{"product_id":"hp-zgx-fury-g1n-gb300-ai-workstation-with-nvidia-blackwell-ultra","title":"HP ZGX Fury G1n GB300 AI Workstation with NVIDIA Blackwell Ultra","description":"\u003c!-- ZGX-FLASH-SALE-START --\u003e\n\u003ch2\u003e\u003cstrong\u003eHP ZGX Fury G1n GB300 AI Workstation with NVIDIA Blackwell Ultra, 748GB Coherent Memory, 72-Core Grace CPU \u0026amp; Dual 400G ConnectX-8 Networking - Local Warranty \u003c\/strong\u003e\u003c\/h2\u003e\n\u003ch3 data-start=\"217\" data-end=\"288\" class=\"PDq2pG_selectionAnchorContainer\"\u003e\n\u003cstrong data-start=\"217\" data-end=\"286\"\u003eNext-Generation Enterprise AI Workstation Powered by NVIDIA GB300\u003c\/strong\u003e\u003cspan aria-hidden=\"true\" class=\"PDq2pG_selectionAnchor\"\u003e\u003c\/span\u003e\n\u003c\/h3\u003e\n\u003cp data-start=\"290\" data-end=\"1013\"\u003eThe HP ZGX Fury G1n GB300 AI Workstation is a next-generation AI supercomputer designed to accelerate the most demanding artificial intelligence, machine learning, and high-performance computing workloads. Built around the NVIDIA Grace Blackwell Ultra (GB300) Superchip, it delivers up to \u003cstrong data-start=\"579\" data-end=\"606\"\u003e20 PFLOPS of AI compute\u003c\/strong\u003e, empowering organisations to train, fine-tune, and deploy large language models (LLMs), AI agents, generative AI applications, computer vision models, and advanced scientific simulations entirely within their own infrastructure. It is purpose-built for enterprises, research institutions, universities, government agencies, and AI innovation labs seeking maximum performance with complete data sovereignty.\u003c\/p\u003e\n\u003ch3 data-start=\"1015\" data-end=\"1076\"\u003e\u003cstrong data-start=\"1015\" data-end=\"1074\"\u003e748GB Coherent Unified Memory for Large-Scale AI Models\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp data-start=\"1078\" data-end=\"1551\"\u003eThe HP ZGX Fury G1n features an impressive \u003cstrong data-start=\"1121\" data-end=\"1157\"\u003e748GB of coherent unified memory\u003c\/strong\u003e, enabling AI models and massive datasets to reside in a single memory space for significantly improved performance and efficiency. This unified architecture reduces data movement between CPU and GPU, accelerating AI inferencing, retrieval-augmented generation (RAG), foundation model fine-tuning, engineering simulations, digital twins, cybersecurity analytics, and complex research workloads.\u003c\/p\u003e\n\u003ch3 data-start=\"1553\" data-end=\"1620\"\u003e\u003cstrong data-start=\"1553\" data-end=\"1618\"\u003e72-Core NVIDIA Grace CPU with Dual 400G ConnectX-8 Networking\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp data-start=\"1622\" data-end=\"2120\"\u003eAt the heart of the workstation is the \u003cstrong data-start=\"1661\" data-end=\"1705\"\u003e72-core NVIDIA Grace Arm Neoverse V2 CPU\u003c\/strong\u003e, engineered to work seamlessly with the Blackwell Ultra GPU through NVIDIA's high-bandwidth coherent architecture. Combined with \u003cstrong data-start=\"1835\" data-end=\"1885\"\u003edual NVIDIA ConnectX®-8 400GbE QSFP networking\u003c\/strong\u003e, the system delivers ultra-low latency communication and exceptional bandwidth for distributed AI training, private AI clusters, and high-performance computing environments, ensuring outstanding scalability for enterprise deployments.