MacBook Pro buyers weigh local LLM speed

The useful takeaway is that RAM is not the whole story on Apple Silicon; capacity decides if a model loads, but bandwidth decides if it runs like a tool or like wet cement.

• –Apple’s own M5 specs back the community’s instinct here: the M5 Pro tops out at 307GB/s bandwidth, while the 40-core M5 Max reaches 614GB/s, which is the kind of jump that should show up directly in prompt processing and tokens per second.
• –The Reddit consensus is that CPU is mostly secondary for inference if the workload stays on the GPU and shared memory, though it matters more once layers spill to CPU or you are doing heavier preprocessing around the model.
• –Apple is explicitly pitching the new MacBook Pro for local AI workloads, claiming much faster LLM prompt processing on M5-class machines, which gives the thread’s “bandwidth first” argument some official support.
• –Independent research on Apple Silicon runtimes points the same direction: Macs are increasingly viable for private, on-device LLM use, but they still trail NVIDIA boxes on absolute throughput, so the premium only makes sense if you also want a high-end daily-driver laptop.
• –The practical buyer logic is simple: 64GB gets you into serious local-model territory, but the Max chip is the one that meaningfully improves experience rather than just eligibility.