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$ASML is upgrading EUV source power to 1,000W lifting throughput to ~330 wafers/hour. That’s a path to ~50% more chip output per tool by 2030.

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Shay Boloor

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78,607 Aufrufe • vor 5 Monaten •via X (Twitter)

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ASML unveiled an upgrade for the light source in its EUV process that increases power from 600W to 1,000W. This improvement could increase wafer yields by as much as 50% by 2030.
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ASML unveiled an upgrade for the light source in its EUV process that increases power from 600W to 1,000W. This improvement could increase wafer yields by as much as 50% by 2030.

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.Dylan Patel lays out how we know the hard upper bound on how much compute can be produced annually by 2030: around 200 GW/year. That’s a crazy number (there’s about 20 GW of AI deployed in the world right now), but it’s nowhere near enough to satisfy Sam/Elon/Dario/Demis’s ambitions. Lots of things in the supply chain can be scaled up over 4 years, including things that other people think are bottlenecks, like datacenter power or fab clean room space. But the thing that’s inflexible over that timeline is the number of EUV tools. Dylan forecasts that production of ASML’s EUV tools will scale from 60 per year now to about 100 per year by the end of the decade - which means something like 700 total machines running in 2030. For a fab to make a GW worth of the Rubin chips that NVIDIA is deploying later this year, it needs to make 55,000 3nm wafers, 6,000 5nm wafers, and 170,000 memory wafers. Each 3nm wafers needs about 20 EUV passes, so about 1.1 million passes per GW. Adding on 5nm and memory, you need two million passes. Each tool can do 75 passes per hour, so with 90% uptime that’s around 600k passes per year - so a single machine can make less than a third of a GW in a year. So in 2030, we have 700 total machines, each making 0.3ish GW a year, which means we can produce 200 GW of compute a year. That’s a lot. But Sam Altman wants a gigawatt a week by the end of the decade. Anthropic and Google will be wanting about the same. And Elon wants to be putting 100 GW in space every year. Any one of these players could maybe get what they need, but not all of them.
2:03

.Dylan Patel lays out how we know the hard upper bound on how much compute can be produced annually by 2030: around 200 GW/year. That’s a crazy number (there’s about 20 GW of AI deployed in the world right now), but it’s nowhere near enough to satisfy Sam/Elon/Dario/Demis’s ambitions. Lots of things in the supply chain can be scaled up over 4 years, including things that other people think are bottlenecks, like datacenter power or fab clean room space. But the thing that’s inflexible over that timeline is the number of EUV tools. Dylan forecasts that production of ASML’s EUV tools will scale from 60 per year now to about 100 per year by the end of the decade - which means something like 700 total machines running in 2030. For a fab to make a GW worth of the Rubin chips that NVIDIA is deploying later this year, it needs to make 55,000 3nm wafers, 6,000 5nm wafers, and 170,000 memory wafers. Each 3nm wafers needs about 20 EUV passes, so about 1.1 million passes per GW. Adding on 5nm and memory, you need two million passes. Each tool can do 75 passes per hour, so with 90% uptime that’s around 600k passes per year - so a single machine can make less than a third of a GW in a year. So in 2030, we have 700 total machines, each making 0.3ish GW a year, which means we can produce 200 GW of compute a year. That’s a lot. But Sam Altman wants a gigawatt a week by the end of the decade. Anthropic and Google will be wanting about the same. And Elon wants to be putting 100 GW in space every year. Any one of these players could maybe get what they need, but not all of them.

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$ASML is projecting ~$55B in revenue by 2030 with gross margins approaching 60%. That only works because every advanced chip built by $TSM and designed by $NVDA still has to pass through ASML’s tools. ASML remains the AI kingmaker.
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$ASML is projecting ~$55B in revenue by 2030 with gross margins approaching 60%. That only works because every advanced chip built by $TSM and designed by $NVDA still has to pass through ASML’s tools. ASML remains the AI kingmaker.

