping restaurants get discovered and booked right when it matters most.

In closing, I'd like to thank Googlers everywhere for their contributions to our success and our customers and partners for their continued trust. Anat, over to you. Thank you, Philipp.

My comments will focus on year-over-year comparisons for the second quarter, unless I state otherwise. I will start with results at the Alphabet level and will then cover our segments result. I'll end with some commentary on our outlook for the third quarter and full year 2026. We had an outstanding second quarter, delivering our 12th consecutive quarter of double-digit revenue growth. Consolidated revenues were $119.8 billion, up 24%, or 23% in constant currency. Total cost of revenues was $45.9 billion, up 18%. Tech was $16.2 billion, up 10%. Other cost of revenues was $29.8 billion, up 22%, driven by increases in depreciation, inventory costs, primarily from the sales of TPU systems to customers, and content acquisition costs, largely for YouTube. Total operating expenses were up 27% to $33.1 billion. R&D expenses increased by 32%, driven by compensation from investments in AI talent as well as depreciation.

Sales and marketing expenses were up 18% due to investments to support the Gemini app and Search and compensation. G&A expenses increased 24%, primarily driven by compensation and charges for certain legal and other matters. Operating income increased 30% to $40.8 billion, and operating margin was 34%. Other income and expenses was $98 billion, representing a substantial increase from the prior year, primarily due to unrealized gains in our equity securities portfolio. Net income and earning per share increased significantly, primarily due to the unrealized gains in OI&E I just mentioned. We generated strong operating cash flow of $39.1 billion in the second quarter and $185.7 billion for the trailing 12 months. CapEx was $44.9 billion in the second quarter, with the vast majority of this spent in technical infrastructure to support our investments in AI.

Approximately 60% of our investment in technical infrastructure this quarter was in servers, and 40% was in data centers and networking equipment. We had negative free cash flow of $5.9 billion in the second quarter, driven by our investments in CapEx. Free cash flow was $53.3 billion for the trailing 12 months. We ended the quarter with $242.5 billion in cash and marketable securities, which includes $87.1 billion of marketable equity securities. Long-term debt was $98.2 billion. As mentioned in our press release, our board of directors declared a quarterly cash dividend on our common stock of $0.22 per share, which is payable in September. Turning to segment results, Google Services revenues increased 15% to $94.5 billion, reflecting strong growth in Search and subscriptions. Total advertising revenues were up 14%, with growth across all major verticals.

We experienced strong ad growth related to the World Cup, particularly in YouTube ads. Google Search and other advertising revenues increased by 17% to $63.3 billion, with retail and finance driving the largest contributions. YouTube advertising revenues increased 13% to $11.1 billion, driven by direct response advertising as well as brand, with strength in the living room, as Philipp mentioned earlier. Network advertising revenues of $7.3 billion were down 1%. Subscription platforms and devices revenues increased 15% this quarter to $12.9 billion, due to strong growth in both YouTube subscriptions, particularly YouTube Music and Premium, and Google One, which was driven by demand for AI plans. Google Services operating income increased 20% to $39.5 billion, and operating margin was 41.8%. The Google Cloud segment delivered outstanding results in the second quarter, driven by our enterprise AI products and services.

Cloud revenues were up 82% to $24.8 billion, driven primarily by GCP, which grew faster than cloud overall. Core GCP, AI solutions, and AI infrastructure were all important drivers of growth. We also began to recognize revenues from TPU system sales, which we delivered to customer data centers for the first time in Q2. Cloud revenue growth accelerated meaningfully even after excluding the impact of TPU system sales. Cloud operating income was $8.8 billion, more than tripling year-over-year, and operating margin increased from 20.7% in the second quarter last year to 35.6%. Google Cloud's backlog increased by more than $50 billion sequentially, reaching $514 billion in the second quarter. The increase was driven by strong demand for our enterprise AI offerings.

The majority of the backlog is related to typical GCP contracts from a broad mix of customers, and we expect to recognize just over 50% of the total backlog as revenue over the next 24 months. In other bets, revenues were $382 million, and operating loss was $1.8 billion, as we continue to expand Waymo's business and invest in key other bets. In Alphabet-level activities, the operating loss was $5.8 billion, driven by shared AI R&D expenses. Turning to our outlook and business performance expectations in the second half of 2026. First, in terms of revenues, at the current spot rates, we would expect a slight FX headwind to our consolidated revenue in Q3 compared to a one percentage point FX tailwind in Q2. This impact will be seen primarily in Search and YouTube ads.

