Google's Q3 revenue hit $127.6 billion, AI spending is even more aggressive, and cash flow is flashing red

Original author: Li Hailun

Original editor: Xu Qingyang

Original source: Tencent Tech

On October 28, US local time, Google's parent company Alphabet released its financial results for the third quarter of fiscal year 2026, ended September 30.

Although revenue continued to grow, Alphabet's third-quarter revenue, adjusted earnings per share, and free cash flow all fell short of Wall Street expectations, and future capital expenditures will increase further, causing the company's stock price to fall 9.79% to $293.09 in after-hours trading.

The earnings report showed that Alphabet's third-quarter revenue reached $127.577 billion, up 25% from $102.346 billion in the same period last year. Although Alphabet's revenue grew 25% year over year, marking its 13th consecutive quarter of double-digit growth, actual third-quarter revenue of $127.577 billion still fell short of Wall Street analysts' expectations of $128.22 billion.

Operating income reached $40.576 billion, up 30% year over year; the operating margin was 32%, up from 31% in the same period last year.

In terms of net income, although Alphabet's third-quarter revenue grew 25% year over year, net income attributable to common shareholders fell 25% year over year, from $34.979 billion in the same period last year to $26.170 billion.

The main reason was that changes in the fair value of equity securities turned other gains and losses from a gain of $12.759 billion in the same period last year to a loss of $8.221 billion, of which net losses from changes in the fair value of equity securities amounted to $8.664 billion. Diluted earnings per share were $2.12, below $2.87 in the same period last year; on a basis excluding the impact of equity securities losses, earnings per share were $2.67, below Wall Street analysts' expectations of $3.02.

In terms of cash flow, Alphabet's third-quarter free cash flow was negative $9.065 billion, compared with positive $24.461 billion in the same period last year, a decrease of $33.526 billion year over year. Capital expenditures during the same period reached $51.355 billion, an increase of about 114% from $23.953 billion as of the end of 2025.

The company maintained its full-year 2026 capital expenditure guidance of $195 billion to $205 billion and expects capital expenditures to increase significantly in 2027.

Alphabet CEO Sundar Pichai said in the earnings report that AI investment is driving growth in the search business, with search query volumes, including commercial queries, growing at the fastest year-over-year rate in the past five years. Google Cloud revenue grew 103% year over year, first-party model APIs process nearly 32 billion tokens per minute, more than four times the level a year earlier. On the consumer product side, the Gemini App reached 1 billion users, making it the fastest-growing product in Google's history; global subscriptions for YouTube Music and Premium also surpassed 150 million.

Capital Expenditures Continue to Grow

As of September 30, 2026, Alphabet's total assets reached $1,003.312 billion, surpassing $1 trillion, a substantial increase from $595.281 billion at the end of 2025. Among these, net fixed assets reached $372.827 billion, up from $246.597 billion at the end of 2025; marketable securities reached $208.764 billion; cash, cash equivalents, and marketable securities totaled $265.098 billion.

In the third quarter, Alphabet's capital expenditures expanded further to $51.355 billion, an increase of about 114% from $23.953 billion in the same period last year, mainly reflecting the company's continued investment in AI computing power and related infrastructure, as well as inventory build-up needed to expand TPU system sales, which also put pressure on cash flow. At the same time, although the company's revenue continued to grow, the sharp increase in capital expenditures still put pressure on cash flow, pushing free cash flow from positive $24.551 billion in the same period last year to negative $9.065 billion, below analysts' expectations of negative $2.7 billion.

On the debt side, Alphabet's long-term debt rose to $125.102 billion, a significant increase from $46.547 billion as of the end of 2025. The company maintained its full-year 2026 capital expenditure guidance of $195 billion to $205 billion and expects capital expenditures to grow further significantly in 2027. As investment in AI infrastructure continues to expand, the company's financing needs and debt scale have also risen accordingly.

