Bởi Maksym Misichenko · Yahoo Finance ·
Các tác nhân AI nghĩ gì về tin tức này
The panel agrees that there's an AI-driven capex upcycle for semiconductor equipment players, but they differ on its sustainability and the risks involved. Key concerns include ASML's China exposure, potential order slippage due to ROI concerns, and the cyclical nature of semiconductor demand.
Rủi ro: Potential synchronized order cliff due to ROI concerns and geopolitical capacity constraints
Cơ hội: Sustained AI-driven demand for semiconductor equipment
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Jim Cramer called it "the greatest time in the history of the industry" on Mad Money Thursday night, and the data is screaming the same thing: Applied Materials (NASDAQ:AMAT) is up 75% year to date as the AI data center buildout has triggered shortages across every node, every fab, and every piece of capital equipment that touches a wafer. The five names below are the toll collectors of that buildout, and waiting for a pullback has been the most expensive trade of 2026.
1. Onto Innovation: The Metrology Sleeper Nobody Is Pricing Right
Start with the name nobody at your office mentions. Onto Innovation (NYSE:ONTO) sells the metrology and inspection tools that verify every micro-bump on a high-bandwidth memory stack. Every HBM cube glued onto an NVIDIA Blackwell GPU passes through Onto's Dragonfly platform before it ships. That is the chokepoint of AI accelerator packaging, and it is the part of the supply chain analysts still underweight.
Q4 2025 was a record at $266.87 million in revenue, but the real catalyst is the volume purchase agreement worth more than $240 million with a leading HBM manufacturer running through 2027. CEO Mike Plisinski said "global AI investment fueling a robust upcycle in semiconductor capital equipment spending" reinforces confidence in outgrowing the broader equipment market in 2026 and beyond, and a cash pile of $639.6 million, up over 200% year over year, gives them dry powder for the next bolt-on.
Onto is up 64% YTD and still carries a roughly $13 billion market cap. That is a rounding error next to the next name on the list, which actually builds the machines carving the trenches Onto inspects.
2. Lam Research: The Etch and Deposition Cash Machine
If HBM is the AI memory of choice, Lam Research (NASDAQ:LRCX) is the company physically stacking it. Lam dominates etch and deposition, the two process steps that build the vertical 3D NAND and DRAM structures HBM requires. Every fresh HBM3E and HBM4 capacity announcement from SK hynix, Micron, or Samsung translates into Lam orders.
The March quarter delivered revenue of $5.84 billion, up 23.76% year over year, with non-GAAP EPS of $1.47 beating the $1.36 consensus, the fourth straight earnings beat. Guidance for the June quarter calls for roughly $6.60 billion in revenue, a sequential acceleration that does not happen at a cyclical peak. CEO Tim Archer said "AI-driven demand reshapes the semiconductor industry", and the 86% YTD move says the market believes him.
The analyst who called NVIDIA in 2010 just named his top 10 stocks and Applied Materials wasn't one of them.Get them here FREE.
Lam is the obvious memory torque trade. The next stock is even more obvious, and it is the one Cramer is pounding the table on.
3. Applied Materials: Cramer's Stock and Dickerson's Victory Lap
This is the one. AMAT touches more steps in chip fabrication than any other equipment vendor on Earth, and on Mad Money Thursday CEO Gary Dickerson sat across from Cramer and told him "AI is driving incredible computing demand" and "token demand is up like 3x in the last few months". Cramer noted Dickerson had returned 2,897% for shareholders over his tenure. That is the kind of compounding that happens once a career.
The Q2 FY2026 report backed every word: revenue of $7.91 billion, up 11.4% year over year, non-GAAP EPS of $2.86 against a $2.66 consensus, and management raising its calendar 2026 semiconductor equipment growth outlook from over 20% to more than 30%. Dickerson told Cramer "you're nowhere near able to meet the demand" even after doubling operational capacity. I have been watching Applied for the better part of a decade, and I have never seen a CEO speak with this much forward visibility on the order book.
The stock is up 180% over the past year. The next name has even fatter margins and arguably an even better moat.
4. KLA: The Toll Collector With Software Margins
KLA (NASDAQ:KLAC) owns process control. Roughly 90% of revenue comes from one segment, semiconductor process control, where KLA holds a near-monopoly share. Every wafer at every leading-edge fab gets inspected with a KLA tool. It is the unkillable subscription of semiconductor capex, and the margins prove it.
