谷歌财报足够亮眼，但华尔街为什么不买账？

Original by Odaily Planet Daily (@OdailyChina)

Author: Azuma (@azuma_eth)

On the morning of July 22, Beijing time, Google parent company Alphabet announced its Q2 2026 earnings report after the US stock market close.

Looking purely at the performance figures, this was a nearly perfect report card. In Q2, Alphabet achieved revenue of $119.8 billion, a 24% year-over-year increase, and operating profit of $40.8 billion, up 30% year-over-year. The company has maintained double-digit revenue growth for the 12th consecutive quarter, with its core business continuing to show strong resilience.

• Odaily Note: As shown in the table above, many investors noticed Google's explosive Q2 EPS of $9.11, far exceeding last year's $2.31. However, this is mainly due to the valuation increase of its 14% stake in Anthropic. Excluding this gain, EPS would be $2.85, below market expectations of $2.95.

Among these, Google Cloud, which attracted the most market attention, delivered results significantly exceeding expectations. Last quarter, Google Cloud revenue reached $24.77 billion, an 82% year-over-year increase, making it Alphabet's fastest-growing business segment.

Meanwhile, Google's traditional core business remained solid. Google Services revenue was $94.54 billion, up 15% year-over-year. Within this, Search and other revenue reached $63.27 billion (up 17%), and YouTube advertising revenue hit $11.06 billion (up 13%).

From revenue and profit to AI business progress, Google delivered almost everything investors hoped to see. Interestingly, however, Alphabet's stock didn't rise after the earnings release; instead, it fell nearly 3% in after-hours trading.

Why isn't the market buying it? The reason isn't hard to understand: compared to "how much money Google made," the market now cares more about "how much it will cost Google to win the AI era."

Capex Surges to $200 Billion, Free Cash Flow Turns Negative for the First Time

In the past few years, thanks to continuous profit generation from Search and Advertising, Google has been one of the tech giants with the strongest cash flow. But this pattern is rapidly changing as AI competition intensifies.

To secure a leading position in AI infrastructure, Alphabet is ramping up spending. In Q2, Alphabet's capital expenditure reached $44.9 billion (exceeding market expectations of $44.2 billion). The company also raised its full-year 2026 capital expenditure guidance from the previous $180-190 billion to $195-205 billion.

By spending category, most funds are allocated to AI infrastructure construction, including servers, data centers, and network equipment. This means Google might invest close to $200 billion in a single year to bet on AI.

This massive investment has put new pressure on Google. In Q2, due to rapidly growing capital expenditure, Alphabet's free cash flow turned negative for the first time. Operating cash flow was $39.1 billion, while capital expenditure was $44.9 billion, resulting in a free cash flow of -$5.855 billion.

During the post-earnings investor call, Alphabet CFO Anat Ashkenazi acknowledged the cash flow issue, stating, "Investment in AI infrastructure will continue to put pressure on the income statement and cash flow."

Furthermore, to support this continuous AI infrastructure expansion, Google has started large-scale borrowing. In June, Alphabet completed an offering of stock and convertible preferred stock, netting approximately $49.6 billion. The company also issued $20.3 billion in senior unsecured bonds to supplement capital needs.

For a company that previously won investor favor based on strong cash flow advantages, this is undoubtedly a significant shift. Of course, the market isn't opposing Google's continued investment in AI. The real question is: "How long will it take for these investments to translate into a new growth curve?"

Google Cloud Performs Well, But Not Enough

Fortunately, the Google Cloud revenue performance in Q2 can somewhat alleviate some investor anxiety.

Enterprises training models and deploying AI applications require massive computing resources, and cloud services are the key entry point connecting AI capabilities with business customers. In Q2, Google Cloud revenue reached $24.77 billion, an 82% year-over-year increase, not only significantly exceeding market expectations but also marking the fastest growth rate in recent years.

