The real limit is on the Nvidia cards. They are cut down a fair bit, often with less VRAM until you really go up in price point.
They also come with NPUs but the docs are bad and none of the local LLM inference engines seem to use the NPU, even though they could in theory be happy running smaller models.
Even M1 MBP 32GB performance is pretty impressive for its age and you can get them for well <$1K second hand.
I have one.
I use these models: gpt-oss, llama3.2, deepseek, granite3.3
They all work fine and speed is not an issue. The recent Ollama app means I can have document/image processing with the LLM as well.
I take my laptop back and forth from home to work. At work, I ban them from in-person meetings because I want people to actually pay attention to the meeting. In both locations where I use the computer, I have a monitor, keyboard, and mouse I'm plugging in via a dock. That makes the built-in battery and I/O redundant. I think I would rather have a lower-powered, high-battery, ultra portable laptop remoting into the desktop for the few times I bring my computer to in-person meetings for demos.
I wish the memory bandwidth for eGPUs was better.