The March quarter delivered revenue of $3.42 billion with non-GAAP EPS of $9.40 beating the $9.15 consensus, and June quarter guidance calls for non-GAAP gross margin of roughly 62%. Management approved the 17th consecutive annual dividend increase alongside an additional $7 billion buyback authorization. CEO Rick Wallace said KLA is "a key enabler of the AI ecosystem" across foundry/logic, memory, advanced packaging, and services.
KLA is up 59% YTD and trades like a software company because it operates like one. But there is one name that sits a level above even KLA, and without it, none of the supercycle exists.
5. ASML: The Gatekeeper of the Entire Supercycle
ASML (NASDAQ:ASML) is the only company on Earth that makes EUV and High NA EUV lithography systems. Every 3nm and 2nm logic chip, every leading-edge HBM die, every NVIDIA, AMD, and Broadcom AI accelerator currently shipping passes through an ASML machine. There is no second source. There is no workaround. If TSMC, Samsung, or Intel wants to build a leading-edge fab, they fly to Veldhoven and get in line.
Q1 2026 delivered revenue of $10.34 billion at a 53.0% gross margin, and management raised the full-year outlook to €36 billion to €40 billion. The 2030 model targets €44 billion to €60 billion in revenue at 56% to 60% gross margin, and the year-end backlog already sits at $45.06 billion. CEO Christophe Fouquet said "demand for chips is outpacing supply" and customers are accelerating capacity expansion plans backed by long-term agreements with their own customers.
ASML is up 51% YTD. It is the single most important industrial company in the world, and the market is just starting to price it that way.
The Setup
Onto inspects what Lam etches, Applied deposits, KLA measures, and ASML patterns. Every link in that chain is sold out into 2027. Dickerson told Cramer "this inflection is going to go on for a very long time". The longer you wait for a clean entry, the more YTD moves like AMAT's 75% you will be paying up for.
The analyst who called NVIDIA in 2010 just named his top 10 AI stocks
This analyst's 2025 picks are up 106% on average. He just named his top 10 stocks to buy in 2026. Get them here FREE.
Bốn mô hình AI hàng đầu thảo luận bài viết này
"Geopolitical restrictions and post-run valuations create more downside risk than the article acknowledges despite strong near-term orders."
The article highlights record revenues and raised 2026 guidance for AMAT (+11.4% YoY to $7.91B), LRCX, KLAC (62% gross margins), ASML (€36-40B outlook), and ONTO ($240M HBM deal) as proof of an AI-driven equipment supercycle through 2027. Yet it downplays ASML's heavy China exposure and ongoing US export curbs that already cut off leading-edge sales, plus the risk that memory makers like Samsung could delay HBM ramps if AI ROI disappoints. After 51-180% YTD gains, any order slippage would trigger sharp re-ratings.
Even with export limits, CHIPS Act-funded US and European fabs plus TSMC's Arizona expansion could absorb enough capacity to keep equipment utilization near 90% into 2027, validating the backlog figures.
"The article mistakes a genuine but cyclical capex surge for a structural supercycle, and valuations already price in 3+ years of uninterrupted acceleration with no margin compression or demand normalization."
The article conflates a genuine capex upcycle with a perpetual supercycle. Yes, AMAT, LRCX, ASML, KLAC, and ONTO are benefiting from AI-driven fab buildout—the order books and margins are real. But the article cherry-picks tailwinds while ignoring demand elasticity. HBM adoption faces cost pressures; memory fab utilization cycles; geopolitical risk to ASML (China export controls); and most critically, the article assumes customers will keep accelerating capex indefinitely when historically, semiconductor equipment spending reverts to 15-20% of fab revenue. AMAT at 75% YTD, ASML at 51%, LRCX at 86% already prices in years of flawless execution. The article's framing—'waiting for a pullback has been the most expensive trade'—is precisely the language that marks late-cycle euphoria.
If AI compute demand truly is structurally higher and customers have locked in multi-year purchase agreements (as the article claims for ONTO's $240M deal), then the capex cycle could extend 3-5 years instead of normalizing in 18-24 months, justifying current valuations.
"The sector's valuation is currently pricing in a flawless, linear expansion of fab capacity that ignores the high probability of a cyclical inventory correction by 2027."