In Google Services, as Philipp mentioned, we continue to benefit from innovation in Search by improving the user and advertiser experience with AI. At the same time, in Q3, we will begin lapping an acceleration in Search performance that began in the third quarter last year. In Google Cloud, we are seeing significant demand for products and services, which we expect to drive strong growth. As I mentioned earlier, we started delivering TPU system to customer data centers in the second quarter. We continue to expect to recognize a relatively small portion of the revenues from our existing TPU system sales agreements this year, ramping as we exit 2026. We anticipate the vast majority of the revenues from these agreements will be realized in 2027.

Given the supply-constrained environment, we plan to expand the use of third-party capacity in Q3 as a bridging strategy while we build out more internal capacity. This strategy allows us to keep growing our customer base and capture greater overall value. However, it will create modest margin pressure in the near term as we utilize this capacity. Moving to investments, we are updating our full-year 2026 CapEx guidance range to $195 billion-$205 billion, up from our previous estimate of $180 billion-$190 billion. The increase in the range is primarily due to an acceleration in the delivery of capacity to meet growing demand. As we previously shared, we continue to expect our CapEx to increase significantly in 2027 and will provide more details at a later date.

In terms of expenses, the significant increase in our investments in 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 we are investing in marketing to support our AI products. Finally, we expect the free cash flow will remain under pressure, driven by our investments in technical infrastructure, which enables us to capitalize on the AI opportunity and continue to drive attractive returns. Q2 represented another strong quarter. Our teams continue to deliver impressive innovation, executing with discipline and velocity. I want to take this opportunity to thank our employees for their contribution to our performance. Sundar, Philipp, and I will now take your questions.

Thank you. As a reminder, to ask a question, you will need to press star one on your telephone. To prevent any background noise, we ask that you please mute your line once your question has been stated. Our first question comes from Brian Nowak with Morgan Stanley. Your line is now open.

Thanks for taking my questions. I have two, one for Sundar, one for Anat. Sundar, with more time and GenAI products and tools in the market and investment continuing to step up. Can you just give us some perspective on how your view on the size of the overall GenAI ROIC opportunity and the timing of the ROIC has changed now versus one year ago? Then, Anat, you talked quite a bit about supply capacity constraints. Maybe a similar question for you around forward CapEx. How is your budgeting philosophy and just constraints you're putting onto forward spend? How are those changing as you think about the right amount to spend in 2027 to close this capacity constraint?

Look, thanks, Brian. It's a good question. I do think, it feels like we are in very early innings of what feels like secular shift across multiple areas. In our core information businesses, just the possibilities when I see what all you can do with the absolute frontier capabilities, there's still a lot of work ahead to translate all that into experiences for our consumer users. You can think about end-to-end agentic experiences to really meaningfully do a lot more for them. All of that looks like extraordinary opportunities with extraordinary returns for executing well on those opportunities. Similarly, on the enterprise side, as you can see from our demand, which is reflected in our growth rates, et cetera. Again, in my conversations with many CEOs, many companies, they're all still barely scratching the early stages of what's possible here.

I think, we used to talk about cloud itself, very small percentage of overall workloads and enterprises have shifted to cloud. Think about what percentage of workloads are really AI native and AI enabled. It again feels very early. I would say, from a ROIC standpoint, I think, we are taking a full stack approach. We are seeing momentum across consumers and enterprises and developers and so on. It feels like if anything, over the past year, we've gotten more bullish on the opportunities ahead. I'll turn it over to Anat.

Thanks for the question on how do we think about forward-looking CapEx in the context of supply constraints. We're still in a supply constraint environment. I think we've said this now for multiple quarters in a row, we are seeing very strong demand, both from external cloud customers as well as across the business. Our goal is to invest as long as we see an attractive return on that investment, as Sundar mentioned earlier. We do take a long-term view, so we take multi-year view at what the needs are, as well as focus on next year and the near term and building aggressively to meet those demands. As you've seen, while we have increased our capacity quite significantly over the past three years, the demand still outpaces that investment. We are, just like the rest of the industry, working in a supply-constrained environment.

We're working hard to do this. We do have a benefit of having the full stack approach, so we're able to drive operational efficiencies, technological efficiencies within our technical infrastructure organization so that we can deliver more compute. As long as we see these attractive opportunity to invest, we will continue to invest.