\u003c\/p\u003e\n\u003ch3 data-start=\"2122\" data-end=\"2193\"\u003e\u003cstrong data-start=\"2122\" data-end=\"2191\"\u003eEnterprise-Ready AI Infrastructure for Mission-Critical Workloads\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp data-start=\"2195\" data-end=\"2729\"\u003eDesigned for continuous operation, the HP ZGX Fury G1n offers enterprise-class reliability, advanced thermal engineering, secure remote management, and support for NVIDIA Multi-Instance GPU (MIG) technology to maximise resource utilisation across multiple users and AI workloads. Whether deployed as a standalone AI workstation or integrated into a private AI cloud, it provides the performance, security, and scalability required for healthcare, finance, manufacturing, engineering, autonomous systems, and government AI initiatives.\u003c\/p\u003e\n\u003ch3 data-start=\"2731\" data-end=\"2773\"\u003e\u003cstrong data-start=\"2731\" data-end=\"2771\"\u003eTechnical Specifications\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp\u003e\u003cstrong\u003eGeneral\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eModel: HP ZGX Fury G1n\u003cbr\u003eProduct Name: HP ZGX Fury G1n GB300 AI Workstation with NVIDIA Blackwell Ultra, 748GB Coherent Memory, 72-Core Grace CPU \u0026amp; Dual 400G ConnectX-8 Networking\u003cbr\u003eManufacturer: HP\u003cbr\u003eProduct Family: HP ZGX\u003cbr\u003eProduct Series: HP ZGX Fury\u003cbr\u003eProduct Type: Enterprise AI Workstation \/ Deskside AI Supercomputer\u003cbr\u003eCompute Platform: NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip\u003cbr\u003eProcessor Architecture: NVIDIA Grace CPU + NVIDIA Blackwell Ultra GPU\u003cbr\u003eCPU Platform: NVIDIA Grace CPU\u003cbr\u003eGPU Platform: NVIDIA Blackwell Ultra\u003cbr\u003eSystem Architecture: Coherent CPU-GPU Accelerated Computing Platform\u003cbr\u003eCPU Core Count: 72 Arm Neoverse V2 Cores\u003cbr\u003eTotal Coherent Memory: 748GB\u003cbr\u003eAI Compute Performance: Up to 20 PetaFLOPS FP4\u003cbr\u003eSupported AI Model Size: Up to 1 Trillion Parameters\u003cbr\u003eHigh-Speed Networking: Dual 400G NVIDIA ConnectX-8 Networking\u003cbr\u003eMaximum Aggregate High-Speed Network Bandwidth: Up to 800Gbps\u003cbr\u003eDeployment Type: Deskside, Enterprise Laboratory, AI Development Facility or Rack-Ready Environment\u003cbr\u003ePrimary Workloads: Generative AI, Agentic AI, Large Language Models, Model Training, Fine-Tuning, Inferencing, Data Science and High-Performance Computing\u003cbr\u003eTarget Users: Enterprises, Government Agencies, Universities, Research Institutions, AI Developers, Data Scientists and Engineering Teams\u003cbr\u003eOperating System: NVIDIA AI-Optimised Linux Environment, Configuration Dependent\u003cbr\u003eNVIDIA AI Software Stack: Supported\u003cbr\u003eEnterprise Remote Management: Supported, Configuration Dependent\u003cbr\u003eWarranty: HP Enterprise Workstation Warranty, Configuration Dependent\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eProcessor Specifications\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eProcessor Platform: NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip\u003cbr\u003eCPU Manufacturer: NVIDIA\u003cbr\u003eCPU Model: NVIDIA Grace CPU\u003cbr\u003eCPU Quantity: 1\u003cbr\u003eCPU Architecture: Arm\u003cbr\u003eCPU Core Architecture: Arm Neoverse V2\u003cbr\u003eCPU Core Count: 72 Cores\u003cbr\u003eCPU Class: Datacentre-Class Accelerated Computing Processor\u003cbr\u003eCPU-GPU Interconnect: NVIDIA NVLink-C2C\u003cbr\u003eCPU-GPU Coherency: Supported\u003cbr\u003eUnified CPU-GPU Address Space: Supported\u003cbr\u003eHigh-Bandwidth CPU-GPU Communication: Supported\u003cbr\u003eLow-Latency Data Exchange: Supported\u003cbr\u003eLarge-Scale Parallel Computing: Supported\u003cbr\u003eMulti-Threaded AI Processing: Supported\u003cbr\u003eScientific Computing: Supported\u003cbr\u003eHigh-Performance Computing: Supported\u003cbr\u003eData Science Processing: Supported\u003cbr\u003eContinuous Enterprise