AI is the main use case for memory bandwidth that I know of. Local LLM’s are memory bandwidth limited when running inference, so once you fall into that trap yo

AI is the main use case for memory bandwidth that I know of. Local LLM’s are memory bandwidth limited when running inference, so once you fall into that trap you end up wanting the 400 gb/s max memory bandwidth of the m1/m2/m3 max, paired with lots and lots of RAM. Apple pairs memory size and bandwidth upgrades to core counts a lot more in m3 which makes the m3 line-up far more expensive than the m2 line-up to reach comparable LLM performance. Them touting AI as a use case for the m3 line-up in the keynote was decidedly odd, as this generation is a step back when it comes to price vs performance.