HP’s ZGX Fury AI station is now available to order, and HP paired the availability news with a collaboration with Red Hat and NVIDIA to put Red Hat AI Factory with NVIDIA on top of it. The ZGX Fury is HP’s take on NVIDIA’s DGX Station design, built around the GB300 Grace Blackwell Ultra Desktop Superchip with 748GB of unified memory and up to 20 petaFLOPS of FP4 compute, and HP is positioning it less as a personal workstation than as a shared inference box that a department, a factory floor, or a branch office can run without a data center behind it. We have one in the lab now, so a full review is coming; this is what HP has said so far.
HP ZGX Fury Hardware: One GB300 Superchip, 748GB of Memory, Tower or 5U
The core of the system is the same silicon we tested in the MSI XpertStation WS300: one Blackwell Ultra GPU with 252GB of HBM3e at 7.1TB/s, tied to a 72-core Grace CPU with 496GB of LPDDR5X over NVLink-C2C. HP’s spec sheet fills in details the platform announcements skipped. The CPU memory is four 128GB SOCAMM modules delivering 396GB/s, and the Grace CPU is soldered to the host processor module rather than socketed. The two pools add up to the 748GB coherent space that lets the GPU address CPU memory directly, which is what makes trillion-parameter inference and fine-tuning of models in the 100 billion parameter class possible on a single box. HP’s footnote on those model sizes is that the harness quantizes at FP4.
Two embedded M.2 slots hang off the Grace CPU on PCIe 5.0 and hold the operating system in a software RAID 1 mirror. Two more M.2 slots come off the PCIe switch inside the ConnectX-8 SuperNIC and serve as a RAID 0 data volume, with 2TB or 4TB of self-encrypting NVMe chosen at purchase.
Networking is the ConnectX-8 with two QSFP112 ports at 400Gbps each, which can link two ZGX Fury systems together, plus a 10GbE RJ-45 for the host and a separate 1GbE RJ-45, Mini-DP, and micro-USB for the BMC. The rest of the I/O is workstation-normal: two USB-A and two USB-C ports up front, four more USB ports at the rear, audio jacks, a Kensington slot, and a C20 inlet for the power cord. There is no display output from the GB300 itself; HP offers an optional NVIDIA RTX PRO GPU to drive monitors so the Blackwell Ultra GPU stays dedicated to inference. The chassis is a tower that also ships with rails for a 5U rack slot, and HP uses liquid cooling with optimized airflow, which matches what we found on the MSI unit, where a 1,400W-rated loop kept the GPU at 71C under full load.
HP ZGX Fury Software: Ubuntu, Z Runtime, and Red Hat Certification
HP ships the ZGX Fury with Ubuntu 24.04 LTS and NVIDIA’s AI developer tools, an NVIDIA-approved partner BIOS and BMC firmware, and two HP-specific layers. HP Z Runtime is a pre-installed command-line tool for pulling, serving, and managing models locally, and HP Z Toolkit adds open-source frameworks, MLflow experiment tracking, and Ollama testing with discovery and sync across ZGX systems. The idea is that a team prototypes on a ZGX Nano and moves the same workflow to a ZGX Fury when it needs more memory, more throughput, or more concurrent users.
The new piece is Red Hat. HP says the ZGX Fury is certified for Red Hat Enterprise Linux and listed in the Red Hat Ecosystem Catalog today, and the two companies are developing what HP calls an open, enterprise-grade AI platform that runs Red Hat AI Factory with NVIDIA on the ZGX Fury. Red Hat AI Factory with NVIDIA is Red Hat’s packaging of RHEL, OpenShift, and Red Hat AI Enterprise with NVIDIA AI Enterprise for deploying models, agents, and applications across hybrid cloud. On the ZGX Fury, HP says the combination is meant to cut environment setup time and deployment risk, improve GPU utilization through optimized CUDA libraries, scheduling, and multi-GPU workload orchestration, and let developers offload compute to the box without changing their existing workflows. The platform is also being designed to run multiple AI workloads on one system with workload isolation and governance, which is how HP gets from a deskside machine to something IT can manage as edge infrastructure.
“The future of AI is moving closer to where people work, machines operate and critical decisions are made,” said Jim Nottingham, Senior Vice President and Division President of Advanced Compute and Solutions at HP. “Together with Red Hat and NVIDIA, HP is extending enterprise AI from the data center to the edge with an open, enterprise-grade inference platform designed to give customers greater choice, control and consistency as they deploy local AI factories.” Chris Marriott, Vice President of Enterprise Platforms and Solutions at NVIDIA, framed it the same way: running “powerful AI locally while maintaining the security, scalability, and consistency enterprises demand.”
The ZGX Fury is orderable now through HP; pricing was not disclosed in the announcement. The Red Hat AI Factory integration is a planned solution rather than a shipping SKU, and HP says customers will be able to evaluate it in a sandboxed environment on HP devices before moving to production, with timing, eligibility, and supported configurations still to come. The competitive picture is filling in quickly: MSI’s WS300 is shipping on the same superchip, and AMD’s Threadripper Halo Station is aimed at the same workloads. Our ZGX Fury review will put HP’s version of the platform through the same model and testing we ran on the MSI.