Workloads: Supported\u003cbr\u003eAI Pipeline Processing: Supported\u003cbr\u003eEnterprise Model Development: Supported\u003cbr\u003eOptimised for NVIDIA CUDA-X Libraries\u003cbr\u003eOptimised for NVIDIA AI Enterprise Software\u003cbr\u003eOptimised for Large Language Model Workloads\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eAI Performance\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eMaximum AI Compute Performance: Up to 20 PetaFLOPS FP4\u003cbr\u003eAI Accelerator: NVIDIA Blackwell Ultra GPU\u003cbr\u003eGPU Generation: NVIDIA Blackwell Ultra\u003cbr\u003eTensor Core Generation: Fifth-Generation NVIDIA Tensor Cores\u003cbr\u003eTransformer Engine: Second-Generation NVIDIA Transformer Engine\u003cbr\u003eFP4 AI Computing: Supported\u003cbr\u003eFP6 AI Computing: Supported\u003cbr\u003eFP8 AI Computing: Supported\u003cbr\u003eFP16 AI Computing: Supported\u003cbr\u003eBF16 AI Computing: Supported\u003cbr\u003eTF32 Computing: Supported\u003cbr\u003eINT8 AI Inferencing: Supported\u003cbr\u003eMixed-Precision Computing: Supported\u003cbr\u003eMicroscaling Data Formats: Supported\u003cbr\u003eDynamic Precision Management: Supported\u003cbr\u003eAI Reasoning Acceleration: Supported\u003cbr\u003eGenerative AI Acceleration: Supported\u003cbr\u003eLarge Language Model Acceleration: Supported\u003cbr\u003eFoundation Model Training: Supported\u003cbr\u003eFoundation Model Fine-Tuning: Supported\u003cbr\u003eProduction AI Inferencing: Supported\u003cbr\u003eLong-Context Inferencing: Supported\u003cbr\u003eMultimodal AI Processing: Supported\u003cbr\u003eAI Agent Development: Supported\u003cbr\u003eLong-Running AI Agent Support: Supported\u003cbr\u003eRetrieval-Augmented Generation: Supported\u003cbr\u003eScientific AI Processing: Supported\u003cbr\u003eHigh-Performance Data Analytics: Supported\u003cbr\u003eSupported AI Model Size: Up to 1 Trillion Parameters\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eAI Features\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eLarge Language Model Development\u003cbr\u003eLarge Language Model Training\u003cbr\u003eLarge Language Model Fine-Tuning\u003cbr\u003eLarge Language Model Inferencing\u003cbr\u003eFoundation Model Development\u003cbr\u003eFoundation Model Optimisation\u003cbr\u003eGenerative AI Application Development\u003cbr\u003eAgentic AI Development\u003cbr\u003eAutonomous AI Agents\u003cbr\u003eLong-Running AI Agents\u003cbr\u003eReasoning Model Processing\u003cbr\u003eRetrieval-Augmented Generation\u003cbr\u003eMultimodal AI Processing\u003cbr\u003eNatural Language Processing\u003cbr\u003eComputer Vision\u003cbr\u003eSpeech Recognition\u003cbr\u003eSpeech Synthesis\u003cbr\u003eRecommendation Systems\u003cbr\u003ePredictive Analytics\u003cbr\u003eDigital Twin Simulation\u003cbr\u003eScientific Machine Learning\u003cbr\u003ePhysics-Informed Machine Learning\u003cbr\u003eDrug Discovery\u003cbr\u003eMolecular Modelling\u003cbr\u003eGenomics Research\u003cbr\u003eMedical Imaging Analysis\u003cbr\u003eFinancial Modelling\u003cbr\u003eFraud Detection\u003cbr\u003eCybersecurity AI\u003cbr\u003eManufacturing AI\u003cbr\u003eAutonomous Systems Development\u003cbr\u003eRobotics AI\u003cbr\u003eEnterprise Knowledge Assistants\u003cbr\u003ePrivate AI Deployment\u003cbr\u003eSovereign AI Deployment\u003cbr\u003eOn-Premise Model Development\u003cbr\u003eLocal AI Inferencing\u003cbr\u003eHybrid Cloud AI Development\u003cbr\u003eDatacentre AI Deployment\u003cbr\u003eProduction Model Serving\u003cbr\u003eMulti-User AI Development\u003cbr\u003eEnterprise MLOps\u003cbr\u003eAI Factory Development\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eMemory