Alphabet and Meta Platforms reported earnings showing stronger growth, while market reactions moved in opposite directions. Alphabet shares rose by 7% in after-hours trading, while Meta shares declined by 7%. The difference reflects how investors are assessing AI-related spending and revenue models.

Impressive Earnings With Divergent Outcomes

Both companies increased capital expenditure forecasts as investment in artificial intelligence expands. Sundar Pichai, Chief Executive Officer of Alphabet, raised 2026 capex guidance to $180 billion–$190 billion. In parallel, Mark Zuckerberg, Chief Executive Officer of Meta, increased the company’s forecast to $125 billion–$145 billion, citing higher infrastructure and component costs.

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Strategies Shaped By Cloud Infrastructure

Alphabet continues to generate revenue from cloud services alongside AI development. Cloud revenue increased by 63%, supported by a backlog of approximately $460 billion. This model allows the company to link infrastructure investment with revenue growth, alongside offerings that include internally developed processing units. Peers such as Microsoft and Amazon follow a similar structure.

Defending Heavy Investments In AI

Meta’s approach differs due to the absence of a large cloud business. Investment is linked more directly to advertising performance and user engagement. During the earnings call, Zuckerberg referred to improvements in engagement and advertiser outcomes, alongside the rollout of products such as the Muse Spark model.

The Road Ahead

Meta’s share performance has trailed some peers, while its investment focus includes custom silicon developed with Broadcom and additional use of chips from AMD alongside systems based on Nvidia technology. These investments are tied to expanding AI infrastructure and supporting internal workloads. At the same time, Alphabet continues to scale its AI infrastructure, with Sundar Pichai noting increased demand for both GPU and TPU capacity during the latest earnings call. Market reactions reflect differences in how these approaches are evaluated, particularly in relation to revenue generation from cloud services and advertising models.