I can confirm what @ihomway says: it works after a reboot. 👍

It's still not working. Do we need to remove the previous toolchain download somehow?

But shouldn't the stack trace be longer in this case?

When you call CIRAWFilter(imageURL: rawURL, options: [:]) you are calling the old, deprecated CIFilter RAW API. What happens if you just use CIRAWFilter(imageURL: rawURL) (the actual initializer of CIRAWFilter)?

How does the crash look like? Where does it crash? Do you have a crash log?

Deferred here means that it's doing the bulk of the work later, but gives you something you can use and show the user quickly. So you can quickly show a preview of the capture (the 12 MP image) and a few seconds later update it with the fully processed 48 MP image. Since you want to use CIRawFilter, I'm afraid you have to wait for the full image to arrive before you can present the user with editing controls. But you can use the smaller image to bridge the UI transition.

All I did was to set the system & Siri language to English (US) and log in with a US sandbox account under Media & Purchases. Then I could enable Apple Intelligence on my iPad in Germany.

What device did you test on? The trick only works on iPad, not on iPhone and also not on the Simulator (not even in supported countries). It also has to be an iPad that supports Apple Intelligence (M1 or newer).

Tested with macOS 15.2 RC 2.

On iOS, there is a watch dog that kills processes on the GPU that run too long. I don't think there is much you can do to change the timing limit. The only way to prevent that is to improve the runtime of your algorithm. You could also try splitting up the work into multiple steps, if possible. E.g., by splitting up the images into regions and performing the regression on the regions first, and then once more on the results of step one.

Thanks for the reply! I already filed FB14074014 for this. I also attached a small sample project now.

Did you already file Feedback for this issue?

Do you have any advanced tips setup? How are you calling Tips.configure()?

Via a private property on MLModelConfiguration: config.setValue(1, forKey: "experimentalMLE5EngineUsage") (1 = disabled, 0 = enabled if possible, 2 = force).

Very strange indeed. The workaround works, thanks!