Specifications\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eTotal System Memory: 748GB\u003cbr\u003eMemory Architecture: NVIDIA Coherent Unified Memory\u003cbr\u003eCPU-GPU Shared Memory Pool: Supported\u003cbr\u003eUnified Address Space: Supported\u003cbr\u003eHardware Memory Coherency: Supported\u003cbr\u003eDirect CPU and GPU Memory Access: Supported\u003cbr\u003eHigh-Bandwidth Memory Architecture: Supported\u003cbr\u003eLow-Latency Memory Access: Supported\u003cbr\u003eReduced CPU-GPU Data Copying: Supported\u003cbr\u003eLarge AI Model Loading: Supported\u003cbr\u003eLarge Context Window Processing: Supported\u003cbr\u003eTrillion-Parameter Model Inferencing: Supported\u003cbr\u003eMulti-Billion Parameter Model Fine-Tuning: Supported\u003cbr\u003eLarge Dataset Processing: Supported\u003cbr\u003eIn-Memory Data Science: Supported\u003cbr\u003eAI Model Checkpoint Processing: Supported\u003cbr\u003eRetrieval-Augmented Generation Support: Supported\u003cbr\u003eVector Database Processing: Supported\u003cbr\u003eLarge Embedding Database Processing: Supported\u003cbr\u003eHigh-Concurrency Inferencing: Supported\u003cbr\u003eMulti-User AI Workloads: Supported\u003cbr\u003eScientific Simulation Support: Supported\u003cbr\u003eHigh-Performance Data Analytics: Supported\u003cbr\u003eMemory-Intensive AI Pipeline Support: Supported\u003cbr\u003eEnterprise AI Application Support: Supported\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eGPU Specifications\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eGPU Manufacturer: NVIDIA\u003cbr\u003eGPU Architecture: NVIDIA Blackwell Ultra\u003cbr\u003eGPU Type: Datacentre-Class Enterprise AI Accelerator\u003cbr\u003eGPU Integration: Integrated with NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip\u003cbr\u003eTensor Cores: Fifth-Generation NVIDIA Tensor Cores\u003cbr\u003eTransformer Engine: Second-Generation NVIDIA Transformer Engine\u003cbr\u003eNVIDIA CUDA Support: Supported\u003cbr\u003eNVIDIA CUDA-X Support: Supported\u003cbr\u003eNVIDIA cuDNN Support: Supported\u003cbr\u003eNVIDIA TensorRT Support: Supported\u003cbr\u003eNVIDIA TensorRT-LLM Support: Supported\u003cbr\u003eNVIDIA Triton Inference Server Support: Supported\u003cbr\u003eNVIDIA RAPIDS Support: Supported\u003cbr\u003eNVIDIA NeMo Support: Supported\u003cbr\u003eNVIDIA NGC Container Support: Supported\u003cbr\u003eNVIDIA AI Enterprise Support: Supported\u003cbr\u003eNVIDIA GPUDirect RDMA: Supported\u003cbr\u003eNVIDIA GPUDirect Storage: Supported\u003cbr\u003eMixed-Precision AI Computing: Supported\u003cbr\u003eFP4 Tensor Processing: Supported\u003cbr\u003eFP8 Tensor Processing: Supported\u003cbr\u003eBF16 Tensor Processing: Supported\u003cbr\u003eAI Training Acceleration: Supported\u003cbr\u003eAI Fine-Tuning Acceleration: Supported\u003cbr\u003eAI Inferencing Acceleration: Supported\u003cbr\u003eGenerative AI Acceleration: Supported\u003cbr\u003eAI Reasoning Acceleration: Supported\u003cbr\u003eScientific Simulation Acceleration: Supported\u003cbr\u003eData Analytics Acceleration: Supported\u003cbr\u003eVisualisation Support: Configuration Dependent\u003cbr\u003eAdditional NVIDIA RTX PRO GPU Support: Configuration Dependent\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eStorage Specifications\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eStorage Technology: Enterprise NVMe Solid-State Drive\u003cbr\u003eStorage Interface: PCI Express NVMe\u003cbr\u003eStorage Generation: Configuration Dependent\u003cbr\u003eInstalled Storage Capacity: Configuration Dependent\u003cbr\u003ePrimary Boot Storage: NVMe SSD\u003cbr\u003eEnterprise NVMe SSD Support: Supported\u003cbr\u003eStorage Expansion: Configuration Dependent\u003cbr\u003eM.2 