TSMC stock rises 51% in 2026 as AI chip demand boosts revenue and production. - Pluang

Skyler Monroe (0:10)

Hey everyone, welcome back to The AI Hardware Show. I'm your host Skyler Monroe, and if you're into the chips, the silicon, the data center tech powering the AI revolution, you are absolutely in the right place. Before we dive in, a huge thank you to our sponsors, Ada, helping businesses integrate AI seamlessly into their workflows. Ago Consulting, that's Ago, your go-to for silicon development consulting from AI to so, and Zen Semiconductor, the umbrella powering a whole portfolio of silicon industry ventures from their Sierra RISC vCPUs to the Loom AI fabric, plus Ada for deploying AI at scale in any business. All right, we've got a loaded episode today. We're talking TSMC's incredible stock run, Nvidia Price Hike's OpenAI's new custom chip called Jalapeño, a fascinating Korea-based robotics chip story, and Meta quietly rewriting the economics of AI silicon. Let's get into it. Okay, first up, TSMC, Taiwan Semiconductor Manufacturing Company. If you follow this space at all, you know this name. They are the foundry. The place where the world's most important chips get made, Nvidia's GPS, Apple's Aseries, AMD's processors, nearly all of it runs through TSMC's fabs. And in 2026, their stock has surged 51%.

That is not a typo, 51%.

Now, what's driving that? Simple answer, AI chip demand is absolutely through the roof, and it's not slowing down. Every hyperscaler, every cloud provider, every startup trying to train a model or run inference at scale needs chips. And most of those chips get made at TSMC. So when AI spending goes up, TSMC wins. Full stop, think of TSMC like the world's most sophisticated chip kitchen. All these tech companies, Nvidia, AMD, Google, Apple, OpenAI, they come in with their chip recipes, their designs, and TSMC bakes them. They don't compete with their customers on chip design. They just make the chips better and faster than anyone else on the planet. That's their whole game. And right now demand for what's coming out of that kitchen is insane.

Revenue is up, production is ramping, and TSMC has been investing heavily in advanced nodes. We're talking 3 nanometer, 2 nanometer, the bleeding edge of what's physically possible in semiconductor manufacturing.

These advanced nodes are exactly what AI accelerators need to pack more transistors, run more efficiently, and hit those performance targets that model training demands.

What's also really interesting here is the geopolitical layer. There's been so much conversation about supply chain risk, about Taiwan's position in the global chip economy, and yet money keeps flowing into TSMC because there is simply no realistic alternative at this scale and this capability level.

Intel's trying, Samsung's trying, but TSMC still holds the crown. And that 51% stock rise, that's investors essentially saying they believe AI infrastructure spending is not a blip. It's a sustained multi-year build out. Data centers need chips, chips need fabs, fabs need TSMC. It's a pretty clean supply chain story, and right now, TSMC is sitting at the very beginning of it, collecting a toll on every major AI chip that ships.

The broader takeaway here is that foundry capacity is becoming a strategic national and corporate asset. We're seeing governments subsidize domestic chip manufacturing, the chips act in the US, similar programs in Europe and Japan, precisely because everyone has realized that whoever controls the fabs controls the future. TSMC knows this. Their shareholders clearly know this. And a 51% run in one year is the market putting a very loud exclamation point on that thesis. All right, story number two. And this one is going to sting a little if you're a company buying Nvidia hardware. According to reporting from the information, Nvidia AI chip prices are set to rise by about 17%.

And we're hearing this from server makers who are already passing that message along to their customers. So this isn't rumor, it's happening at the supply chain level. Now, 17% sounds like a number, but let's put it in context. We're talking about chips that are already extraordinarily expensive. An H100 GPU was running somewhere in the range of $30,000 to $40,000 per unit at various points. A Blackwell B200 is even pricier.

A one 17% increase on top of that is tens of thousands of dollars per chip. And when you're buying these things by the rack, by the cluster, by the thousands, that math gets brutal very fast. So why is Nvidia raising prices? The short answer is because they can. Demand has not softened. If anything, the queue to get Nvidia hardware is still long, and companies are still paying up because the alternative, not having the compute, is worse. Nvidia has pricing power right now that is genuinely remarkable. It's the kind of leverage you get when you're selling something people consider mission critical and there's not enough supply to go around. But here's where it gets strategically interesting. Price hikes like this are exactly the kind of thing that accelerates the custom silicon movement. Every time Nvidia raises prices, the ROI calculation for building your own chip shifts. If you're a hyperscaler spending hundreds of millions of dollars a year on Nvidia GPS, a 17% increase is not a rounding error. That's a massive delta that starts making internal chip programs look a lot more attractive. Think about it like this. If you're renting office space and your landlord keeps raising rent, at some point you start seriously considering whether it makes more sense to just buy the building. That's essentially what Google did with TPS, what Amazon did with Tranium and Inferentia, and what we'll talk about in a minute with OpenAI and Meta. Nvidia's pricing is ironically funding the motivation for its own competition. Now, to be fair to Nvidia, their chips are genuinely best in class. The software ecosystem, CUDA, is deep, mature, and sticky. You don't just swap out Nvidia and plug in something else without real engineering pain. That software moat is arguably as valuable as the hardware itself, and it's a huge reason why companies keep paying up even when the price goes up. But 17% is significant. And if this becomes a trend, if prices keep creeping up cycle after cycle, we're going to see more and more workloads migrate to custom silicon, to AMD, to whatever alternatives get mature enough to handle production inference at scale. The competitive pressure is building, even if Nvidia's position today looks unassailable. Watch this space closely. All right, story three, and this one is genuinely exciting from a pure silicon nerd perspective.