Thank you both. Our next question comes from Doug Anmuth with J.P.

Morgan. Your line is now open.

Thanks for taking the questions. One for Sundar and one for Anat. Sundar, can you just talk about your confidence level that the Gemini models can remain at the frontier? I know you had the Gemini, the Flash model releases this week. Google perhaps doesn't make maybe quite as much noise as some of the other leading labs or perhaps have quite the frequency. Just curious how you'd address any concerns about that ability to continue developing leading models. Then just related, can you talk about your plans for coding and how you look to close the gap in that part of enterprise? Then Anat, just following the recent equity and debt raises, can you just help us understand how you think about optimal capital structure and how you view the cost of debt versus equity? Thanks. Thanks, Doug. The frontier is incredibly dynamic space, and it's fiercely moving forward.

At any given moment when you take a snapshot, it feels dynamic. We've had clearly frontier models. There are many attributes on which we are still at the frontier. There are areas where we've acknowledged we need to improve. Coding and agentic coding is an example of that, and the teams are very focused on it. With 3.6 Flash, and by the way, Flash is our workhorse model, and we see tremendous demand for it, given it generally hits a sweet spot of performance, cost, reliability, latency, et cetera. We've incorporated Gemini and Flash, particularly in our entire portfolio of solutions, be it in cybersecurity, data analytics.

If you think about an area like customer service, you need really good voice quality, you need live streaming, you need the ability to reason on that. If you're a professional services firm, you need high-quality summarization, content generation, et cetera. Flash does very well on all of that. In terms of agentic coding, we are iterating, and you will see us make continued iterations. 3.6 Flash, for example, compared to 3.5 Flash, jumped over 10 points in DeepSuite as a benchmark, and it is more token efficient doing so. We are using it internally. We are testing it with many customers in coding. We see the progress just in six weeks from the prior version to the new version, and you will see more continued iterations on that as well.

In terms of the frontier, we are both very committed and very confident of being at the frontier. For the next generation of frontier, you're going to need much larger base models. We are now training Gemini 4, and we're being very ambitious with it. I am very excited by the progress I'm seeing internally on Gemini 4, and I'm confident that people will be pleased when we are putting it outside. We will need Gemini 4 as a larger base model to compete at that frontier level, so we are focused on executing on that well.

On the question regarding our capital structure and recent equity and debt raise. As we think about our investment needs, as I said, we look at the next year and multiple years out, we first look at how much we can support based on cash from operations. As you've seen in our results today, we continue to generate very healthy, strong cash flow from operations. That's our first source of funding. Then we look at debt, and most recently we did the equity raise. We have expanded our debt portfolio quite significantly over the past 12 months. If you've seen a year ago, we were at about $16 billion, and we went to about $100 billion across multiple currencies and geographies, so we're expanding that portfolio.

We also want to make sure we have a resilient, not just growth outlook, but also a resilient balance sheet and a strong balance sheet, healthy balance sheet, which is the rationale behind expanding into the equity markets. At this point, we're not planning to go back to the equity markets, with the exception of, as you recall, part of our equity offering was the ATM or at the market offering that we will do to address the stock-based comp or the tax on SBC, which we'll do for some period of time. We look at those three dimensions, the cash flow from operations, debt levels, and equity, and a way to balance it in a way that ensures that we continue to maintain a healthy balance sheet.

Thank you both. Our next question comes from Eric Sheridan with Goldman Sachs.

Your line is now open.

Thanks so much for taking the questions. Maybe two, if I could, both on TPUs. Sundar, can you talk about some of your key learnings as you scale your TPU efforts in terms of both the demand for TPUs and how you think about balancing the external demands for TPUs versus the internal demand for custom silicon inside the organization as you look over the next couple of years? Ruth, if I could just follow up, you made some comments in your prepared remarks about the impact of TPUs on Google Cloud. I didn't know if you could give us a little bit more granularity about the size of TPUs as a part of the revenue backlog and how to think about the revenue recognition or the potential for margin impact from TPUs in the years ahead. Thanks so much. Okay. I think in terms of, first of all, we are very pleased with our TPU roadmap progress, and the value in terms of performance, and the edge it gives, and we obviously use it extensively.

In terms of allocating our TPUs, look, our first priority is making sure we are allocating what we need to compete at the frontier in terms of AGI development. That is the foundation for everything we do. Given the extraordinary demand to balance the external demand, even for most cloud customers, we are using both TPUs and GPUs mainly for serving our models. Think Vertex AI, Gemini Enterprise, the momentum we see. We're using it or agentic workloads, et cetera. We are using it for those purposes.

