“Our assumption for any new Galaxy is always going to be 75%. That's our assumption for Galaxy S26.”

In context

“we have this trend that is very healthy, and the premium tier is expanding and is adding more compute. That is the reason why our Android business, even on a market that is relatively flat, which is the handset market. We continue to grow our content, ASPs and earnings because we see premium tier expanding. A lot of the upside we have in the handsets is primarily driven by the Android premium tier. Second part is our relationship with Samsung. We have said for a number of years -- a number of reasons, and this has been true in the past, I think, several years that what used to be a normal relationship at a 50% share, the new baseline is about 75% share. And that is always going to be our financial assumption. When we out-execute, sometimes we get more than 75%, on Galaxy S25, we got 100%. Our assumption for any new Galaxy is always going to be 75%. That's our assumption for Galaxy S26. Operator: The next question comes from the line of Samik Chatterjee with JPMorgan. Samik Chatterjee: Cristiano, you mentioned the -- on the data center side, starting with that, you mentioned the price performance for the inferencing performance that you're trying to deliver. I mean most of the training clusters that we've sort of seen the other incumbents sort of talk about the ranges of installation cost is somewhere in the sort of $30 billion, $40 billion per gigawatt that we're hearing of. Can you just right size us in terms of when you're thinking about the deployment on a gigawatt basis, what kind of cost performance or price performance are you thinking of relative to these inferencing workloads that you can support on the AI 200 or AI 250? And I'm also trying to get to sort of wha”