NVMe Storage Support: Configuration Dependent\u003cbr\u003ePCIe Storage Expansion: Supported, Configuration Dependent\u003cbr\u003eRAID Support: Configuration Dependent\u003cbr\u003eStorage Redundancy: Configuration Dependent\u003cbr\u003eSelf-Encrypting Drive Support: Drive and Configuration Dependent\u003cbr\u003eHigh-Speed AI Dataset Loading: Supported\u003cbr\u003eLarge AI Model Repository Support: Supported\u003cbr\u003eAI Model Checkpoint Storage: Supported\u003cbr\u003eVector Database Storage: Supported\u003cbr\u003eTraining Dataset Storage: Supported\u003cbr\u003eContainer Image Storage: Supported\u003cbr\u003eLocal Model Cache Support: Supported\u003cbr\u003eHigh-Speed Data Preprocessing: Supported\u003cbr\u003eContinuous Enterprise Read and Write Workloads: Supported\u003cbr\u003eStorage Health Monitoring: Configuration Dependent\u003cbr\u003eRemote Storage Status Monitoring: Configuration Dependent\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eNetworking Specifications\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eHigh-Speed Network Platform: NVIDIA ConnectX-8\u003cbr\u003eHigh-Speed Network Controller Quantity: 2\u003cbr\u003eHigh-Speed Network Ports: 2 × 400G\u003cbr\u003eMaximum Per-Port Network Bandwidth: Up to 400Gbps\u003cbr\u003eMaximum Aggregate Network Bandwidth: Up to 800Gbps\u003cbr\u003eNetwork Connector Type: Configuration Dependent\u003cbr\u003eNVIDIA ConnectX-8 SuperNIC Support: Supported\u003cbr\u003eHigh-Speed Ethernet Support: Supported\u003cbr\u003eInfiniBand Support: Configuration Dependent\u003cbr\u003eRDMA Support: Supported\u003cbr\u003eRoCE Support: Supported\u003cbr\u003eRoCE v2 Support: Supported\u003cbr\u003eNVIDIA GPUDirect RDMA: Supported\u003cbr\u003eNVIDIA GPUDirect Storage: Supported\u003cbr\u003eUltra-Low-Latency Networking: Supported\u003cbr\u003eHigh-Throughput Networking: Supported\u003cbr\u003eDistributed AI Training: Supported\u003cbr\u003eMulti-Node Model Training: Supported\u003cbr\u003eAI Cluster Interconnect: Supported\u003cbr\u003eHigh-Performance Storage Fabric: Supported\u003cbr\u003eScale-Out AI Infrastructure: Supported\u003cbr\u003eEnterprise AI Fabric Integration: Supported\u003cbr\u003eHigh-Performance Computing Cluster Support: Supported\u003cbr\u003eRapid Model Distribution: Supported\u003cbr\u003eLarge Dataset Transfer: Supported\u003cbr\u003eDatacentre Network Integration: Supported\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003ePorts \u0026amp; Expansion\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e2 × 400G NVIDIA ConnectX-8 High-Speed Network Connections\u003cbr\u003eEnterprise PCI Express Expansion: Supported\u003cbr\u003ePCIe Expansion Generation: Configuration Dependent\u003cbr\u003eAdditional NVIDIA RTX PRO GPU Expansion: Configuration Dependent\u003cbr\u003eHigh-Speed Storage Expansion: Supported\u003cbr\u003eEnterprise Network Adapter Expansion: Supported\u003cbr\u003eStorage Controller Expansion: Supported\u003cbr\u003eSpecialised Accelerator Expansion: Configuration Dependent\u003cbr\u003eUSB Connectivity: Configuration Dependent\u003cbr\u003eDisplay Connectivity: Configuration Dependent\u003cbr\u003eDedicated Management Interface: Configuration Dependent\u003cbr\u003eAudio Connectivity: Configuration Dependent\u003cbr\u003eRack Integration: Supported, Configuration Dependent\u003cbr\u003eFuture Enterprise Hardware Expansion: Supported\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional GPU Expansion\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eAdditional GPU Support: Up to 1 × NVIDIA RTX PRO Blackwell Generation GPU, Configuration Dependent\u003cbr\u003eProfessional Visualisation Acceleration: Supported with