HP Z8 Fury G5 vs NVIDIA DGX Spark

HP's flagship workstation, the Z8 Fury G5, is a formidable and highly scalable tower aimed at demanding professional media, VFX, and AI creators who need a four-GPU ceiling. Built around Intel's Xeon W9-3495X (56 cores), 128 GB DDR5 ECC, and up to four NVIDIA RTX A6000 cards, it is a credible local-LLM training and inference rig at the upper end. Configured prices vary enormously: a 1-GPU base build lands around $7,995, a 2-GPU build around $14,000, and a fully loaded 4x RTX A6000 configuration pushes well past $25,000. The price field below reflects a typical 1-GPU configured build, so readers planning multi-GPU AI work should expect to roughly triple that figure.

The NVIDIA DGX Spark is the productized version of Project DIGITS — a 150 x 150 x 50.5 mm box 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.