M2 Ultra can run 128 streams of Llama 2 7B in parallel
For those wondering why the M2 Ultra is so fast, or the M1 &amp; M2 series in general, it&#x27;s because inference&#x27;s main bottleneck is memory bandwidth, not compute power. And the M2 Ultra has a bandwidth of 800 GB&#x2F;s which is about 8 times faster than an average modern desktop CPU (dual-channel DDR4-6400 offers a bandwidth of 102 GB&#x2F;s).<p>This high bandwidth is really a result of Apple having designed a unified memory architecture for the M1 and M2 chips. Typically on a laptop or desktop, the CPU and GPU have distinct memory systems: high-bandwidth (but relatively low-capacity) graphics memory, and relatively low-bandwidth (but high-capacity) CPU memory. Apple decided to simplify that and instead implemented a single high-bandwidth memory system shared by the CPU and GPU. The only downside is that such high-bandwidth memory had to be tightly integrated in the M2 package, so the maximum capacity is limited. For example whether you spend 5,600 USD (cheapest Mac Studio machine with M2 Utra and 192 GB) or $10k+ (maxed out Mac Pro), you will only ever get 192 GB RAM max. For that amount, a PC could get 1024 GB RAM (5× more!) But on the other hand, if your workload, like inference, doesn&#x27;t need more than 192 GB, then that&#x27;s great. Personally I think Apple made the right tradeoff here. 800 GB&#x2F;s of memory bandwidth on a general purpose CPU, on a single socket, has never been done before (to my knowledge.)