Apple’s M5 Ultra Mac Studio is creating an interesting alternative to the traditional NVIDIA approach to local AI.
The important difference isn’t simply processor speed.
It’s the amount of memory Apple can put into a single desktop system and how that memory is shared across the machine.
In this video, we compare the M5 Ultra approach with NVIDIA’s RTX PRO 6000 Blackwell and explore:
256GB unified memory
1.2 TB/s memory bandwidth
96GB GPU memory on the RTX PRO 6000 Blackwell
Why memory capacity matters for large AI models
Where NVIDIA still has major advantages
Why local AI hardware is becoming more competitive
Apple doesn’t need to beat NVIDIA at every AI workload to be relevant.
It simply needs to give certain users a compelling way to run large AI models locally.
And that could make the next hardware battle much bigger than GPU performance alone.
