From direct exp Mac m1 and m2 air and mini run 7b quantized models ok but barely, they prefer 3b like orca mini. So your goal for running a 30b quantized is realistic, but only for inference and I would use ollama or other model servers that run as api's and then run your interface client separately, strealit, chainl et al. From a devs standpoint I prefer mac's just bec the Linux core in macos. My experience with pc laptop nvidia gpu's for inference isn't great. If you want plug it and go setup I rec mb. Dealing with c compliers is a pia in windows which includes llama.cpp, solidity and various others.
Training or fine tuning on any consumer level hw isn't practical to me unless it's a million param model.
From direct exp Mac m1 and m2 air and mini run 7b quantized models ok but barely, they prefer 3b like orca mini. So your goal for running a 30b quantized is realistic, but only for inference and I would use ollama or other model servers that run as api's and then run your interface client separately, strealit, chainl et al. From a devs standpoint I prefer mac's just bec the Linux core in macos. My experience with pc laptop nvidia gpu's for inference isn't great. If you want plug it and go setup I rec mb. Dealing with c compliers is a pia in windows which includes llama.cpp, solidity and various others. Training or fine tuning on any consumer level hw isn't practical to me unless it's a million param model.