Head-to-head · Best AI Workstations

Apple Mac Studio M3 Ultra vs NVIDIA DGX Spark

Which is the better buy? Side-by-side on rating, price, strengths, and watch-outs — with the published ratings we averaged to get there.

The short answer

NVIDIA DGX Spark comes out ahead by a narrow margin (4.3 vs 4.6). The gap is mostly about Best for local-LLM developers — CUDA-native 128 GB dev box — read the strengths below before deciding.

Ranked #5 in Best AI Workstations

Apple Mac Studio M3 Ultra

4.3

$3,999as of Apr 25

The Apple Mac Studio with the M3 Ultra chip is the highest-memory-bandwidth single-machine pick in this guide. The base 96 GB / 64-GPU-core configuration starts at $3,999 and scales up to 512 GB unified memory — enough to hold a 405B-parameter Q4 model on a single desktop. Memory bandwidth of 819 GB/s is roughly three times that of a Mac mini M4 Pro and gives the Mac Studio the fastest single-user 70B Q4 inference of any machine in this guide that doesn't have a discrete pro GPU. Reviewers across PCMag, TechRadar, Tom's Guide, and Macworld praised its compactness, silent operation, and raw performance in creative workflows; the trade-off is the closed Apple ecosystem (MLX/Metal only, no CUDA) and zero hardware upgradability after purchase. For local-LLM developers who can live within the Mac toolchain and need a 256+ GB unified memory ceiling, this is the most cost-effective path under $10,000.

Strengths

— Up to 512 GB unified memory at 819 GB/s — the highest memory bandwidth in this entire guide
— Compact and stylish desktop chassis (3.7 x 7.7 x 7.7 inches) with silent operation
— Operates quietly even under heavy AI inference load

Watch-outs

— Internal components like GPU and storage are not upgradable
— High price for the 256/512 GB unified-memory configs that unlock 405B-class models
— Lacks Wi-Fi 7 support

$3,999 · Check Price on Amazon Full review →

Higher ratedRanked #2 in Best AI Workstations

NVIDIA DGX Spark

4.6

$4,699as of Apr 25

The NVIDIA DGX Spark is the productized version of Project DIGITS — a 150 mm cube housing the GB10 Grace Blackwell Superchip, 128 GB unified LPDDR5x, and the full CUDA AI stack out of the box. Tom's Hardware called it 'a well-rounded toolkit for local AI'; ServeTheHome called it 'must-have for AI developers'; LMSYS published the most thorough independent benchmarks. The 128 GB unified-memory ceiling is the headline feature: it loads models that would otherwise need a $30K+ multi-GPU rig. The catch is bandwidth-limited decode — LMSYS measured Llama-3.1 70B FP8 at 2.7 tokens/sec single-batch, while GPT-OSS 120B (MoE, ~17B active) hits ~14.5 tokens/sec per ServeTheHome. Best understood as a CUDA-native development box for buyers who need to iterate on big-model code without renting cloud GPUs.

Strengths

— 128 GB unified LPDDR5x memory — fits 70B FP8 / 120B Q4 / 405B with two clustered units
— Full CUDA + NVIDIA AI stack preinstalled; the most polished local-AI dev box on the market
— Compact 150 mm cube, 240 W max — fits any desk, runs cool and quiet

Watch-outs

— 273 GB/s LPDDR5x bandwidth caps decode tok/s on dense large models — 70B FP8 measures ~2.7 tok/s on a single unit
— Linux-only, no Windows or gaming use; specialist hardware for AI developers
— Price raised from $3,999 to $4,699 in February 2026 due to memory supply

$4,699 · Buy at nvidia.com Full review →

How they stack up

Apple Mac Studio M3 Ultra

The Apple Mac Studio M3 Ultra is the best Mac-ecosystem AI workstation and competitive on raw local-LLM throughput per dollar. Versus the DGX Spark ($4,699 / 128 GB), the base Mac Studio M3 Ultra ($3,999 / 96 GB) loses on memory ceiling but wins on memory bandwidth (819 vs 273 GB/s) — meaning faster decode tok/s on dense models that fit. Step up to a 256 GB or 512 GB Mac Studio config and you exceed the Spark's memory ceiling at higher bandwidth, at the cost of premium Apple memory pricing. Versus the multi-GPU PC workstations (Puget, HP Z6/Z8), the Mac Studio cannot match peak training throughput but is silent, half the size, and roughly half the price of an equivalent dual-GPU PC build.

NVIDIA DGX Spark

The DGX Spark is the cheapest path to 128 GB of CUDA-addressable unified memory anywhere on the market. Versus the GMKtec EVO-X2 ($1,699) or Beelink GTR9 Pro ($2,000), it's roughly 2.5x the price but offers the full NVIDIA software stack the Strix Halo boxes can only approximate via ROCm or Vulkan. Versus the Puget Genesis II ($10K+), it's a single-purpose dev box — no multi-display creative workflow, no gaming, no general workstation duty. Pair two Sparks via the ConnectX-7 networking and you get 405B-class model coverage at roughly $9,400, the cheapest legal path to that ceiling.

Specs side-by-side

Spec	Apple Mac Studio M3 Ultra	NVIDIA DGX Spark
CPU	Apple M3 Ultra (up to 32-core)	20-core Arm (10x Cortex-X925 + 10x Cortex-A725)
GPU	Integrated up to 80-core Apple GPU	NVIDIA GB10 Grace Blackwell Superchip
RAM	96–512 GB unified memory	128 GB unified LPDDR5x
Storage	Up to 16 TB SSD	4 TB NVMe M.2 (user-replaceable, self-encrypting)
Memory Bandwidth	819 GB/s	273 GB/s
Form Factor	Compact desktop	Compact desktop (150 mm cube, 1.2 kg)

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