DGX Spark vs Mac Studio (2026): two ways to run local AI — bandwidth, price, watts

Our Recommendation

You run one big model and want the highest decode speed per euro → DGX Spark: a single Spark runs Qwen3.8-Flash-Next 125B (NVFP4) at 48.7 tok/s decode — a 125-billion-parameter frontier-class model at reading speed on a €4,999-class box. You want the quietest possible development machine that also does local AI → Mac Studio: macOS + Apple Silicon runs 27B-class models at 53.3 tok/s decode (with MTP) and doubles as a daily driver. You plan to cluster → decide by fabric, not by chip: four Sparks stay within reach of a 2x 200 GbE fabric (three in a ring, four via a RoCE switch; clustered memory stacks to 512 GB, power to ~400 W sustained) and four Sparks are a documented pattern, while multi-Mac clustering over Thunderbolt 5 RDMA remains a weekend experiment. Maximum privacy per euro → neither alone: check what your target model/quantization actually runs at before buying; the community benchmarks in our local-AI recipe hub list every number with its condition and source for both platforms. A Mac Studio at twice the price is not "twice as fast" — it is a wider pipe running a different engine.