To The Moon

Alphabet will report its second-quarter results on Wednesday after the U.S. market closes.

This earnings release matters far beyond $Alphabet(GOOGL)$ itself.

TSMC and ASML have already shown that demand for advanced chips and semiconductor equipment remains strong. Google now has to answer the next question in the AI value chain:

Can all that spending on chips, servers and data centers turn into cloud revenue, advertising growth and free cash flow?

Wall Street currently expects roughly $116.8 billion in Q2 revenue, including about $22.2 billion from Google Cloud. Options markets are pricing in an earnings move of around 5.3%.

The first test: Can Google Cloud keep growing above 60%?

Google Cloud was Alphabet’s strongest business in the first quarter.

Revenue rose 63% year over year to $20 billion, while backlog nearly doubled sequentially to more than $460 billion. Alphabet said enterprise AI infrastructure and AI solutions were major drivers of that acceleration.

For Q2, the market expects Cloud revenue of around $22.2 billion, representing growth of roughly 63%. (IG)

That is already a demanding forecast.

If Google Cloud maintains or exceeds that pace, it would suggest that Alphabet’s infrastructure spending is converting into real customer demand.

Investors should focus on:

• Cloud revenue growth

• Operating margin

• Remaining contract backlog

• Enterprise AI adoption

• Whether compute shortages are still limiting growth

Alphabet previously said Cloud revenue could have been even higher if it had more available compute capacity. (Sahm)

A strong result would support the entire AI infrastructure chain. A slowdown would raise questions about whether capacity is expanding faster than customer spending.

The second test: Is AI strengthening Search or disrupting it?

Search remains Alphabet’s main profit engine.

Google has been integrating AI Overviews and AI Mode into more search experiences. Management has argued that AI features are encouraging users to ask more complex questions and return to Search more often. Search and other advertising revenue grew 19% in Q1. (blog.google)

The market now needs evidence that this new behavior can be monetized.

Key questions include:

• Are AI-powered searches generating comparable ad revenue?

• Are users clicking fewer traditional links?

• Is commercial search activity still growing?

• How much additional computing cost comes with each AI query?

• Can stronger engagement offset higher inference costs?

The best outcome would be faster search usage, stable advertising economics and manageable AI costs.

The risk is that AI answers reduce clicks while the cost of serving each query rises.

The third test: What happens to the $180–190 billion capex plan?

Alphabet expects to spend $180 billion to $190 billion on capital expenditure in 2026, roughly double last year and about six times its 2022 level. The overwhelming majority will go toward technical infrastructure, including servers, data centers and networking. The company has also said that 2027 spending should increase significantly again. (blog.google)

This creates a difficult setup for the market.

If Alphabet raises capex again, suppliers across the AI hardware chain may benefit. Investors could still worry about depreciation, power costs and pressure on free cash flow.

If Alphabet cuts or slows spending, cash-flow pressure may ease. The market could interpret that as weaker AI demand.

Reuters noted that any pullback in Alphabet’s AI spending outlook could have ripple effects across the broader AI ecosystem. (Reuters)

The most bullish combination would be:

Cloud growth remains strong, AI revenue accelerates and capex stays elevated.

The most worrying combination would be:

Capex rises again, while Cloud growth, margins or AI monetization begin to slow.

The fourth test: Can TPUs become a real external business?

Google’s custom TPU chips have historically been an internal advantage.

They help Alphabet train and run Gemini models while reducing its dependence on external accelerators for some workloads.

That strategy is now moving toward external commercialization.

Alphabet has said it will begin delivering TPUs directly to selected customers’ data centers. A small amount of related revenue is expected later in 2026, with the majority expected in 2027. (Sahm)

This could give Google a second AI infrastructure revenue stream alongside Cloud.

Investors should watch for:

• Direct TPU sales or delivery updates

• External customer adoption

• Whether TPUs improve Cloud margins

• New Gemini and API usage data

• How Google positions TPUs against Nvidia and other custom chips

The likely industry structure is not a winner-takes-all market.

Cloud companies may use a mix of Nvidia GPUs, AMD accelerators and their own custom silicon depending on workload, cost and availability.

Stocks that could react

Alphabet

$Alphabet(GOOGL)$ and $Alphabet(GOOG)$ will trade on Cloud growth, Search advertising, capex, margins and AI monetization.

AI chips and custom silicon

$NVIDIA(NVDA)$ remains the main supplier of general-purpose AI compute.

$Broadcom(AVGO)$ is a key custom-chip and data-center networking name.

$Taiwan Semiconductor(TSM)$ manufactures advanced AI chips for multiple customers.

$Advanced Micro Devices(AMD)$ provides an alternative accelerator and data-center platform.

$Marvell Technology(MRVL)$ offers exposure to custom silicon and high-speed connectivity.

Networking, power and data centers

$Arista Networks(ANET)$ supplies high-speed data-center networking.

$Vertiv(VRT)$ provides power and thermal-management systems.

$Eaton(ETN)$ is exposed to data-center electrical infrastructure.

$Constellation Energy(CEG)$ and $Vistra(VST)$ are tied to rising data-center power demand.

Cloud competitors

$Microsoft(MSFT)$ will be the clearest comparison through Azure and its OpenAI ecosystem.

$Amazon(AMZN)$ remains the cloud-market leader through AWS.

$Oracle(ORCL)$ offers high-growth AI infrastructure exposure, alongside heavier financing and capex questions.

TigerComments Take

Alphabet’s earnings will be the first major downstream test after strong results from the semiconductor supply chain.

TSMC and ASML have already confirmed that chip orders and equipment demand remain strong.

Google now needs to prove that those chips can generate:

• Cloud revenue

• Search and advertising growth

• Gemini adoption

• TPU sales

• Sustainable cash flow

The AI spending boom is real.

The next stage of the market will depend on whether the returns are becoming equally real.

What matters most in Google’s earnings?

A. Google Cloud growth
B. $180–190 billion AI capex
C. AI Search and advertising
D. TPU and Gemini monetization

Do you think Alphabet is becoming the most complete AI platform across models, chips, cloud and applications—or does the spending still need more time to prove its return?

Disclaimer: This post is for market discussion only and does not constitute investment advice. Investing carries risk.