To the extent people want it as infrastructure, we are balancing it by increasingly looking at opportunities to put TPUs in their data centers or in other data centers, like the project we are doing with Blackstone, et cetera. We are using that as an ability to balance and make sure we are allocating as much of the available compute for frontier model development, as well as serving both our consumer business and our enterprise business in terms of first-party models.

In terms of revenue recognition and how we look at the TPU system sales. The way to think about it is the following. When we sign the agreements that I've mentioned in the prepared remarks, they would be then reflected in the cloud backlog. The vast majority of the $514 billion of cloud backlog is the GCP agreements, but the TPU system sales are reflected in that backlog. We start building inventory to be able to sell those systems. You see that impact on the cash from operations because we built ahead, obviously, as we're building that business and ramping up. Once we start delivering the sales, generally that's when we start recognizing revenue. This quarter was a small amount of that total agreement.

We'll continue to ramp up throughout 2026, you'll see the vast majority of the revenue from that agreement come through in 2027.

Your next question comes from Ross Sandler with Barclays. Your line is now open.

Yeah. Just back to the AI model kind of war that's going on, Sundar. Just wanted to ask about the speed of model releases, and how you can potentially speed up the cadence by which Gemini is releasing models. We all saw the third-party compute deal with SpaceX. What else are we doing to kind of speed up the pace of model releases compared to some of the other folks out there? You just mentioned the Flash models, which have been very successful, to your point. Do you view that as the right end of the market to be in, given how crowded the lower cost end of the model space has become? Just any thoughts on how you see all that playing out.

Thanks, Ross. Look, two things I'll say. First of all, we really think about the parade of frontier. We want to make sure for our customers we are offering best models at various price points, right? You will see us. It's very important to us to have the best frontier models out there, as well as models which are very performant and low cost. This is why we have Flash-Lite, Flash Pro, et cetera. We are committed to being at the full parade of frontier. On the speed of model releases, I do think you will see us continue to pick up pace. Obviously, we announced Gemini 3.5 Flash at Google I/O. We have followed that up with Gemini 3.6 Flash, and you'll see continued iterations of that model, with further progress in agent decoding, et cetera. We are really focused, putting a lot of effort into Gemini 4.

It's a very ambitious effort. We want to compete at the frontier level of where the frontier will be when Gemini 4 comes out, we are applying a lot of our compute and effort in that direction. With that, we are creating a baseline on top of which you will see us rapidly iterate with subsequent model releases. Picking up pace and releasing models almost at a monthly cadence is part of our roadmap as we are building Gemini 4 as well.

Your next question comes from Michael Nathanson with MoffettNathanson. Your line is now open.

Thanks. Thank you. One for Sundar and one for Nat. Sundar, just keeping with the model theme of this call, can you talk a bit about what you think the moats are to this new model war, right? What is your strategic advantages that fuel your business, that even if everyone gets to the same type of model capabilities, what gives you the edge to keep growing like you're doing? Then, Nat, back to Eric's question, anything you can tell about the margin impact on TPUs going forward, right? Is it incremental margin to the core cloud margin, or is it a lower margin coming through? Thanks. Michael, first of all, there are many layers at which we are providing solutions, right?

I think part of what the value of our full stack approach is, customers are coming to us for solutions. If you take an area like cybersecurity or data analytics, people are deploying solutions in which models are an ingredient in that solution, right? Take cyber, people are using Chronicle and Wiz and with our upcoming CodeMender product, they're using it to detect and patch vulnerabilities and so on. Take data analytics. People are bringing what's been in the past siloed data sources, putting it all together, and having an intelligence layer on top of it with Gemini Enterprise. The model is just an ingredient in those solutions. I think it's important to remember that.

Even within where you're purely on a more model consumption area, what looks as models are increasingly becoming end-to-end orchestrated systems, right? Workflows, agentic workflows. To develop all this, it's your ability not just to bring the compute you need to train and serve the data quality, the environments you have, your ability to continually improve, provide customers with that peace of mind that all the data they have, their data, their trajectories, are confidential to them. None of that in any way flows back to the models. Their ability to configure and serve all this in a secure way and manage it and provision it and so on. These are big end-to-end things, this is what our cloud business as a whole is focused on building it. We are seeing demand across all of these components.

