vs Mac Studio
Apple withdrew the comparison
Between March and May 2026 Apple discontinued the 512GB, 256GB and 128GB Mac Studio configurations — reporting supply pressure from exactly the local-AI demand this machine serves. The top Mac Studio you can order today has 96GB.
DGX Spark
128GB
$4,699 US direct · in stock
Mac Studio M3 Ultra — the largest Apple sells
96GB
$5,299 base · 6–10 week lead times reported
$600 more, 32GB less. Our 100GB-class library — DeepSeek V4 Flash at 104GB, Laguna at Q6, MiniMax-M2.5 — does not load on any Mac Studio currently on sale.
Where Apple silicon wins — and it does
Bandwidth is destiny for decode speed, and Apple has more of it.
An M5 Max MacBook (128GB, 614 GB/s) decodes gpt-oss-120b at ~87.9 tok/s against the Spark’s 33.5–50 — roughly twice as fast, on battery, in a laptop. If your workload fits 96GB and single-stream speed is what you feel, Apple silicon is a real competitor. Two community benchmarks disagree on the exact gap (different chips, different workloads); both are in our research file with provenance, unaveraged.
What the Mac cannot do is load the 100GB class at all — and Apple no longer sells a desktop that can. The Spark’s argument was never speed. It is that the frontier open model loads, on your desk, for a one-time price, from stock.
Questions, answered straight
- Doesn't Apple still sell 128GB machines?
- In laptops, yes — a 128GB MacBook Pro exists and decodes fast. The desktop Mac Studio line stops at 96GB as of May 2026. The secondary market still has withdrawn configs at collector pricing.
- What if Apple brings big memory back?
- An M5 Ultra refresh is rumoured for October 2026, and this page carries a review date for exactly that reason. If Apple ships 256GB again at a sane price, we will update this comparison the week it happens — the rest of our argument (price, stock, CUDA ecosystem, clustering) does not depend on Apple's roadmap.
- Is macOS or DGX OS better for local AI?
- Different ecosystems: MLX and llama.cpp Metal are excellent on Apple silicon; the Spark runs the CUDA stack — vLLM, TensorRT, ComfyUI playbooks, NVFP4 quants — plus official NVIDIA playbooks for this exact machine. If your tooling is CUDA-shaped, that decides it before the hardware does.
Verified 4 August 2026 against Apple’s store and primary reporting. Review monthly — Apple’s line-up is the moving part here.