{"product_id":"hp-zgx-fury-g1n-gb300-ai-workstation-1","title":"HP ZGX Fury G1n GB300 AI Workstation","description":"\u003cp style=\"margin:1em 0\"\u003eThe HP ZGX Fury G1n is a next-generation enterprise AI workstation powered by the NVIDIA Grace Blackwell Ultra (GB300) Superchip. Engineered to deliver up to 20 PFLOPS of FP4 AI compute, it accelerates large language model training, foundation model fine-tuning, generative AI deployment, and high-performance scientific simulations entirely on-premises.\u003c\/p\u003e\u003cp style=\"margin:1em 0\"\u003eFeaturing 748 GB of coherent unified memory—combining 252 GB of ultra-fast HBM3e GPU memory at 7.1 TB\/s with 496 GB of LPDDR5X CPU memory over NVLink-C2C—the system natively supports models with up to 1 trillion parameters. This architecture delivers massive throughput for retrieval-augmented generation (RAG), engineering simulation, and complex data science workflows.\u003c\/p\u003e\u003cp style=\"margin:1em 0\"\u003eEquipped with a 72-core NVIDIA Grace Arm Neoverse V2 CPU and dual NVIDIA ConnectX-8 400 GbE QSFP interfaces, the ZGX Fury G1n enables high-throughput clustering with up to 800 Gb\/s bandwidth. Built-in datacentre-class cooling ensures reliable 24\/7 continuous operation without requiring dedicated liquid-cooled rack infrastructure.\u003c\/p\u003e\n\u003ctable class=\"pu-table\" style=\"width:100%;border-collapse:separate;border-spacing:0;border:0;box-shadow:none;outline:none;background:none;table-layout:fixed;margin:0 0 1em\"\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eBrand\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eHP\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eModel\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eHP ZGX Fury G1n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eProduct Type\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eEnterprise Desktop AI Supercomputer \/ AI Workstation\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eProcessor Platform\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eNVIDIA GB300 Grace Blackwell Ultra Superchip\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eGPU\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003e1 × NVIDIA Blackwell Ultra\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eCPU\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003e1 × NVIDIA Grace (72-Core Arm Neoverse V2)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eAI Performance\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eUp to 20 PFLOPS FP4 Tensor Core\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eTotal Coherent Memory\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003e748 GB Unified\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eGPU Memory\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003e252 GB HBM3e (7.1 TB\/s)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eCPU Memory\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003e496 GB LPDDR5X (396 GB\/s)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eInterconnect\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eNVLink-C2C (900 GB\/s)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eModel Support\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eUp to 1 Trillion Parameters\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eGPU Partitioning\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eMulti-Instance GPU (MIG) — Up to 7 Instances\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eNetworking SuperNIC\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eNVIDIA ConnectX-8 (Up to 800 Gb\/s Ethernet)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eHigh-Speed Ports\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003e2 × QSFP (400 Gb\/s each)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eStandard Ethernet\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003e10 GbE + 1 GbE Management\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eDrive Platform\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eM.2 Gen 5 Platform Slots\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eOperating System\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eUbuntu with NVIDIA AI Developer Tools (DGX Software Stack)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eAI Software Stack\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eCUDA, NVIDIA AI Enterprise, TensorRT, NVIDIA NIM, PyTorch, TensorFlow\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003ePower Supply\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eHP Enterprise High-Efficiency Power Supply (~1,600 W Platform)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eCooling System\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eDatacentre-Class Component Cooling (No Liquid-Cooled Rack Required)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eChassis Color\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top;border-bottom:1px solid rgba(128,128,128,0.16);border-bottom:1px solid color-mix(in srgb,currentColor 12%,transparent)\"\u003eBlack\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border:0;padding:0.4em 0.75em 0.4em 0;opacity:0.65;vertical-align:top\"\u003eWarranty\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top\"\u003e3\/3\/3 HP Enterprise Workstation Warranty\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e","brand":"HP","offers":[{"title":"RTX PRO 2000 Blackwell \/ 4x2TB","offer_id":48537189155074,"sku":"E6ZS0PT","price":152224.34,"currency_code":"SGD","in_stock":true},{"title":"RTX PRO 4000 Blackwell \/ 2x2TB + 2x4TB","offer_id":48537189187842,"sku":"E6ZS5PT","price":155658.54,"currency_code":"SGD","in_stock":true},{"title":"No Graphics Card \/ 4x2TB 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