GOOG Q2 result-top 10 holding--AI acceleration

 GOOGL Q2 RESULT

My thoughts

To cut to the chase, the most important conclusion to come to regarding GOOG is whether the massive capex will deliver attractive returns. The most recent result showed some promising signs, but the comment that capex will again significantly increase into 2027 will push out any hard conclusions. Traditionally, the market has priced stocks higher when we can see a peak in the capex cycle, and that may be the case here, even if the returns are attractive.

The Q2 results were strong, with revenues up an astonishing 24%, with the highlights being a huge acceleration in GCP (AI infrastructure and cloud) revenues of +82% and margins much higher. Of course, this is where the bulk of capex is going, so it is reassuring to see strength here. Search is also accelerating, which can be traced to Gemini’s integration with search, and it appears that GOOG has found the way to monetise AI-initiated queries. YT was solid and is integrating with Gemini as well. The success of these businesses using AI is a bull point for further diffusion and adoption by the broader economy.

Margins were higher, which has been a concern as higher depreciation and spend on foundation models occur. My thinking here is that we see the costs before all the benefits, so margin improvement is a great outcome. GOOG did flag that it will be cycling stronger comps, especially in search, for the rest of the year. Management also stated that they are procuring expensive compute over the quarter of two from third parties as their compute comes on. Client demand is strong, and they would rather take the margin hit ST than risk alienating the clients who promise large long-term profitability.

The backlog continues to climb, and that will have to be watched (graph below). The increases in capex have brought some concern about GOOG going FCF negative over the period, and likely to continue for a while yet. IMO this concern is misplaced; the concern should be whether the capex generates attractive returns. If it does, GOOG should invest as much as is prudently possible. As for prudence, the capex still leaves GOOG net cash of $144B, so no concerns on balance sheet stability at this stage. Signs of + ROI are increased customer commitments, increased token usage, increased product adoption and increased infrastructure demand. There is a criticism that GOOG is spending into a non-returning black hole that we can see no return on, that flies in the face of certainly the management narrative and the numbers, although these are nascent. The other supportive comment is that the demand is broad-based. The positive outcome of AI being used internally in GOOG (as well as Meta), indicates that there are efficiencies for the broader economy to come. To be clear, the thesis here is that GOOG is building into excess demand, not a “build and they will come” strategy; the numbers obscure the successful returns on the vintage capex by continual huge increases in capex. My view holds until this thesis is proved wrong. AI ROI remains the key.

The cloud numbers are quite astonishing and are so great that we are witnessing GOOG's business mix changing from basically all advertising to advertising and AI infrastructure. That mix change IMO is positive and should be reflected in the rating at some stage. The cloud numbers also included the dilutive acquisition of Wiz.

GOOG announced the selling of TPU’s as a business. Of course, GOOG needs these itself but is selling into clients' private cloud, as an alternative to NVDA chips. The amounts are small but could accelerate into 2027 and beyond. GOOG chip capacity is not that far behind NVDA.

MTM gains were made on Anthropic and SpaceX of about $98B. Although large in absolute terms, these holdings are worth about $12/GOOG share for Anthropic and $8/share for SpaceX, so nice to have but not huge in the GOOG world.

Part of the thesis is that GOOG can win in this very competitive game due to being a fully integrated player. GOOG also has enormous established scale for distribution. That means owning the chips, the DC, the models and the orchestration/harnessing layers that can be efficiently integrated compared to others who own part of the chain. That leads to scale advantages, distribution strength, product integration and cost efficiency. GOOG announced a series of models that focused on the fast and cheap part of the market. That makes complete sense to me. GOOG is also a player in frontier models, with Anthropic and OpenAI and expressed confidence in matching these players. Whether GOOG has to be the leader in this race is open to debate. A fast follower is an attractive proposition for someone with scale distribution. The negatives are whether market share gains are sticky for the first to market or not; that is unclear at this stage. IMO GOOG needs to keep up but not necessarily lead. GOOG admits to lagging Anthropic et al in coding and is making strides to close this gap. Gains in enterprise AI customers still appear to be happening. Management suggested that AAI penetration into the client base workflows is still minute, with a huge runway ahead.

Search continues to show that monetisation from longer queries is being achieved. Gemini integration has led to better ad quality, better ad tools and better AI user experience. Monetisation is developing alongside the product, which was a huge concern not that long ago.

VALUATION and PORTFOLIO SIZING

GOOG is currently my third largest holding. The reported numbers are better than my estimates, so I'm upgrading my estimates. Cloud/AI and search are the main contributors. My base case assumptions, based on attractive AI ROI, are than eps expands at 16% CAGR for 5 years and we exit at a 22x PE. At $318, that generates a 10% return, so attractive. If we assume a market multiple 20X exit multiple, a 10% return is generated at $280. That looks like the SP to add, given I have a large holding. Profit-adjusted cost price is $69.

