As you outline for us, a major shift for this company that run it has. Thank you very much indeed for your time. You've gone from a company selling IP, selling the blueprints to your customers, to a company. Now, for the first time in its history, we'll be designing and making chips. It's a significant moment. How significant is it and why move in this direction?
Thank you, Tom. It is a very big day for ARM. There's no doubt about that. We've been an IP provider since we started. We started selling computer subsystems a few years ago, which was sort of the next step. But it's not a physical thing. But as we grew into the CCS business, we had customers that kept asking for more and more and more. And here we are today with Arm's first chip product is our Amagi CPU, which Mehta is our lead partner for, and better asked us to do it with them.
So we did talk to them about matter and the partnership that one one of your customers open eye also. Also a customer. What are the commitments from matter from Openai to take this chip on board? When do you start shipping?
So as Mohammed said, it's available now and we'll start shipping at the end of this year. We're not saying anything publicly about the volumes associated with it, but they are material enough that we have to start talking about the product because it's going to start showing up in our revenue this year.
The revenue start showing up this year. And in your presentation earlier here in San Francisco, you talked about potentially just this one revenue stream, just this one part of the business, potentially $100 billion by 2030. Talk us through how you get to that $100 billion.
So we're looking here then, Tom, at the general purpose CPU, TAM, which today in 2026 is about $60 billion, $70 billion depending on your math. I talked about a genetic grabbing a four CPU workload even today. So $60 billion going to $100 billion by the end of decade in terms of market opportunity. It's not really that much of a stretch.
How much of this is about that huge demand we're seeing, particularly here in Silicon Valley for Agenti? How much of this is aligned to that shift?
I think it's something key that's underpinning everything, and that's the demand for compute period. And compute has been perceived in AI about just generating tokens, but those tokens need to be distributed, managed, orchestrated, scheduled. That's all work that only CPUs can do. So the more and more compute that drive the genetic A.I. drive huge, huge CPU demand, which is great for the product we just announced today.
The other number that you announced was $1,000,000,000,000, and that's the entire business by 2030. You were a $4 billion revenue company in 2025, and you're looking at $1,000,000,000,000 potentially by 2030. Just unpack that for us. How do you get to $1,000,000,000,000 potentially by 2030?
Yeah. So what I showed there was a TAM total available market of $1,000,000,000,000 by the end of the decade. And I showed a picture that had some other DI photographs and things that we could do with the tagline We're not stopping here. So more to come. But today's all about the IQ.
What's to come? So you have the pipeline of CPU used, you move into GPU use. What else? What else is involved in more to come.
The compute demand for A.I. is off the charts and ARM is at the heart of literally every A.I. compute workloads. So we have a lot of different ways to go address that.
Can you give me some detail, right. In terms of revenues in the next 12 to 24 months coming from this product?
So we're going to talk to you about a little bit later. But the market potential for this product is game changing for the company. It puts us in a whole different zip code relative to the size and market we can address and the kind of revenues we can drive.
How does it come up? The cost of margins, the spend on R&D, is that the pain point potentially?
So one of the things to think about when you get into the chip business is the margin gross margin percentage may be less, but the gross margin dollars may be much, much larger. So if you think about let's use the TAM example, $3 Billion, TAM, 95% gross margin, you'd call that $2.8 billion. Take $100 billion TAM and apply a 50% gross margin. You're at $50 billion. So $50 billion of gross margin versus slightly under three. So percentage is less dollars, much, much, much more.
The critics might say the Hyperscalers are doing custom silicon. Jensen Huang talked about CPU use their own CPUs that maybe ARM is late to the game. Are you late on this?
No, I don't think we're late at all. And I think if you just look at what we've seen with the genetic A.I. and the fact that CPUs are being seen again as first class customers, it's a proof point that there is going to be huge demand for this product. And by the way, Tom, it's not just in the data center. As I talked about, ARM is the heart of physical A.I. or the heart of autonomous vehicles. We're at the heart of mobile phones, edge devices that fit inside your ear, wearables that all needs compute. In a very big way with AIG.