Obviously, having our own models allows us to really optimize these solutions and bring an integrated offering. We will also provide other models as part of these solutions. We also bring infrastructure as part of these solutions, et cetera, and take a whole full stack approach. I think we are very well positioned there.

On the TPU margins, we don't break out margins for any specific products or infrastructure component. Certainly, there are benefits from designing and manufacturing our own chips. The way to think about it is this is an expansion of our total addressable market, so it expands the opportunities by providing solutions to customers that need those systems in their data centers. Overall, if you think about the Cloud margins, obviously a really fantastic expansion of margin to 35.6% this quarter. Outstanding strong operational discipline across the business and leveraging growth in the top line.

As you think about Q3 and through the remainder of the year, I've mentioned some of it in the prepared remarks, given the supply-constrained environment we're in, we are planning to expand the use of third-party capacity in Q3 as a bridging strategy while we continue to build out internal capacity. That capacity, given the cost of that capacity, will put some pressure on operating margins for Cloud. The last item we mentioned in the past was the integration of Wiz. Does create some headwind here in the near term in 2026 related to the acquisition.

Thanks, guys. Your next question comes from Mark Shmulik with Bernstein.

Your line is now open.

Yes, thanks for taking the questions. Anat, just on these third-party deals and kind of the bridge in capacity, is there a particular objective where the constraints are most severe, or is it really broad-based? I guess, stepping back a bit and thinking about capacity allocation across the businesses, has that changed at all, or is there a way to contextualize how you're now thinking about the trade-off between allocating compute to Search versus model training versus for the GCP business? Thank you. Mark, I can comment on it.

Look, again, on allocation, I think the baseline with which we start is what it takes to continue AGI development at the frontier. Obviously, the priors on that are just based on where the model frontier moves. We start with that as a baseline. Beyond that, we are prioritizing our core product areas like Search, YouTube, et cetera, as well as Cloud. Within Cloud, we are prioritizing the compute to make sure we can serve our models in the context of Vertex and Gemini Enterprise, and our core solutions, be it data analytics and cybersecurity, et cetera. Right? Our core serving for our core products across consumers and enterprises is where the compute is primarily going, and that's how we think about it.

I think on the bridge deal, the main thing I would say is, look, on the margin, there are very, very large customers of ours on Cloud who we are trying to support them through this extraordinary moment. The incremental opportunities they are bringing to us, while a short-term cost over a few months may be very high, in the lifetime of the deal, as we bring more capacity on, is highly ROI positive. Right? Those are factors we are taking into account. Are you willing to take upfront six-month deal to be able to serve that customer in what is a multi-year opportunity, where the margins and the returns are very, very attractive over that multi-year horizon? Hopefully, that gives some color on how we thought about those opportunities.

Your next question comes from Ron Josey with Citi. Your line is now open.

Great. Thanks for taking the question. Maybe I'll switch topics somewhat and, Philipp, ask you a little bit more about monetization from a Search and YouTube perspective. Just given the greater signal we have with AI searches, then you talked about YouTube strength, talk to us a little bit more on how advertisers are leveraging the greater personalization and targeting that Google has to drive this ROAS. A question we often get is, Google is that size and scale, we're still growing 17%. Any reasons what's driving that all-time high on searches? Thank you. Yes, thank you so much for the question.

Look, our 17% year-over-year growth rate in the Q2 Search and other revenues was really driven by many parts of our business working well together and very, very deep Gemini integration. Maybe to zoom out for a second, all the major verticals contributed to the growth. Retail drove the greatest contribution, not managed, followed by really meaningful contributions from finance, tech, media, entertainment, and so on. I think it's really important to understand that Gemini supercharges our ability, and this goes specifically to your question, to understand what people are looking for and match the right ads. We're applying Gemini models really across our entire ads infrastructure, whether it's ads quality, advertising tools, ads in new AI experiences. We're really deeply integrating Gemini into the customer tools to make the campaigns more efficient, which comes on top of this.

We have our AI-powered campaigns like AI Max that help advertisers actually adapt and find the opportunities beyond keyword. Again, that's an ability for us to go deeper and target better. AI Max continues to unlock, we mentioned this, billions of net new searches that weren't really monetizable before. On the YouTube side, high level, the ads growth was driven by direct response and brand advertising. I shared earlier, we continue to see a lot of fermenting in the living room. We have a really exciting ads roadmap as well ahead of us on the brand side, on the direct response side. Demand Gen and YouTube Shorts remain really interesting opportunities here. Again, this has targeting components to it, obviously.

