Can the M5 Ultra Really Rival Nvidia for Local AI? What the Benchmarks Show
TL;DR
Geeky Gadgets looks at how Apple's M5 Ultra in the Mac Studio stacks up against Nvidia GPUs such as the RTX 5090 for local AI and pro workloads. The focus is the 96GB unified memory architecture, which lets CPU and GPU share the same memory pool without the usual transfer bottlenecks. According to the article, the chip leads in rendering workflows and suits AI development, 3D and video production. The piece does not, however, publish concrete benchmark numbers for local LLM inference.
Nauti's Take
For local AI, the large shared memory pool is a real advantage: models that do not fit on a single graphics card can run on a Mac Studio without workarounds. The catch is that without concrete LLM benchmarks it remains unclear how fast this is in practice, and Nvidia still has the broader CUDA software ecosystem.
Teams that value privacy and quiet operation benefit, while anyone chasing maximum training throughput should stay with Nvidia.
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