Skip to main content
  • $33,999.00
  • This item is not returnable
  • Sold by NeweggBusiness

    Shipped by NeweggBusiness

    ABS AI Workstation - 144GB Aggregate VRAM (2x 72GB NVIDIA RTX PRO 5000 Blackwell), Intel Xeon W9-3575X, 128GB ECC DDR5 RDIMM, 2TB+4TB NVMe M.2, 2000W 80+ Gold, Ubuntu (Zaurion ZAW9-3575X-RP500072X2)

    • Item #: 9B-89-850-012
    • Mfr. Part #: ZAW9-3575X-RP500072X2
    • 2x RTX Pro 6000 Blackwell MaxQ | Threadripper PRO 7975WX | 128GB DDR5 | 2TB+4TB SSD
    • 2x RTX Pro 6000 Blackwell MaxQ | Xeon W9-3575X | 128GB DDR5 | 2TB+4TB SSD
    • 3x AMD Radeon AI Pro R9700 | Threadripper 9965WX | 128GB DDR5 | 2x 2TB M.2
    • 3x Intel Arc Pro B70 | Threadripper 9965WX | 128GB DDR5 | 2x 2TB M.2
    • RTX Pro 6000 Blackwell | Threadripper PRO 7975WX | 128GB DDR5 | 2TB+4TB SSD
    • RTX Pro 6000 Blackwell | Threadripper PRO 7975WX | 64GB DDR5 | 1TB+2TB SSD
    • RTX Pro 6000 Blackwell | Xeon W5-2455X | 64GB DDR5 | 1TB+2TB SSD
    • RTX Pro 6000 Blackwell | Xeon W9-3575X | 128GB DDR5 | 2TB+4TB SSD
    • 2x RTX Pro 5000 Blackwell 72GB | Threadripper PRO 9975WX | 128GB DDR5 | 2TB+4TB SSD
    • 2x RTX Pro 5000 Blackwell 72GB | Xeon W9-3575X | 128GB DDR5 | 2TB+4TB SSD
    • RTX Pro 5000 Blackwell 72GB | Threadripper PRO 9965WX | 128GB DDR5 | 2TB+4TB SSD
    • RTX Pro 5000 Blackwell 72GB | Xeon W5-2455X | 128GB DDR5 | 2TB+4TB SSD
    • Compliance Documents Required for Purchase
    • Assembled in USA
    • TAA Compliant
    • Operating System: Ubuntu
    • CPU: Intel Xeon W9-3575X
    • GPU: 2x RTX Pro 5000 Blackwell (72GB GDDR7)
    • Motherboard: Gigabyte MW83-RP0
    • Memory: 128GB DDR5 Server RAM - ECC, Registered
    • OS SSD: 2TB M.2 NVMe (Installed)
    • Data SSD: 4TB M.2 NVMe (Installed)
    • LAN: 2 x 10GB/s LAN, 1 x 10/100/1000 Mbps Management LAN
    • PSU: Single 2000W ATX 80 PLUS Gold power supply
    • Barebone: Gigabyte W773-W80
    • AI Agent Ready: Optional pre-installed OpenClaw (enterprise AI agent framework)
    • Local LLM Support: Optional Qwen 3.5 27B or higher models for on-prem AI inference
    Please note that this product is non-returnable and non-refundable.
    +
    +
    Overview
    Specs
    Reviews
    ABS Zaurion Ruby Tower · Dual-GPU, Max Threads

    One Box, Many Jobs.

    Intel Xeon W9-3575X  +  2x NVIDIA RTX PRO 5000 Blackwell 72 GB

    88 threads and two independent 72 GB GPUs mean this single tower can genuinely run two workstreams at once — not just a bigger version of a one-job-at-a-time machine. 144 GB of aggregate VRAM, split however the work needs it.

    144 GB Aggregate VRAM 44c / 88t CPU Ubuntu Ready Assembled in USA · TAA
    Dark indigo-lit industrial workspace with a single compact matte-black tower workstation standing on the floor beside a desk with dual monitors showing multi-panel dashboards
    2x 72 GB
    GDDR7 GPUs, 144 GB aggregate
    44c / 88t
    Intel Xeon W9-3575X
    128 GB
    DDR5, ECC Registered
    6 TB
    NVMe SSD storage installed
    2000 W
    80 PLUS Gold PSU
    AI Silicon Spotlight · Hardware First

    What This Pairing Actually Buys You

    The highest CPU thread count in this chassis lineup's dual-GPU tier, feeding two independent 72GB GPUs:

    GPU · 2x NVIDIA RTX PRO 5000 Blackwell

    144 GB Aggregate, Two Independent Cards

    • Two independent 72 GB GPUs — 144 GB aggregate, not a single unified pool. Run two workloads, or split one large job across both.
    • Blackwell 5th-gen Tensor Cores with FP41 accelerate agentic and generative AI on each card.
    • 4th-gen RT Cores1 drive photoreal rendering previews on either GPU.
    • Universal MIG1 can partition either card further for multiple concurrent users.
    CPU · Intel Xeon W9-3575X

    44 Cores, 88 Threads, Two GPUs to Feed

    • 44 cores / 88 threads on LGA4677 — the highest thread count Intel option in this chassis lineup's dual-GPU tier.
    • Notably more cores and threads than this lineup's AMD-based dual-GPU alternative, on the same Compare Options list — a genuine platform difference, not a universal rule about either vendor.
    • 8-channel DDR5 memory keeps both GPUs supplied with data without the CPU becoming the shared bottleneck.
    • Workstation-grade ECC memory support brings server-class reliability to long dual-GPU jobs.
    Two GPUs, Two Workstreams

