Hello, I noticed a substantial decrease in performance compared to previous releases of tensorflow for M1 Macs. I previously installed the alpha release of tensorflow for M1 from GitHub, found here: https://github.com/apple/tensorflow_macos and was very impressed by the performance. I used the following script to benchmark my M1 Mac and other systems: https://gist.github.com/tampapath/662aca8cd0ef6790ade1bf3c23fe611a#file-fashin_mnist-py Running the alpha release from GitHub, my M1 Mac handsomely outperformed both google colab's random GPU offerings and an RTX 2070 windows computer. Recently, I went back to the GitHub repository, looking for new updates on tensorflow support for the M1 and was redirected here to the tensorflow-metal PluggableDevices installation guide: https://developer.apple.com/metal/tensorflow-plugin/ After installing the conda environment and running the same benchmark script, I realized my M1 systems's was running much slower. Additionally, the following error messages printed to the console while running the benchmark: 2021-08-12 21:48:16.306946: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:305] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support. 2021-08-12 21:48:16.307209: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:271] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical PluggableDevice (device: 0, name: METAL, pci bus id: <undefined>) 2021-08-12 21:48:16.437942: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:176] None of the MLIR Optimization Passes are enabled (registered 2) 2021-08-12 21:48:16.441196: W tensorflow/core/platform/profile_utils/cpu_utils.cc:128] Failed to get CPU frequency: 0 Hz Has anyone else noticed this loss in performance? The results I got are as follow: benchmark script duration tf GitHub alpha 🟢 9.62s new tf-metal 🔴 76.52s google colab 🔴 57.53s RTX 2070 PC 🔴 23.18s both tf GitHub alpha and new tf-metal were ran on the same 13" M1 MacBook Pro. I wrote an installation guide for the GitHub alpha release if anyone wants to compare results, or run a faster version of tensorflow compatible with their M1 Mac: https://github.com/apple/tensorflow_macos/issues/215