Optional GPU\u003cbr\u003eRay-Traced Rendering: Supported with Compatible Optional GPU\u003cbr\u003eAI-Assisted Rendering: Supported\u003cbr\u003eEngineering Simulation: Supported\u003cbr\u003eDigital Content Creation: Supported\u003cbr\u003eComputer-Aided Design: Supported\u003cbr\u003eComputer-Aided Engineering: Supported\u003cbr\u003eVisual Computing: Supported\u003cbr\u003eSynthetic Data Generation: Supported\u003cbr\u003eOmniverse Workloads: Supported\u003cbr\u003eDigital Twin Visualisation: Supported\u003cbr\u003eAI and Graphics Converged Workflows: Supported\u003cbr\u003eOptional GPU Availability: Configuration Dependent\u003cbr\u003eOptional GPU Power Requirement: Configuration Dependent\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eNVIDIA NVLink-C2C Architecture\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eCPU-GPU Interconnect: NVIDIA NVLink-C2C\u003cbr\u003eCoherent Interconnect: Supported\u003cbr\u003eUnified Memory Access: Supported\u003cbr\u003eHigh-Bandwidth Communication: Supported\u003cbr\u003eLow-Latency CPU-GPU Data Transfer: Supported\u003cbr\u003eShared Virtual Addressing: Supported\u003cbr\u003eHardware Cache Coherency: Supported\u003cbr\u003eReduced Data Movement: Supported\u003cbr\u003eImproved AI Pipeline Efficiency: Supported\u003cbr\u003eLarge Model Processing: Supported\u003cbr\u003eMemory-Intensive Data Science: Supported\u003cbr\u003eScientific Computing Acceleration: Supported\u003cbr\u003eIntegrated Superchip Communication: Supported\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eOperating System\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eOperating System Platform: NVIDIA AI-Optimised Linux\u003cbr\u003eOperating System Version: Configuration Dependent\u003cbr\u003eUbuntu Linux Compatibility: Supported\u003cbr\u003eNVIDIA GPU Driver Stack: Supported\u003cbr\u003eNVIDIA CUDA Development Environment: Supported\u003cbr\u003eNVIDIA Container Toolkit: Supported\u003cbr\u003eDocker Support: Supported\u003cbr\u003eKubernetes Support: Supported\u003cbr\u003ePython AI Development: Supported\u003cbr\u003eC++ CUDA Development: Supported\u003cbr\u003eAI Framework Compatibility: Supported\u003cbr\u003eRemote Administration: Supported\u003cbr\u003eCommand-Line Administration: Supported\u003cbr\u003eEnterprise Package Management: Supported\u003cbr\u003eSecurity Update Support: Supported\u003cbr\u003eContainerised Workload Support: Supported\u003cbr\u003eCloud-Native AI Development: Supported\u003cbr\u003eDatacentre Deployment Compatibility: Supported\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eNVIDIA AI Software Support\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eNVIDIA AI Enterprise\u003cbr\u003eNVIDIA CUDA Toolkit\u003cbr\u003eNVIDIA CUDA-X Libraries\u003cbr\u003eNVIDIA cuDNN\u003cbr\u003eNVIDIA TensorRT\u003cbr\u003eNVIDIA TensorRT-LLM\u003cbr\u003eNVIDIA Triton Inference Server\u003cbr\u003eNVIDIA NeMo\u003cbr\u003eNVIDIA NeMo Framework\u003cbr\u003eNVIDIA NeMo Retriever\u003cbr\u003eNVIDIA RAPIDS\u003cbr\u003eNVIDIA NGC Containers\u003cbr\u003eNVIDIA Container Toolkit\u003cbr\u003eNVIDIA NCCL\u003cbr\u003eNVIDIA Nsight Systems\u003cbr\u003eNVIDIA Nsight Compute\u003cbr\u003eNVIDIA Base Command Manager Compatibility\u003cbr\u003eNVIDIA Omniverse Compatibility\u003cbr\u003eNVIDIA NIM Microservices\u003cbr\u003eNVIDIA Blueprints\u003cbr\u003eNVIDIA AI Workbench\u003cbr\u003eNVIDIA DGX Cloud Integration\u003cbr\u003eNVIDIA Enterprise Support, Licence Dependent\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eAI Framework Support\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003ePyTorch\u003cbr\u003eTensorFlow\u003cbr\u003eJAX\u003cbr\u003eONNX