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🇺🇸 Elon: "Scaling civilization means to scale power in space." He ties it to building massive chip output, accelerating factories, and increasing power generation to support future AI demand. The idea: more energy → more compute → faster innovation → repeat at scale. Source: Elon Musk Tesla

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Here’s why $EUV is a $100 ETF… In order to make the next generation of chips even more intricate… ASML $ASML had to develop a way to generate a type of light that does not naturally occur on Earth’s surface called EUV… Extreme UltraViolet 10 Stocks to benefit from this bottleneck… 1) TSM $TSM 2) ASML $ASML 3) Lam Research $LRCX 4) Corning $GLW 5) Applied Materials $AMAT 6) Ciena $CIEN 7) Lumentum $LITE 8) KLA $KLAC 9) Coherent $COHR 10) MACOM $MTSI
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Here’s why $EUV is a $100 ETF… In order to make the next generation of chips even more intricate… ASML $ASML had to develop a way to generate a type of light that does not naturally occur on Earth’s surface called EUV… Extreme UltraViolet 10 Stocks to benefit from this bottleneck… 1) TSM $TSM 2) ASML $ASML 3) Lam Research $LRCX 4) Corning $GLW 5) Applied Materials $AMAT 6) Ciena $CIEN 7) Lumentum $LITE 8) KLA $KLAC 9) Coherent $COHR 10) MACOM $MTSI

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$ASML says it is already close to securing all the EUV orders needed for 2027 as memory lithography revenue surges 75% this year. The company is expanding Low-NA EUV capacity by 30% in 2027 to ~85 systems and is evaluating another 30% increase for 2028.
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$ASML says it is already close to securing all the EUV orders needed for 2027 as memory lithography revenue surges 75% this year. The company is expanding Low-NA EUV capacity by 30% in 2027 to ~85 systems and is evaluating another 30% increase for 2028.

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Elon Musk believes SpaceX can deploy 100 gigawatts per year by 2030 • 1 GW per year by end of 2027 • 10 GW per year in 2.5 years • 100 GW per year in 3.5 years “Depending on the progress in chip making, going beyond that to scale to a terawatt per year which is 1,000 gigawatts”
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ELON: TESLA FUTURE'S HINGES ON THE AI5 CHIP PROJECT "The AI5 chip, which is going to be a great chip, all of Tesla hinges on that chip. That's the chip that is going into our next generation of self-driving cars, and it's also essential for the Optimus robot. So that chip program was in bad shape. It wasn't closing because it's quite an ambitious chip design, and it really wasn't on a path to success. And then we also had the Dojo program, which was doing okay but not on a path to be competitive with NVIDIA. So I collapsed the two programs into just one program, which is to get everyone focused on the AI5 chip, which is essential. Continue to use NVIDIA for training, but we need the AI5 inference chip, which is a very powerful chip, but it's also a very low-power chip. So it doesn't use a lot of power. Its performance per watt is extremely good. I think it's probably going to be at least 2 to 4 times better than NVIDIA performance per watt at the inference level in the car and the robot. And I don't know, 10% of the cost of an NVIDIA chip, something like that. So these are very important numbers to achieve." Source: Elon Musk, Baron Capital, Ron Baron, Tesla
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ELON: TESLA FUTURE'S HINGES ON THE AI5 CHIP PROJECT "The AI5 chip, which is going to be a great chip, all of Tesla hinges on that chip. That's the chip that is going into our next generation of self-driving cars, and it's also essential for the Optimus robot. So that chip program was in bad shape. It wasn't closing because it's quite an ambitious chip design, and it really wasn't on a path to success. And then we also had the Dojo program, which was doing okay but not on a path to be competitive with NVIDIA. So I collapsed the two programs into just one program, which is to get everyone focused on the AI5 chip, which is essential. Continue to use NVIDIA for training, but we need the AI5 inference chip, which is a very powerful chip, but it's also a very low-power chip. So it doesn't use a lot of power. Its performance per watt is extremely good. I think it's probably going to be at least 2 to 4 times better than NVIDIA performance per watt at the inference level in the car and the robot. And I don't know, 10% of the cost of an NVIDIA chip, something like that. So these are very important numbers to achieve." Source: Elon Musk, Baron Capital, Ron Baron, Tesla

