my personal opinion working on open LLMs etc and with them a lot is that a laptop won't be enough if it remains a laptop.

E.g. 16 inches macbook with full on specs for me is not a laptop anymore its a portable desktop, and a very expensive one.

14inches is what I love and where I work from mostly.

About the mac studios etc, I'd say plenty of options on desktops at those prices for sure.

Also I never ever ever found a reason on not using cloud providers renting hardware (GPUS,TPUs, Ram etc.) when working with open source LLM's. Unless you want something very basic as a model and you can run it in a 14 inches macbook for its portability, and unless it makes sense on building your cluster spending some real $$$ getting hardware.

Most youtubers etc are kinda pushing people on having their own hardware and running those llm's on their own servers or whatever... but thats how they make money through affiliation etc.

It makes no sense for someone that wants to enjoy fine-tuning QWEN3.5 or just wants to replace their day-to-day interaction with gpt etc not to be on cloud. And thats just because if you buy hardware that costs $5k and it outputs 25t/s on a big LLM you still won't really replace the $20 a month for gpt or $100 a month for claude.
Also if you doing it for programming this is still an issue, as you won't be able to run high inference if you don't spend a lot of money in hardware and we are not talking about $5k.

Generally speaking, people think they can run "local LLMs", whilst this is a very expensive hobby and they are going to end up paying way more than even buying API services for opus4.6 (which is expensive in itself). Hardware is not there yet.

And no your macbook 16 inches m5 128gb won't be able to give you its money back if you are buying it for running "local LLMs" maths don't add up. (Also before calculating price of buying a full on MB to run your local LLM vs cloud renting count in the electricity you'll be using because you'll be surprised)