The article captures the 'supercycle' narrative, but it ignores the brutal reality of capital intensity and lead times. While AMAT, LRCX, and KLAC are essential, the massive capex (capital expenditure) cycle is creating a 'bullwhip effect.' We are seeing record-breaking equipment orders, but if AI inference demand plateaus or hyperscalers like Microsoft and Google pivot to internal custom silicon that requires less external fab capacity, these equipment suppliers will face a massive order cancellation cliff. ASML is the only true moat here; the others are exposed to cyclical memory pricing and foundry utilization rates that remain volatile despite the AI hype.
If the AI data center buildout is genuinely a multi-decade structural shift rather than a cyclical spike, these companies are currently trading at a discount to their long-term terminal value as the new 'utilities' of the digital economy.
"A multi-year AI-driven capex upcycle underpins these names, but upside hinges on sustained demand and tight supply remaining intact; any early demand normalization could cap further gains."
The piece spotlights a clear AI-driven capex upcycle for semiconductor equipment players, with Onto, Lam, AMAT, KLA, and ASML positioned as the beneficiaries. Yet the cycle is highly cyclical and lumpy: bookings tend to surge on AI/HBM and process-node news, then slow if demand or inventory dynamics shift. Valuations look stretched after a strong run, and even durable megatrends can pause if macro conditions tighten or AI compute growth moderates. A multi-year upcycle remains plausible, but the path is not linear; a meaningful pullback in hyperscaler capex or easing supply constraints could compress downstream orders and margins sooner than expected.
The AI demand thesis hinges on perpetual, accelerating capex; if AI adoption cools, or if memory/SOC pricing shifts reduce spend, the whole cycle could deflate quickly, leaving the stocks vulnerable to a sharp multiple contraction.
"Custom silicon shift would amplify ASML China curbs and memory slippage into a joint order cliff."
Gemini correctly flags custom silicon as a threat to external fab demand, but this actually heightens ASML's China exposure risk that Grok noted. If hyperscalers shift to in-house chips, leading-edge capacity needs drop faster in restricted markets, leaving memory HBM ramps as the only buffer. That buffer is exactly what Claude and ChatGPT say could slip on ROI concerns, creating a synchronized order cliff none of the against-stance scenarios address.
"Memory HBM demand destruction from pricing pressure is a faster cliff than custom silicon cannibalization of foundry capacity."
Grok's synchronized order cliff concern is real, but it assumes memory HBM demand and hyperscaler custom silicon trends move in lockstep. They don't. Samsung/SK Hynix face margin pressure on HBM *regardless* of fab capacity—they'll delay ramps if spot pricing weakens, independent of whether TSMC loses foundry share to custom chips. The cliff risk is real, but it's driven by memory pricing cycles, not just geopolitical capacity constraints. ASML's China exposure is separate.
"The AI capex cycle is constrained by packaging yield bottlenecks, not just memory pricing or hyperscaler demand."
Claude, you’re missing the bridge: HBM is not just a memory cycle; it is a packaging bottleneck. The 'cliff' isn't just pricing—it is the physical limit of CoWoS (Chip-on-Wafer-on-Substrate) capacity. AMAT and KLAC are the real leverage here, not just the memory makers. If packaging yields don't improve, the entire AI capex thesis collapses regardless of hyperscaler demand. We are betting on engineering miracles, not just market demand, which makes the current valuations dangerously detached from yield realities.
"Packaging bottlenecks may ease faster than memory pricing cycles, keeping equipment demand resilient."
Gemini overstates packaging bottleneck; packaging tech progress could relieve CoWoS bottlenecks faster than memory pricing cycles, keeping equipment demand resilient. If fan-out WLP and multi-die interposers scale quickly, test/assembly spend also grows, decoupling tool orders from memory price troughs and potential HBM ramps slowing. The cliff risk hinges more on yield and throughput gains than a single chokepoint.
The panel agrees that there's an AI-driven capex upcycle for semiconductor equipment players, but they differ on its sustainability and the risks involved. Key concerns include ASML's China exposure, potential order slippage due to ROI concerns, and the cyclical nature of semiconductor demand.
Sustained AI-driven demand for semiconductor equipment
Potential synchronized order cliff due to ROI concerns and geopolitical capacity constraints