We continue to innovate really heavily in direct response with shoppable ad formats in the living room, which will help us drive strength in retail as well.

Your next question comes from Ken Gawrelski with Wells Fargo. Your line is now open.

Thank you very much. Two questions, please. First, how would you assess the forecasted returns on compute capacity investments in 2027 compared to prior years, 2025 and 2026, in light of the supply chain constraints and supply chain inflation we're seeing? I'm curious as to how you think about the return profile of 2027 and kind of future investments versus past investments in capacity. The second one, a little different topic here. When you think about Waymo, what are the key factors you would consider when evaluating a change in corporate structure for Waymo? I know you've previously been reticent to talk about this, but the business is scaling. Clearly, there's leadership there and has a lot of momentum. Under what conditions would it make sense for Waymo to live outside of Alphabet? Thank you. Look, Ken, on your first question, if I understand it, we are working off a discipline ROIC framework here.

Obviously, to the extent that our input cost is going up to us, we reflect that in our ability to price our solutions and see returns there. All of that is factored into how we are planning. I think our compute capacity investments in 2027, to the first question I answered, I think we are seeing strong demand indicators, including long-term deals, the existing deals which we have, which are renewing with exceptional demand on a moving forward basis. We are using all that to plan and invest accordingly. I think if anything, the dynamics look healthier than where we were about a year ago, that's what gives us the confidence to undertake those investments.

On Waymo, look, I think we are really focused on executing and scaling up Waymo. We have set it up with our bet structure and given the team a lot of support. Alphabet has continued, I think, our ability to think and plan long term, and invest in the business, and give them that long-term roadmap. The confidence in undertaking a long-term roadmap and scaling up, I think is all hugely valuable. We're really focused on scaling the business right now and executing to that extraordinary potential, and that's what we're focused on.

Thank you very much. Our last question comes from Sridar Kajuria with Riff Research.

Your line is now open.

Okay. Thanks a lot for taking my questions. Could I please ask you two? One is on TPU long-term strategy. Longer term, is it fair to think that as TPU sales scale, you'd build merchant silicon business with a software stack that goes with it? Second is on YouTube revenue. Given how strong engagement is, what are some of the factors that could drive accelerating growth rate at YouTube, on a go-forward basis? Thank you. Maybe I'll answer the first one.

Philipp can broadly talk about YouTube revenue growth as well. On the first one, on TPUs, look, I think we've been operating with TPUs for a while. A lot of our cloud serving is done on TPUs, and we are also seeing strong demand for TPUs as standalone systems from other customers. Obviously the industry has constraints, too. We have to plan, and we allocate on a forward-looking basis along the principles I spoke about earlier. I don't want to project out too far into the future there, but I do think obviously we will scale up based on the opportunities we see and the demand we see, commensurate with the constraints that exist and the allocation needs we have for frontier model development, making sure we can serve our consumer businesses and enterprise businesses well.

Philipp, you want to add on YouTube monetization?

Yes. Thank you so much. Look, I mentioned it, the drivers of YouTube ads revenue growth. I think there's a lot of things we're actually excited about when we look at our ads roadmap here. In brand, we see ongoing opportunities on CTVs in the living room. We're building tools to help advertisers find creators, scale across screens, and then measure the results. We have a slate of new and returning creator shows that are coming exclusively to YouTube. We see opportunities in direct response, particularly with Demand Gen. Demand Gen and Shorts, I mentioned, remain a really interesting opportunity here to expand our base to more small and medium advertisers across more verticals, shorter videos. Actually, this important one create more opportunities for less disruptive ads, increasing the overall ad effectiveness.

We're going to continue to see a lot of innovation, in my opinion, in direct response with shoppable ad formats in the living room, which again, we mentioned, that drives retail strength. We announced a few other formats here at Brandcast. We announced Buy with Google Pay to enable CTV viewers to actually complete purchases directly on their TV with two clicks, which is a really interesting opportunity over time. We launched the Affiliate Partnership Boost to drive incremental sales, and the creator earnings, obviously, from YouTube Shopping affiliate commissions. Overall, frankly, very exciting times.

Thanks, Sundar. Thanks, Philipp. Thank you.

That concludes our question-and-answer session for today. I'd like to turn 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 third 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.