Well, I finally got it to install. I'm not sure what made it work, but I did some things: Removed Python 3.12 and install 3.11.9 Added parameters to .condarc file: channels: - apple - conda-forge - defaults subdirs: - osx-arm64 - osx-64 - noarch Reran the 3 steps above. Note that the tensorflow_deps still threw an error but the rest worked! Reran the config test below, which now shows GPU present! >>> tf.__version__ '2.16.1' >>> tf.config.list_physical_devices() [PhysicalDevice(name='/physical_device:CPU:0', device_type='CPU'), PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]

Thanks for these replies! I'll try them both today or tomorrow. I was able to get a fresh install to work on a different MacBook Air M2. Although simple tf/keras/gpu test scripts required several edits to even run and display versions and available devices! I've seen a comment on yt that the reason I can't find answers is because M3 users likely prefer the apple mlx libraries over tensorflow due to unified memory support. Thoughts?

Also note following version info: Macos 14.4.1, ARM64 tf.version = 2.16.1 python=3.9 Although I've tried python 3.12, 3.10, 3.8.