Max 16k images for Image Classifier training????

I'm hitting a limit when trying to train an Image Classifier. It's at about 16k images (in line with the error info) - and it gives the error:

IOSurface creation failed: e00002be parentID: 00000000 properties: {
    IOSurfaceAllocSize = 529984;
    IOSurfaceBytesPerElement = 4;
    IOSurfaceBytesPerRow = 1472;
    IOSurfaceElementHeight = 1;
    IOSurfaceElementWidth = 1;
    IOSurfaceHeight = 360;
    IOSurfaceName = CoreVideo;
    IOSurfaceOffset = 0;
    IOSurfacePixelFormat = 1111970369;
    IOSurfacePlaneComponentBitDepths =     (
        8,
        8,
        8,
        8
    );
    IOSurfacePlaneComponentNames =     (
        4,
        3,
        2,
        1
    );
    IOSurfacePlaneComponentRanges =     (
        1,
        1,
        1,
        1
    );
    IOSurfacePurgeWhenNotInUse = 1;
    IOSurfaceSubsampling = 1;
    IOSurfaceWidth = 360;
} (likely per client IOSurface limit of 16384 reached)

I feel like I was able to use more images than this before upgrading to Sonoma - but I don't have the receipts....

Is there a way around this? I have oodles of spare memory on my machine - it's using about 16gb of 64 when it crashes...

code to create the model is

        let parameters =  MLImageClassifier.ModelParameters(validation: .dataSource(validationDataSource),
                                                            maxIterations: 25,
            augmentation: [],
            algorithm: .transferLearning(
                featureExtractor: .scenePrint(revision: 2),
                classifier: .logisticRegressor
            ))

        let model = try MLImageClassifier(trainingData: .labeledDirectories(at: trainingDir.url), parameters: parameters)

I have also tried the same training source in CreateML, it runs through 'extracting features', and crashes at about 16k images processed.

Thank you