    One Box, Many Jobs at Once

    88 threads and two independent GPUs turn "one job at a time" into "two jobs, right now." Some concrete pairings this configuration can actually run:

    A dramatic close-up of the glowing indigo-lit tower workstation between two monitors, one showing a climbing training-progress chart and the other a live code response stream, with an excited person reacting
    GPU 1 Runs
    • Fine-tune a model against a training set
    • Render a production scene
    • Encode a finished video export
    • Run the game engine live
    GPU 2 Runs, at the Same Time
    • Serve live inference requests
    • Preview the next scene's changes
    • Keep editing the next timeline
    • Test the previous build in parallel

    Illustrative workload pairings, not a guaranteed performance benchmark for any specific software.

    AI Features · What This Actually Does

    Six Jobs, Two GPUs Deep

    The listing's own AI Features, translated into what running two GPUs and 88 threads actually enables:

    Developer smiling at a completed training result on dual monitors, tower workstation beside the desk, dark indigo accent lighting

    AI Development

    Fine-tune on one GPU while serving inference on the other, with 88 threads keeping both fed with data.

    Data scientist reviewing dataset dashboards next to the tower workstation, dark indigo accent lighting

    Data Science

    88 threads handle preprocessing for two parallel data pipelines, one feeding each GPU.

    Engineer reviewing scientific simulation visuals next to the tower workstation, dark indigo accent lighting

    HPC

    Split a large simulation across both GPUs, or run two independent simulations side by side.

    Designer reviewing photorealistic renders next to the tower workstation, dark indigo accent lighting

    AI-Driven Rendering & Graphics

    Render two scenes at once on separate GPUs, or split a single large scene's passes across both.

    Video editor working on multiple media timelines next to the tower workstation, dark indigo accent lighting

    Video Content & Streaming

    Encode one project while editing the next, one GPU each, with 88 threads handling the pipeline work around both.

    Game developer reviewing a 3D engine viewport next to the tower workstation, dark indigo accent lighting

    Game Development

    Run the engine live on one GPU while a build tests on the other — one box, two workstreams.

    Scene photos are AI-generated illustrations of typical deployments, not photographs of this exact product.

    Full Configuration

    As Configured

    ZAW9-3575X-RP500072X2
    CPUIntel Xeon W9-3575X — 44-core / 88 threads, LGA46771
    GPU2x NVIDIA RTX PRO 5000 Blackwell — 72 GB GDDR7 each, 144 GB aggregate
    Memory128 GB DDR5, ECC Registered
    Storage2 TB M.2 NVMe (OS)  +  4 TB M.2 NVMe (Data)
    Networking2× 10 Gb/s LAN + 1× 10/100/1000 Mbps management LAN
    MotherboardGigabyte MW83-RP0 (Gigabyte W773-W80 barebone)
    PowerSingle 2000 W ATX 80 PLUS Gold
    Expansion8× RDIMM (8-channel DDR5), 5× PCIe 5.0 x16 + 2× PCIe 4.0 x16 (2 populated), 2× M.2 (both populated)
    OSUbuntu
    OptionalOpenClaw agent framework (pre-installed); Qwen 3.5 27B+ local LLM package
    FAQ

    Quick Answers Before You Buy

    Is the 144 GB of VRAM one big pool or two separate GPUs?

    Two independent 72 GB GPUs — 144 GB aggregate, not a single unified pool. Run two separate workloads, one per GPU, or split a single large job across both.

    Why 44 cores / 88 threads specifically?

    Two GPUs need enough CPU parallelism to keep both fed with data at once. This is the highest core/thread count Intel option in this chassis lineup's dual-GPU 144GB tier — notably more than the AMD-based dual-GPU option in the same tier.

    Can this really run two separate jobs at the same time?

    Yes — with two independent GPUs and 88 CPU threads, this is a genuinely different capability from a single-GPU workstation. Train on one GPU while serving inference on the other, for example.

    Does it come with an AI agent framework or local LLM pre-installed?

    The AI agent framework (OpenClaw) is pre-installed; a Qwen 3.5 27B or higher local LLM package is an optional add-on configured at order time.

    Is it eligible for government / public-sector purchasing?

    It is TAA compliant and assembled in the USA, with compliance documents available for purchase review.

    How is it supported?

    1-year parts and labor limited warranty backed by ABS manufacturer support. As a Build to Order system, it is custom built and stress-tested after purchase.

    Assembled in USA
    TAA Compliant
    144 GB Aggregate VRAM
    Build to Order flexibility
    1. Intel-published core/thread count for the Xeon W9-3575X. GPU architecture features (5th-gen Tensor Cores, 4th-gen RT Cores, Universal MIG) are NVIDIA-published for the Blackwell professional GPU architecture generation, not SKU-specific benchmark figures. ABS Zaurion Ruby ZAW9-3575X-RP500072X2 · Gigabyte W773-W80 platform (LGA4677 socket) · Optional components and software are configured at time of purchase.

    Warranty & Returns

    Warranty, Returns, And Additional Information

    Warranty

    • Limited Warranty period (parts): 1 year
    • Limited Warranty period (labor): 1 year

    Return Policies

    • Return for refund within: non-refundable
    • Return for replacement within: non-replaceable
    • This item is covered by NeweggBusiness.com's Manufacturer Only Return Policy.
    • Read full return policy for details.
    LOADING...