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ASML's EUV machine is one of the most complex machines ever built by humanity. Some *insane* stats about it: → Without EUV machines, it's impossible to manufacture cutting-edge chips for things like $AAPL iPhones, $NVDA GPUs, and $AMZN data centers. → $ASML is the *only* producers of EUV machines in the world. → Shipping a single EUV machine requires 40 freight containers, three cargo planes, and 20 trucks. → Each EUV machine costs around $200M, consists of more than 100,000 parts and weighs 200 tonnes. → The mirrors inside (supplied by Zeiss) are said to be the flattest objects ever produced. If scaled up to the size of Germany, the largest unevenness would be a tenth of a millimeter. → The next generation High-NA EUV systems have been shipped to $INTC and $TSM and costs closer to $400M. This is human ingenuity at its best. Thanks Intel for the fab tour!
4:19

ASML's EUV machine is one of the most complex machines ever built by humanity. Some *insane* stats about it: → Without EUV machines, it's impossible to manufacture cutting-edge chips for things like $AAPL iPhones, $NVDA GPUs, and $AMZN data centers. → $ASML is the *only* producers of EUV machines in the world. → Shipping a single EUV machine requires 40 freight containers, three cargo planes, and 20 trucks. → Each EUV machine costs around $200M, consists of more than 100,000 parts and weighs 200 tonnes. → The mirrors inside (supplied by Zeiss) are said to be the flattest objects ever produced. If scaled up to the size of Germany, the largest unevenness would be a tenth of a millimeter. → The next generation High-NA EUV systems have been shipped to $INTC and $TSM and costs closer to $400M. This is human ingenuity at its best. Thanks Intel for the fab tour!

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Here are 20 companies that will dominate the AI age: 1/ ASML $ASML is revolutionizing the semiconductor industry by enabling chipmakers to produce the world’s most advanced processors with atomic-scale precision. Shrinking transistors to fit more power into smaller chips faces fundamental physical limits. The industry struggled with escalating costs, slower innovation cycles, and diminishing returns from older lithography methods. With $ASML, the process is radically different, its extreme ultraviolet (EUV) lithography machines use cutting-edge optics and physics to etch circuitry at the nanometer scale, enabling faster, more energy-efficient, and more powerful chips. This breakthrough is the backbone of progress in AI, cloud computing, smartphones, and virtually every advanced technology. As AI spreads to all aspects of our economies, an ever-growing number of chips is needed, driving demand for ASML machines and maintenance services.
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Here are 20 companies that will dominate the AI age: 1/ ASML $ASML is revolutionizing the semiconductor industry by enabling chipmakers to produce the world’s most advanced processors with atomic-scale precision. Shrinking transistors to fit more power into smaller chips faces fundamental physical limits. The industry struggled with escalating costs, slower innovation cycles, and diminishing returns from older lithography methods. With $ASML, the process is radically different, its extreme ultraviolet (EUV) lithography machines use cutting-edge optics and physics to etch circuitry at the nanometer scale, enabling faster, more energy-efficient, and more powerful chips. This breakthrough is the backbone of progress in AI, cloud computing, smartphones, and virtually every advanced technology. As AI spreads to all aspects of our economies, an ever-growing number of chips is needed, driving demand for ASML machines and maintenance services.

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ELON MUSK: "The AI 5 chip which is going to be a great chip. All of Tesla hinges on that chip. That's the chip that going to our next gen self driving cars and it's also essential for Optimus. So that chip program was in bad shape. It wasn't on the path to success and we also had the DOJO program which was also doing okay but not on a path to be competitive with NVIDIA. So I collapsed the two programs into just one program to get everyone focused on the AI5 chip. It's performance per watt is extremely good. It is probably going to be at least 2-3 times better than NVIDIA performance per watt and 10% cost of the NVIDIA chip something like that."
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ELON MUSK: "The AI 5 chip which is going to be a great chip. All of Tesla hinges on that chip. That's the chip that going to our next gen self driving cars and it's also essential for Optimus. So that chip program was in bad shape. It wasn't on the path to success and we also had the DOJO program which was also doing okay but not on a path to be competitive with NVIDIA. So I collapsed the two programs into just one program to get everyone focused on the AI5 chip. It's performance per watt is extremely good. It is probably going to be at least 2-3 times better than NVIDIA performance per watt and 10% cost of the NVIDIA chip something like that."

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