A $1,000 used GPU ties the $9,499 Mac Studio at the benchmark everyone runs

The short answer

For models that fit in 24GB, an NVIDIA build wins on speed and costs a fraction of a Mac Studio — a used RTX 3090 measures within ~5% of an M3 Ultra on 7-8B-class generation (llama.cpp, Q4). The…

Buy NVIDIA if your models fit in 24–32GB: faster prompt processing (a 3090 does 2,572 t/s vs the M3 Ultra's 1,471 on the same 7B class), CUDA for fine-tuning and image gen, and upgradeability.

Buy the Mac for big-model capacity per box: a 512GB M3 Ultra runs DeepSeek R1 671B at Q4 around 17–18 t/s entirely in memory — with a documented weakness: prompt processing on huge contexts can take…

Price parity is brutal at the small end: ~$1,000 (used 3090) vs $1,999–9,499 (Mac Studio). It inverts at the top — matching 512GB of NVIDIA VRAM costs multiples of the Mac, if you can even build it.

Power is real money in Europe: a GPU tower under sustained load draws roughly 350–450W more than a Mac Studio, about €25/month at €0.30/kWh if it runs 8 hours a day.

Different questions, different winners

If your models fit in 24–32GB — and for most people getting into local AI, they do — the NVIDIA build is faster where it counts, half the price, and lives in the CUDA ecosystem where every tool…