Hello, we have trouble with summation errors (differences) in the computation of an average pooling layer of a CNN by means of CoreML and on a M1 device with Big Sur. For several consecutive runs we get different results. This happens on GPU, CPU and with the Neural Engine (AI cores). So it's not only restricted to one computation method. The results are not stable. In contrast to this, the results on an Apple Intel device running Big Sur are stable. There we get always the same constant result. We build an easy CNN toy example, that allows for reproducing this effect on a M1 device and that we can provide. Since we wanna provide our photo management software Excire Foto for M1 devices as fast as possible, we really appreciate to find a quick solution for this numerical problem. So please help us. Best regards, your Excire Team