GOOG remains a large holding while the thesis remains intact. I may trade around the edges, but I would like to see the fruits of all this capex appear and we have a good idea of the size (or not) of those profits.

Q2 Transcript summary

We saw 17% revenue growth in Search and Other and YouTube ads grew 13%. Cloud revenue grew 82% powered by strong demand for AI infrastructure and AI solutions and Cloud backlog grew to $514 billion.

We are seeing tons of demand for our workhorse Gemini Flash series because it hits the sweet spot of performance and cost….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.

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.

And we are continuing to incorporate more frontier capabilities into search with agents, personal intelligence and notebooks.

And 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.

Next, the Gemini app, which now has 950 million monthly active users with daily active users tripling in the last year.

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.

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. Our product differentiation is driving expansion in 3 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 7x 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.

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 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 deliver strong price performance.

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.

We continue to accelerate the deployment of Gemini across our entire ads infrastructure to boost performance in 3 areas mentioned before: ads quality, advertiser tools and AI user experiences.

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 has become the core building block for advertisers to fully participate in our new AI experiences. It's out of beta and 0.5 million advertisers have already adopted it. Those who adopt our AI-powered campaigns like AI Max or PMax see an average of 15% more conversions or value on search at a similar ROAS.

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.

In collaboration with the retail industry, we established the open-source universal commerce protocol, UCP, as a new standard for agentic commerce. Merchants are rapidly adopting UCP

This unique convergence of brand equity and commercial action makes YouTube a powerful full-funnel platform.

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 continue 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.

Consolidated revenues were $119.8 billion, up 24% or 23% in constant currency. Total cost of revenues was $45.9 billion, up 18%. TAC 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.

Operating income increased 30% to $40.8 billion, and operating margin was 34%. Other income and expenses were $98 billion, representing a substantial increase from the prior year, primarily due to unrealised gains in our equity securities portfolio.

CapEx was $44.9 billion in the second quarter, with the vast majority of the spend in technical infrastructure to support our investments in AI. We had negative free cash flow of $5.9 billion in the second quarter driven by our investments in CapEx.

Google Services revenues increased 15%...Google Search and other advertising revenues increased by 17% ….YouTube advertising revenues increased 13%. Subscription, Platforms and Devices revenues increased 15%

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 recognising revenue from TPU system sales, which we delivered to customer data centres 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 for a broad mix of customers, and we expect to recognise just over 50% of the total backlog as revenue over the next 24 months.

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're seeing significant demand for products and services which we expect to drive strong growth.

We continue to expect to recognise 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.

And given the supply-constrained environment, we plan to expand the use of third-party capacity in Q3 as a bridging strategy while we build up 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 utilise this capacity.

We are updating our full year 2026 CapEx guidance range to $195 billion to $205 billion, up from our previous estimate of $180 billion to $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 we'll provide more details at a later date.

QUESTION and ANSWER SESSION

I do think it feels like we are in very early innings of what feels like a 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.

So 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. …Now think about what percentage of workloads are really AI-native and AI-enabled. It again, feels like very, very early.

And we are seeing very strong demand, both from external cloud customers as well as across the business. And our goal is to invest as long as we see an attractive return on that investment…

And as you've seen, while we have increased our capacity quite significantly over the past 3 years, the demand still outpaces that investment.

We do have the benefit of having the full stack approach. So we're able to drive operational efficiencies, technological efficiencies within our technical infrastructure organisation so that we can deliver more compute, but as long as we see these attractive opportunities to invest, we will continue to invest.

 

Re LLM-There are many attributes on which we are still at the frontier. There are areas where we have acknowledged we need to improve coding, and agentic coding is an example of that, and I think the teams are very, very focused on it, with 3.6 Flash.

In terms of the frontier, we are both very committed and very confident of being at the frontier.

We want to make sure for our customers we are offering best models at various price points, right? So you will see us. But 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. And with -- so we are committed to being at the full Pareto frontier. On the speed of model releases, I do think you will see us continue to pick up pace.

We are really focused, putting a lot of effort into Gemini 4. It's a very ambitious effort. We wanted to compete at the frontier level of where the frontier will be when Gemini 4 comes out.

Then even within where you're purely on a more model consumption area, people are -- there is what looks as models are increasingly becoming end-to-end orchestrated systems, right, workflows, agentic workflows and 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.

 

I think on the Bridge deal, the main thing I would say is, look, there are, on the margin, very, very large customers of ours on cloud, who we are trying to support them through this extraordinary moment. And 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? So those are factors we are taking into account. So are you willing to take upfront 6-month deal to be able to serve that customer in what is a multiyear opportunity where the margins and the returns are very, very attractive over that multiyear horizon.

 

AI Max continues to unlock we mentioned as billions of net new searches that weren't really monetizable before.