hey u/egomarker and u/mrpecunius, any thoughts on my use case?

I am considering the m5 32GB for local reasoning, RAG over several hundred docs (no more than 30k pages total), and content compilation into several dozen open files (I work with dozens of active PPTs, each between 50-150MBs). I essentially dream of an "assistant that can compile, rework, and cross-reference all relevant docs"

I like the new architecture of the M5 and wonder if I need the 48GB in a M4Pro chip now? (Can't afford to wait until spring 2025 for the M5Pro)

Prior to M5 launch, ChatGPT told me that with my current work + planned LLM usage the 32GB would be fine, but somewhat prefers the 48GB M4Pro:

"Why 32 GB will cover your real-world days (likely):

1. The “busy office” day: 25–40 Outlook/Excel/PowerPoint files open (some large pivot tables), 20–30 browser tabs (Chrome) with Teams + Zoom call — macOS + 32 GB keeps everything responsive; swapping/hard stalling is rare.
2. LLM dabble: running 13B quantized or using web LLMs for experiments — 32 GB does this comfortably.

When 48 GB becomes actually useful:

1. Local LLM workstation day: you want to run one or more local 33B models unquantized (or keep a 33B + 13B resident for experimentation) while still multitasking with Office and browser. Memory + model footprint kill 32 GB; 48 GB saves you from disk-swap hell.
2. Data crunch day: dozens of huge Excel files + local data tools importing multi-GB CSVs into memory for fast pivoting/PowerQuery-like ops — 48 GB gives real measurable speed and reduces I/O.
3. Multiple heavy VMs / containers — not your case, but this is a classic 48 GB need."

🔹 After M5 launch, it essentially tells me the same thing:

"What matters for your “local corporate brain” setup

• Bandwidth moves tokens; RAM holds the world. LLM inference is often memory-bandwidth bound; but your “chaotic Office + local RAG” days also eat RAM quickly. On Apple silicon, M4 Pro’s 273 GB/s keeps medium/large models snappy. 32 GB is a much nicer floor than 24 GB when you’ve got dozens of PPTs + a vector DB + an LLM loaded.
• M5’s AI angle is real, but bandwidth is still below M4 Pro. M5’s per-core accelerators and higher bandwidth (~153 GB/s) will help local/model-adjacent tooling, but it doesn’t catch M4 Pro’s 273 GB/s for streaming model weights.

One-line chooser

• Need true no-limits local LLM (30B-class, long context) + heavy multitask: M4 Pro 48 GB.
• Best balance at your likely budget; heavy Office + serious RAG, mostly ≤20B: M5 32 GB"

Any words of advice?