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$420 billion: Alphabet and Amazon's 2026 AI capex, and the hardware names positioned to capture it

$420 billion is the projected combined AI infrastructure outlay from Alphabet (NASDAQ: GOOGL) and Amazon (NASDAQ: AMZN) in 2026, with Alphabet guiding to between $195 billion and $205 billion and Amazon targeting approximately $220…

By Kwame Asante·Aug 23, 2026·2 min read·earnings·GOOGL · AMZN · NVDA · AVGO

Key takeaways

  • Alphabet and Amazon are projected to spend a combined roughly $420 billion on AI infrastructure in 2026, with Alphabet guiding to $195-$205 billion and Amazon targeting about $220 billion.
  • Four hardware companies sit directly in this spending stream: Nvidia, Broadcom, Micron Technology, and Sandisk.
  • Amazon raised its 2026 capex from $200 billion to $220 billion because memory chip prices have risen sharply amid capacity that has not kept pace with hyperscaler demand.
  • Two-thirds of Sandisk's revenue growth came from higher selling prices and one-third from increased output, making the memory trade a margin story rather than a volume story.
  • Micron's management says the memory shortage will last into 2028, extending the window of above-trend pricing for both Micron and Sandisk.

$420 billion is the projected combined AI infrastructure outlay from Alphabet (NASDAQ: GOOGL) and Amazon (NASDAQ: AMZN) in 2026, with Alphabet guiding to between $195 billion and $205 billion and Amazon targeting approximately $220 billion. At Alphabet's midpoint of $200 billion, the components sum to the headline. Four hardware names sit directly in the spend stream: Nvidia (NASDAQ: NVDA), Broadcom (NASDAQ: AVGO), Micron Technology (NASDAQ: MU), and Sandisk (NASDAQ: SNDK).

Company 2026 capex guidance Label
Alphabet $195B to $205B Projected
Amazon ~$220B Projected
Combined midpoint ~$420B Projected

Compute layer: Nvidia volume versus Broadcom's TPU

Nvidia is the baseline beneficiary. Cloud clients specify Nvidia compute because workloads built on it can migrate between providers without architecture rewrites, a flexibility that sustains demand. Nvidia has told investors it expects AI hyperscaler spending to top $1 trillion in 2027. If that figure tracks, 2026 reads as mid-cycle.

Broadcom enters through the Tensor Processing Unit, co-developed with Alphabet. TPUs carry better cost-performance than Nvidia chips on properly configured workloads. The configuration process can bind clients to Alphabet's cloud ecosystem rather than leaving them portable. Broadcom expects its custom AI semiconductor division to exceed $100 billion in sales, against $10.8 billion recorded in the second quarter.

Memory: price-driven gains on a fixed cost base

Amazon revised its 2026 capex up from $200 billion to $220 billion because memory chip prices have risen sharply, with the same supply pressure likely shaping Alphabet's guidance. Capacity has not kept pace with hyperscaler demand.

Sandisk's latest quarterly results broke down the revenue split: two-thirds of growth traced to higher selling prices, one-third to increased output. Input costs for Sandisk and Micron have held steady. Only the end selling price has moved, which is what makes the memory trade a margin story rather than a volume story. Micron's management has said the shortage will last into 2028, extending the window of above-trend pricing for both companies. That 2028 timeline is the firmest forward commitment either company has made.

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Frequently asked

How is the $420 billion combined figure calculated?

It sums Amazon's approximately $220 billion 2026 capex target with Alphabet's guidance at its midpoint of $200 billion (from a range of $195-$205 billion).

Why is Broadcom positioned to benefit from this spending?

Broadcom enters through the Tensor Processing Unit co-developed with Alphabet, and it expects its custom AI semiconductor division to exceed $100 billion in sales, up from $10.8 billion in the second quarter.

What makes Nvidia the baseline beneficiary?

Cloud clients specify Nvidia compute because workloads built on it can migrate between providers without architecture rewrites, and Nvidia expects AI hyperscaler spending to top $1 trillion in 2027.

Why are memory chip prices rising?

Capacity has not kept pace with hyperscaler demand, and Micron's management expects the shortage to last into 2028.