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Lam Research targets 50%+ gross margin as AI chip demand surges

Lam Research targets 50%+ gross margin as AI chip demand surges

3 Key Points

  1. What happened

    Lam Research reported third-quarter non-GAAP gross margin of 49.9% and record revenues of $5.84 billion(約9300億円), up 24% year over year. The company guided for fourth-quarter revenues of $6.6 billion(約1.1兆円) at the midpoint and a non-GAAP gross margin of 50.5%, marking the first time it has guided above the 50% threshold. Strong demand for advanced memory, foundry, and packaging equipment is driving the improvement.

  2. Why it matters

    AI is the biggest driver of the company's profitability gains. Equipment makers serving chipmakers investing in AI processor production are seeing better product mix and higher returns. For Lam Research customers, this reflects a major shift in spending priorities toward AI infrastructure—a trend that may signal sustained investment cycles in semiconductor manufacturing capacity over the coming year.

  3. What to watch

    Lam Research expects advanced packaging revenues to increase by more than 50% in calendar year 2026 as chipmakers invest in complex packaging technologies for AI processors. Management also forecasts wafer fabrication equipment spending of about $140 billion(約22兆円) this year.

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FAQ
What is driving Lam Research's margin improvement?
Strong demand for advanced memory, foundry, and packaging equipment used in AI chips and high-bandwidth memory production is improving the company's product mix and allowing it to generate higher returns from its portfolio.
When does Lam Research expect to cross the 50% gross margin threshold?
The company has guided for a non-GAAP gross margin of 50.5% in the fourth quarter of fiscal 2026, which would be the first time it has guided for a margin above the 50% level.
How much will advanced packaging revenue grow in 2026?
Lam Research expects advanced packaging revenues to increase by more than 50% in calendar year 2026 as chipmakers invest in complex packaging technologies for AI processors.
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