One figure in Alphabet's earnings report was particularly noteworthy: unallocated costs at the Alphabet level reached as high as $7.655 billion (compared with $4.467 billion in the same period last year). This expense mainly involves group-shared AI R&D activities, including personnel compensation and technical infrastructure usage costs required for general AI model development, as well as some group management expenses. As AI R&D continues to advance, related costs at the Alphabet group level are also increasing.

AI infrastructure investment and its impact on cash flow have become a common topic in tech giants' earnings reports. On October 21, local time, Meta released its third-quarter 2026 earnings report. The company's advertising business continued to grow, but AI infrastructure investment continued to expand, and capital expenditures climbed further.

In the third quarter, Meta's capital expenditures were $33.942 billion, or $34.906 billion including finance leases; operating cash flow during the same period was $32.786 billion, and free cash flow turned negative at $2.12 billion. The company also raised the upper end of its full-year capital expenditure guidance to $145 billion. After the earnings report was released, Meta's stock price fell nearly 7% on the following trading day.

Oracle sent a different signal. On October 28, local time, the company announced capital expenditure and financing arrangements for the coming years at its investor day, expecting capital expenditures to peak in the next few years, no external financing exceeding $20 billion before fiscal year 2030, and free cash flow to turn positive in the second half of fiscal year 2028. After the news was announced, Oracle's stock price rose more than 12%.

While Meta and Alphabet continue to increase their bets on AI infrastructure, Oracle expects capital expenditures to peak in the coming years and plans to control the scale of external financing. Tech giants' investment strategies for AI infrastructure are beginning to show differences, and the market's focus is gradually shifting to return on investment: whether continued expansion of computing power investment can bring corresponding business growth, and whether companies can maintain healthy cash flow during expansion.

Computing Power Money Printer Erupts Across the Board

In the third quarter, Google Cloud revenue reached $30.709 billion, compared with $15.157 billion in the same period last year, a sharp year-over-year increase of 103%, significantly exceeding analysts' generally expected $28.7 billion. Profitability also improved in tandem, with segment operating income rising sharply from $3.59 billion in the same period last year to $11.121 billion, and the operating margin rising to about 36.2%.

Enterprise demand for AI infrastructure and solutions is the core driver of Google Cloud's business explosion.

As more and more enterprises deploy AI models into actual business operations, demand for computing power, cloud platforms, and model services continues to increase. Alphabet said that TPU system sales also made an important contribution to Google Cloud's revenue growth, reflecting that enterprise customers' demand for AI computing infrastructure is accelerating into actual orders and revenue.

Usage of model services is also growing rapidly. Alphabet disclosed that Google's self-developed flagship model series APIs process nearly 32 billion tokens per minute, more than four times the processing volume a year earlier and up about 40% from the previous quarter.

Google Cloud's revenue doubling and the sharp increase in operating income show that Alphabet's massive investment in AI has begun to translate into considerable revenue and profit through its cloud business. Compared with the cash flow pressure brought by rising capital expenditures, the rapid growth of the cloud business also provides the company with an important window to observe the return on AI investment (ROI).

However, as subsequent infrastructure investment continues to expand, whether Google Cloud can maintain its current growth rate and whether profit growth can continue to cover higher computing power construction costs remain focal points for the market.

Core Advertising and Search Grow Steadily

As Google's traditional core cash cow, the Google Services segment demonstrated strong resilience in the third quarter, generating revenue of $96.302 billion (compared with $87.052 billion in the same period last year) and operating income of $39.157 billion (compared with $33.527 billion in the same period last year).

Among these, "Google Search & Other" revenue reached $63.350 billion, up 12% year over year, but below analysts' expectations of $64.96 billion. There had long been concerns that generative AI would divert traffic from traditional search engines, but as Pichai emphasized: AI investment has not weakened search; instead, it has driven year-over-year search query volume (including commercial queries) to the highest growth rate in the past five years.

At the same time, YouTube advertising revenue reached $11.207 billion, up 9.2% year over year; Google Network advertising revenue was $7.455 billion.

