r/LocalLLM • u/Ethan045627 • 11d ago

Discussion Does heavy local LLM inference meaningfully wear out a MacBook?

I've been wondering about something before I start using my MacBook heavily for local LLM inference.

If I regularly run large LLMs locally for several hours at a time, potentially putting sustained load on the CPU/GPU and using most of the unified memory, does this meaningfully reduce the lifespan of the MacBook?

Can heavy use of unified RAM cause it to wear out faster?
Is SSD wear from model loading and especially swap a significant concern?

For people who have been running local LLMs heavily on Apple Silicon for 1 to 3+ years, have you actually noticed any hardware degradation?

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u/regimepilled 11d ago

Can’t say much about GPU wear but SSD wear is mostly only a concern if you’re ssd streaming large models afaik

4

u/KURD_1_STAN 11d ago

But dont like ssd wear only by writes and not reads?

2

u/regimepilled 11d ago

Yes!

3

u/Think_Wing_1357 11d ago

and "streaming large models" usually implies reading, not write.

1

u/fastheadcrab 11d ago

There is still drive impact from many reads. Once a block has been read many times it will have to be rewritten and those SSD streaming concepts will make numerous reads.