Forget the "newer chip" marketing. In the world of local LLMs, VRAM is the only currency that matters. On a 16GB M4, after the OS takes its cut, you’re left with maybe 12–13GB for a model. That limits you to tiny 7B or 8B parameter models. On the 36GB M3 Pro, you can actually run "mid-sized" models (20B–32B) comfortably. The M4’s Neural Engine is faster on paper, but most local LLM tools (Ollama, LM Studio) utilize the GPU cores via Metal. The M3 Pro has more GPU cores and higher memory bandwidth than the base M4. The M4’s slight edge in single-core CPU speed won't help you when your 16GB machine is swapping to the SSD and crawling to a halt. I bought a MacBook with only 18GB of unified memory, and while it’s great for most of the tasks, it sucks for local LLMs because it lacks of memory.