Daniel Foelber, The Motley Fool Sun, October 11, 2026 at 6:37 AM EDT 6 min read NVDA -0.52% SPCX +1.25% Explore stocks on Coinbase Trading disclosure Trading disclosure The above button links to Coinbase. Yahoo Finance is not a broker-dealer or investment adviser and does not offer securities or cryptocurrencies for sale or facilitate trading. Coinbase pays us for certain activity generated through this link. Prices displayed are informational.
Even near an all-time high, Nvidia (NASDAQ: NVDA) remains one of the best artificial intelligence (AI) growth stocks. It's evolved from a chip company that primarily made graphics processing units (GPUs) for data centers into an AI infrastructure linchpin. Its rack-scale solution goes far beyond GPUs to capture a larger share of the data center market.
Hyperscalers continue to turn to Nvidia to address their compute needs. On its second-quarter 2026 earnings call, Space Exploration Technologies (NASDAQ: SPCX) noted that Nvidia's Vera Rubin architecture is so advanced that it warrants SpaceX building exclusively on Nvidia.
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SpaceX is working with financial institutions to raise $40 billion to fund its AI build-out. And Nvidia is making compute demands more affordable for AI start-ups, labs, and enterprises by partnering with a consortium of six financial institutions to build $500 billion in AI infrastructure.
Vera Rubin and financing options for compute pave the way for Nvidia's growth runway. But ASML (NASDAQ: ASML) could be an even better AI stock for investors to buy in October. Here's why.
ASML sits upstream along the AI value chain. It makes deep-ultraviolet (DUV) and extreme-ultraviolet (EUV) lithography machines for chip manufacturing. Lithography is arguably the most important step, and although other companies compete with ASML on DUV, no company in the world comes close to EUV, especially with its advanced high numerical aperture (High-NA) EUV machines.
EUV machines will be increasingly needed to manufacture advanced AI logic and memory chips at scale. AI models and applications are driving demand for AI compute supporting the build-out of AI data centers, which are outfitted with GPUs, central processing units, memory chips, and associated networking infrastructure. These are manufactured by AI fabs like those operated by Taiwan Semiconductor Manufacturing (NYSE: TSM), Samsung Electronics, and Intel (NASDAQ: INTC), which buy ASML machines.
In this vein, semiconductor equipment manufacturers like ASML, KLA, Applied Materials, and Lam Research are among the simplest ways to bet on increased demand for AI chip manufacturing. But ASML is the best buy of the group because its innovation is outpacing the industry.
The reason EUV systems are vital for AI chip manufacturing is that they produce wavelengths over 14 times shorter than DUV. Shorter wavelengths produce smaller features on microchip layers in a single pass. Denser features per layer allow manufacturers to fit more transitions or a single chip, thereby boosting performance. High-NA EUV takes that precision a step further by using even shorter wavelengths of 8 nanometer (nm) versus 13.5 nm for Low-NA EUV and 193 nm for DUV.
In the second quarter of fiscal 2026, ASML reported 3.8 billion euros in EUV system sales compared to 2.8 billion euros in non-EUV system sales. All but one of those EUV system sales were Low-NA EUV. The High-NA unit that was sold went to Intel, which is now using High-NA for its most advanced products.
Investors need to understand that High-NA EUV adoption is still in the early stages. It took ASML a decade of research and development to crack the code on High-NA EUVs, with the first unit shipped to Intel in December 2023.
It's only been 13 months since SK Hynix (NASDAQ: SKHY) assembled the first High-NA EUV system for commercial chip production. The High-NA EUV system will help SK Hynix manufacture next-generation dynamic random access memory (DRAM) memory chips at scale in South Korea.
However, one challenge with High-NA is that its exposure field is half the size of Low-NA EUV's. It takes twice as many exposures to pattern a single wafer because High-NA optics are magnified much more than Low-NA optics. It's kind of like how high-resolution cameras use lenses to magnify a portion of an image but would need to stitch together different zoomed-in fragments on a single field for an ultra-precise picture.
ASML's solution is to operate High-NA at double the speed of Low-NA's wafer stage and quadruple the speed of Low-NA's reticle stage -- allowing passes to be completed much faster. But the full potential of High-NA is still effectively being held back.
But not for long. On Sept. 8, ASML and Taiwan Semiconductor announced a collaboration to transition from 6-inch photomasks to 12-inch photomasks to increase manufacturing efficiency and lower costs. By expanding the exposure field, 12-inch masks would allow complex chips to be printed in a single pass rather than stitched together -- thereby addressing the greatest drawback of High-NA compared to Low-NA.
ASML and Taiwan Semiconductor hope to establish a 12-inch mask pilot line by 2031, supporting advanced-node manufacturing by 2033. The transition to 12-inch masks unlocks the full efficiency benefits of High-NA and will give AI chip fabs even more incentive to install High-NA systems.
ASML is the best AI growth stock to buy in October because it is just beginning to reap the rewards of over a decade of research and development on High-NA. And switching to 12-inch photomasks allows High-NA to address the manufacturing demands of next-generation AI chips.
ASML already has a virtual monopoly on EUV, but staying ahead of the adoption curve ensures that it keeps its lead over the competition. This is precisely the kind of moat that long-term investors look for when building a growth stock investment thesis.
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Daniel Foelber has positions in ASML and Nvidia. The Motley Fool has positions in and recommends ASML, Applied Materials, Intel, KLA, Lam Research, Nvidia, and Taiwan Semiconductor Manufacturing. The Motley Fool has a disclosure policy.
Meet the Only AI Stock I'd Buy Over Nvidia in October was originally published by The Motley Fool
