Applied Materials Hits Record $9.12B Q3 As AI Fab Spend Surges

Applied Materials posted record fiscal Q3 revenue of $9.12B, guided Q4 to $10.25B, and said it aims to double semi-systems output by 2028 as AI drives chip-equipment demand.

Applied Materials Hits Record $9.12B Q3 As AI Fab Spend Surges

Applied Materials posted record fiscal third-quarter revenue of $9.12 billion, up 25% year-on-year, as chipmakers accelerate spending on the equipment needed to build AI processors, memory, and advanced packaging. Non-GAAP earnings per share reached a record $3.50, up 41% year-on-year, while GAAP EPS climbed to $3.17. The company guided fiscal Q4 to about $10.25 billion in revenue with non-GAAP EPS of roughly $4.02.

Semiconductor Systems Segment Powers Growth

Semiconductor Systems revenue rose to $7.04 billion, up from $5.56 billion a year ago, as AI investment lifted demand across DRAM, high-bandwidth memory, advanced packaging, and increasingly complex transistor structures. Applied Global Services contributed $1.78 billion, up from $1.46 billion. The company generated a record $3.04 billion in operating cash and returned $860 million to shareholders through buybacks and dividends in Q3 alone.

Doubling Capacity By 2028

Management said Applied Materials plans to roughly double semiconductor-systems output by 2028, a signal that hyperscaler chip demand is expected to sustain years of elevated capex. The company sits several layers beneath the Nvidias and AMDs of the AI stack, alongside ASML, Lam Research, and KLA — without their tools, next-generation AI chips do not exist. Related coverage: NVIDIA's Open Secure AI Alliance.

Semiconductor fab cluster tool

High Bar Set By Investors

Despite the record numbers, investors pushed AMAT shares lower after the print, a reminder that valuations across the semiconductor supply chain already price in years of extraordinary AI capex. See related: SMIC foundry acquisition and L&T's $1.57B AI cluster order.

Reporting based on coverage from Applied Materials 8-K, Wall Street Journal, and Yahoo Finance.

Category: Electrical Engineering

Tags: AI Semiconductors AI Chips

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