More importantly, the core driver of cloud business growth is shifting from traditional cloud computing demand towards AI infrastructure and enterprise-level AI solutions. Alphabet stated in its earnings report that Google Cloud's growth this quarter was primarily driven by enterprise AI infrastructure demand, Google Cloud Platform (GCP) AI solutions, and core cloud service growth.

Meanwhile, Google Cloud's order backlog continues to expand. As of the end of Q2, Google Cloud's remaining performance obligations (RPO) reached $514 billion, increasing further from the previous quarter. Over half of this is expected to be recognized as revenue within the next 24 months. At least for now, Google's investment in AI infrastructure isn't just about pursuing a tech race; it is starting to translate into actual business growth.

Compared to other AI giants, Google's biggest advantage is its more complete industry chain. From the Gemini model to self-developed TPU chips to the Google Cloud platform, Google covers multiple layers of AI infrastructure.

Google Cloud's current high-growth trend somewhat provides a阶段性 report on AI investment returns… But it's still far from enough. After all, while Google Cloud's annualized revenue has reached about $100 billion, Alphabet's annual capital expenditure has surged to $200 billion.

As AI infrastructure investment continues to expand, can future revenue growth maintain sufficient speed to ultimately cover this capital spending? The market still doesn't have an answer for now. Judging by the after-hours decline, the market may hold a more cautious view on this.

Is Gemini's Intelligence Becoming the Biggest Concern?

If Google Cloud proves Google can generate commercial benefits from the AI wave, then Gemini determines whether Google can maintain its lead in this long-term competition.

In recent years, Google has emphasized its "full-stack AI" strategy. From underlying TPU chips and data centers, to the Gemini model, to the Google Cloud platform, Google aims to build a complete system covering AI infrastructure and application ecosystem.

According to data disclosed in the earnings report, Gemini's user base is also growing rapidly. Currently, the Gemini App has 950 million monthly active users. The Gemini model API processes approximately 22 billion tokens per minute. Meanwhile, nearly 90% of Fortune 100 companies use Gemini Enterprise.

These figures prove Google hasn't missed the AI commercialization wave. However, market concerns about Gemini persist.

The reason is that the core of AI competition isn't just user numbers and infrastructure scale; model capability equally determines ecosystem attractiveness. Previously, Google delayed the planned launch of Gemini 3.5 Pro, raising market concerns about its model competitiveness. Especially in high-value application scenarios like AI programming and intelligent agents, competitors like Anthropic and OpenAI are iterating rapidly, and Gemini seems to be showing clear signs of falling behind.

For Google, the most important issue now is whether Gemini can prove itself to be back in the first tier.

In the past, Google's biggest advantages were its globally leading search engine, strong engineering capabilities, and massive data resources. But the rules of competition are changing in the AI era. User habits might shift from traditional search to AI assistants, and developers might prioritize more powerful model ecosystems. If Gemini can't prove itself, even with the most comprehensive infrastructure, Google might face the risk of its application value being intercepted by other models.

The AI Race Shifts Focus to "Value Realization"

Looking back, Alphabet's earnings report presents a very clear two-sided picture.

On one hand, Google is proving AI investment isn't just a capital market fantasy. The rapid growth of Google Cloud, the continuous increase in AI infrastructure demand, and the expansion of Gemini's user base all show AI is gradually transitioning from a tech wave to real commercial demand. However, on the other hand, market caution isn't unwarranted. Nearly $200 billion in annual capital expenditure, the first negative free cash flow, and intense competitive pressure on model performance mean Google needs to convince investors that this AI gamble can ultimately yield long-term returns exceeding costs.

The challenge Google faces is actually the problem the entire AI industry is confronting. In the past few years, tech giants like Microsoft, Amazon, and Meta have also continuously expanded AI infrastructure investment. Data centers, computing power, and chip procurement have become main battlegrounds for these giants.

Looking ahead, the market's focus may shift from who invests the most to who can faster convert capital spending into commercial value. For Google and other giants, the AI race may just be entering its critical phase.