Applied Materials, Lam Research and KLA Corp. have all outperformed the chip index over the past month as the AI trade shifts from LLM companies to factory builders.
Semiconductor equipment makers are outperforming the broader chip sector as rising chip prices and factory buildouts shift investor attention away from large language model companies.
Applied Materials, Lam Research and KLA Corp. have all beaten the Philadelphia Semiconductor Index over the past month. The logic is straightforward: if every AI company needs the same Nvidia GPUs, the bottleneck moves upstream to the factories that produce them.
Taiwan Semiconductor Manufacturing Co. said last month it plans to spend $32 billion on new fabrication plants this year, up from $28 billion in 2025. Samsung Electronics and Intel have similar expansion programs. Each new fab requires billions of dollars in wafer-processing equipment, deposition tools and inspection systems – the exact product lines that Applied Materials and its peers sell.
"The AI trade is rotating from the design houses to the capital equipment suppliers," said Stacy Rasgon, an analyst at Bernstein. "The LLM story is getting crowded. The fab buildout is just getting started."
The rotation comes as the cost of training large language models drops. OpenAI, Google and Meta have all released smaller, cheaper models that approach the performance of their flagship systems. That pressures margins for AI chip buyers but does nothing to slow the physical buildout of data centers and chip factories.
Equipment stocks still carry execution risk. Applied Materials faces export controls that limit sales to China, which accounted for 28% of its revenue last quarter. Lam Research warned in April that some customers were delaying orders. The multiyear capex cycle from TSMC, Samsung and Intel provides a revenue floor that most AI software companies lack.
TSMC reports July revenue on Aug. 10. The number will offer the first read on whether the equipment buildout is on pace.
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