[zamadatix]

I get where GP is coming from and it's not really related to typical Apple price bashing. You can list the most fantastical specs for the craziest value and it all really comes down to that single note: "64 GB memory for the GPU/NPU" - where the mini caps out. The GPU/NPU might change the speed of the output by a linear factor but the memory is a hard wall of how good a model you can run and 64 GB total is surprisingly not that high in the AI world. The MacBook Pro units referenced at $5k are the ones that support 128 GB, hence why they are popularly mentioned. ~ the same $ for the Mac Studio when you minimally load it up to 128 GB. Even then you're not able to run the biggest local models, 128 GB still isn't enough, but you can at least run the mid sized ones unquantized.

What I think GP was overlooking is newer mid range models like Qwen2.5-Coder 32B produce more than usable outputs for this kind of scenario on much lower end consumer (instead of prosumer) hardware so you don't need to go looking for the high memory stuff to do this kind of task locally, even if you may need the high memory stuff for serious AI workloads or AI training.