Applied Materials and Lam Research have reported strong semiconductor-equipment demand, with growth tied in part to AI investment. Their results make them worth examining, but they do not by themselves show that either stock is overlooked or undervalued: that conclusion requires a dated comparison of share prices, earnings estimates, cash flow and historical valuations.
What the companies’ latest reported results show
Applied Materials reported record Q3 FY2026 revenue of $9.12 billion, up 25% year over year, for the quarter ended July 26, 2026. The result is a report of past performance; the company’s expectations for the rest of calendar 2026 are forecasts, not reported revenue.
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Lam Research reported $4.25 billion in systems revenue and $2.47 billion in customer support-related revenue for the quarter ended June 28, 2026. Separately, Lam’s full-year FY2026 revenue grew 26.0% from FY2025. Lam attributed the annual increase to equipment demand, particularly from foundry customers, as well as customer-support revenue.
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How Applied Materials and Lam Research differ
Both companies sell equipment and related offerings used in semiconductor manufacturing, so both are exposed to customers’ decisions about fabrication capacity and process technology. Their reported revenue mixes, however, are not interchangeable.
| Company and period | Reported revenue detail | What the category includes |
|---|---|---|
| Applied Materials, Q3 FY2026, quarter ended July 26, 2026 | $7.04 billion in Semiconductor Systems revenue | Revenue serving foundry, logic, other and DRAM customers; the company reported that 67% of the segment was foundry, logic and other, and 26% was DRAM. |
| Lam Research, quarter ended June 28, 2026 | $4.25 billion systems revenue; $2.47 billion customer support-related revenue | Systems revenue covers new leading-edge equipment in deposition, etch and other wafer-fabrication markets. Support-related revenue includes service, spares, upgrades and Reliant product-line equipment. |
Applied changed its segment presentation in FY2026 by moving its 200-millimeter equipment business into Semiconductor Systems. Its comparisons should therefore use the company’s recast figures. Lam’s support-related category includes several offerings, so it should not be treated as directly equivalent to Applied’s segment breakdown.
Why AI and process changes could support demand
Applied CEO Gary Dickerson said on August 13, 2026: “As the rapid global adoption of AI drives unprecedented demand for our materials engineering solutions, we are further raising our Semiconductor Systems revenue expectations for calendar 2026 and are confident we will grow faster than the market this year.” This is management’s outlook, not a guarantee of future sales.
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Lam also says AI is driving higher semiconductor-industry spending across memory and non-memory segments in 2026. Its longer-term growth case includes technology changes such as 3D device scaling, multiple patterning, process-flow changes and advanced packaging integration, which Lam identifies as potential drivers for its deposition, etch and clean businesses. These are company assessments of future opportunities; realized revenue will depend on customer investment and execution.
Applied’s Q3 FY2026 release included Q4 revenue guidance of $10.25 billion, plus or minus $500 million. That is a management forecast, not a result. It can help readers assess the company’s near-term expectations, but it should not be combined with Lam’s historical full-year growth as if both figures covered the same period or represented realized performance.
What could undermine the growth case
Customer spending can change
Equipment sales depend on semiconductor manufacturers’ investment decisions. The reported results show demand in the periods described, but they do not establish how either company would perform through a downturn or set a reliable floor for future sales. Lam’s customer support business is a meaningful part of its reported revenue, but the figures provided do not establish that it is recession-proof or fully recurring.
Export controls can affect Lam’s business
Lam warns that export controls may limit sales or require licenses, increase compliance burdens, and affect whether it can obtain needed materials and components on acceptable terms. Those risks make geography and regulatory exposure important to evaluate; readers should not assume sales to any region will continue at the same level.
Forecasts are not outcomes
AI demand, calendar 2026 growth expectations and technology adoption all form part of management’s growth case. Each remains subject to changing customer budgets, market conditions and execution. A strong quarter or optimistic forecast is evidence to consider, not proof that future results will match expectations.
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How to decide whether either stock is actually overlooked
“Overlooked” is a claim about both the business and what investors currently pay for it. Strong reported growth can be widely recognized in a stock price, while a company with promising technology exposure can still be expensive. The reported operating figures above do not establish current valuation multiples, relative cheapness or a price target.
For a meaningful comparison, use market data and earnings estimates from the same date, and compare both companies on consistent definitions. A valuation check should include:
- Trailing and forward price-to-earnings multiples, with the earnings period and estimate basis clearly identified.
- Enterprise value relative to sales or operating earnings, using consistent accounting periods.
- Free-cash-flow yield alongside recent growth and margins.
- Revenue mix, including Lam’s customer-support-related business and the companies’ different segment definitions.
- China and other geographic exposure, including the effect of export-control requirements.
- Each company’s valuation history and relevant semiconductor-equipment peers, using comparable dates and measures.
Until that dated valuation comparison is made, the defensible conclusion is that Applied Materials and Lam Research have reported strong results and have company-stated AI and technology-related growth opportunities—but whether investors are overlooking either stock remains unresolved. The results alone are not enough to determine whether either is a good stock to buy.
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