In the consumer AI ecosystem, active users of the flagship AI application Gemini App officially surpassed the 1 billion mark, making it the fastest-growing consumer product in Google's history. At the same time, global subscriptions for YouTube Music and Premium also surpassed 150 million.

In addition, the Other Bets segment generated revenue of $372 million, compared with $344 million in the same period last year; its operating loss widened to $2.047 billion, compared with a loss of $1.426 billion in the same period last year.

From a global geographic perspective, the US domestic market continued to serve as the core growth engine, with third-quarter revenue reaching $67.681 billion, up from $60.846 billion in the second quarter of this year.

Overseas markets also performed steadily. Among them, revenue from Europe, the Middle East, and Africa was $32.695 billion, Asia-Pacific revenue was $19.906 billion, and revenue from other Americas regions was $7.10 billion, with all major global regions maintaining solid performance.

Looking at this scorecard, on the one hand, the 25% revenue surge, the doubling of Google Cloud, and Gemini's continuously expanding user base show that Alphabet's commercial capabilities in AI infrastructure, model services, and consumer applications are strengthening; on the other hand, the significantly expanded debt scale and continuously climbing capital expenditures have also kept the market on edge.

In this "computing power long march" jointly bet on by the giants, Alphabet has demonstrated firm strategic resolve. For an empire with half a trillion dollars in annualized revenue, whether the aggressive AI infrastructure can deliver super returns beyond costs in the future will become the core test determining the direction of its valuation in the next stage.

Below is a condensed transcript of Alphabet's third-quarter earnings analyst call:

Pichai's remarks: Let me start with the Gemini 4 series frontier models. Two weeks after Argon's release, demand and usage are strong; on the developer platform, usage climbed 3.5 times as fast in its first week as Gemini 3, even with capacity constraints.

Argon performs outstandingly in fields such as finance, law, cybersecurity, and science, and developers and cloud customers have already used it to untangle legacy codebases, accelerate scientific research, robotics, discover product improvements, and handle domain-specific tasks requiring deep reasoning. Inside Google, over the past few weeks, the Chrome, Ads, and Search teams have used Argon to write and optimize code faster, with code delivery up 35% and errors down 30%.

Argon is just the beginning of the Gemini 4 series. We also released Carbon today, our strongest frontier model, with advanced cybersecurity and long-horizon capabilities, ranking first with 59 points on the recently updated Artificial Analysis Intelligence Index. Carbon outperforms Argon in almost all areas, including full-stack web development, multimodal understanding, complex knowledge work, and scientific reasoning. We are first rolling out Carbon to select trusted cyber defense parties before expanding access, and it is undergoing testing by the US government.

In addition to the Gemini 4 series, on October 27 we released Genie 4, our most advanced world model to date, capable of simulating safe, realistic, interactive worlds in real time and supporting native audio, an important foundation for training robots and agents. This rapid progress highlights our extraordinary model momentum.

We have entered a stage where AI helps improve the speed of training and release. I expect the next 12 months to continue accelerating due to recursive self-improvement (RSI). We have more models coming soon, including more efficient versions to help developers optimize speed and cost, and to deploy to our billions of users.

Next, search. Search is bringing the benefits of AI to more people than any other product. Just as we shifted to mobile more than a decade ago, we are focused on building the best search user experience first and monetizing later.

We are building a seamless experience from AI Overviews and AI Mode all the way to traditional search. People are using our AI features more and searching in entirely new ways; queries are longer, more personalized, and more multimodal.

Queries in AI Mode are on average three times longer than traditional search, and one in five AI Mode searches globally uses voice, images, or documents. We now have more than 50 billion visual searches per month. One area I am particularly excited about is helping people complete everyday tasks such as bookings, form filling, appointments, and shopping.

As AI becomes more personalized and begins to take actions for people and businesses, trust and safety matter more than ever. People already trust Google with everyday tasks, and our leadership in this area remains an important differentiator.

We are building these agentic experiences first in