[D] How's MLX and jax/ pytorch on MacBooks these days?

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So I'm looking at buying a new 14 inch MacBook pro with m5 pro and 64 gb of memory vs m4 max with same specs.

My priorities are pro software development including running multiple VMs and agents and containers, and playing around with local LLMs, maybe fine-tuning and also training regular old machine learning models.

it seems like I'd go for the m4 max because of the extra GPU cores, way higher bandwidth, only marginal difference in CPU performance etc but I'm wondering about the neural accelerator stuff.

However, I'm posting here to get some insight on whether it's even feasible to do GPU accelerated machine learning, DL etc on these machines at all, or if I should just focus on CPU and memory. how's mlx, jax, pytorch etc for training these days? Do these matmul neural engines on the m5 help?

Would appreciate any insights on this and if anyone has personal experience. thanks!