Runtime\u003cbr\u003eHugging Face Transformers\u003cbr\u003eDeepSpeed\u003cbr\u003eMegatron-LM\u003cbr\u003evLLM\u003cbr\u003eTensorRT-LLM\u003cbr\u003eNVIDIA NeMo\u003cbr\u003eNVIDIA Triton Inference Server\u003cbr\u003eNVIDIA RAPIDS\u003cbr\u003eRay\u003cbr\u003eApache Spark\u003cbr\u003eMLflow\u003cbr\u003eKubeflow\u003cbr\u003eDocker\u003cbr\u003eKubernetes\u003cbr\u003eRed Hat OpenShift\u003cbr\u003eVector Database Platforms\u003cbr\u003eEnterprise MLOps Platforms\u003cbr\u003eDistributed Training Frameworks\u003cbr\u003eAI Model Serving Frameworks\u003cbr\u003eScientific Computing Libraries\u003cbr\u003ePython Development Frameworks\u003cbr\u003eCUDA C++ Development Tools\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eContainer \u0026amp; Orchestration Support\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eDocker Containers\u003cbr\u003eNVIDIA Container Toolkit\u003cbr\u003eNVIDIA NGC Containers\u003cbr\u003eKubernetes\u003cbr\u003eRed Hat OpenShift\u003cbr\u003eContainerised AI Development\u003cbr\u003eContainerised Model Training\u003cbr\u003eContainerised Model Inferencing\u003cbr\u003eGPU-Accelerated Containers\u003cbr\u003eCloud-Native AI Deployment\u003cbr\u003eEnterprise MLOps Integration\u003cbr\u003eWorkload Scheduling\u003cbr\u003eDistributed Training Orchestration\u003cbr\u003eModel Serving Orchestration\u003cbr\u003eMulti-User Development Environments\u003cbr\u003eReproducible AI Environments\u003cbr\u003ePrivate Cloud Integration\u003cbr\u003eHybrid Cloud Integration\u003cbr\u003eDatacentre Deployment Integration\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eSecurity Features\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eHP Enterprise Workstation Security\u003cbr\u003eSecure Boot Support\u003cbr\u003eHardware Root of Trust: Configuration Dependent\u003cbr\u003eTrusted Platform Module 2.0: Configuration Dependent\u003cbr\u003eFirmware Integrity Protection\u003cbr\u003eBIOS Protection\u003cbr\u003eSecure Firmware Update Support\u003cbr\u003eHardware-Based Platform Validation\u003cbr\u003ePlatform Integrity Verification\u003cbr\u003eSecure Operating System Environment\u003cbr\u003eRole-Based Administrative Access\u003cbr\u003eSecure Remote Management\u003cbr\u003eEncrypted Management Sessions\u003cbr\u003eManagement Network Isolation: Configuration Dependent\u003cbr\u003eSystem Event Logging\u003cbr\u003eAudit Logging\u003cbr\u003eData-at-Rest Encryption: Drive and Configuration Dependent\u003cbr\u003eSelf-Encrypting Drive Support: Configuration Dependent\u003cbr\u003eEnterprise Authentication Integration\u003cbr\u003ePhysical Security Features: Configuration Dependent\u003cbr\u003eSecure Model and Dataset Processing\u003cbr\u003eOn-Premise Data Control\u003cbr\u003ePrivate AI Workload Support\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eHP Enterprise Security Features\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eHP Sure Start: Configuration Dependent\u003cbr\u003eHP Sure Admin: Configuration Dependent\u003cbr\u003eHP Sure Run: Configuration Dependent\u003cbr\u003eHP Sure Recover: Configuration Dependent\u003cbr\u003eHP Sure Click: Operating System and Configuration Dependent\u003cbr\u003eHP BIOSphere: Configuration Dependent\u003cbr\u003eHP Secure Erase: Supported on Compatible Storage\u003cbr\u003eHP Tamper Lock: Configuration Dependent\u003cbr\u003eHP Client Security Manager: Configuration Dependent\u003cbr\u003ePlatform Certificate Support: Configuration Dependent\u003cbr\u003eEnterprise Device Identity: Configuration Dependent\u003cbr\u003eCentralised Security Management: Configuration Dependent\u003cbr\u003eSecurity Feature Availability: Dependent on Final HP Configuration\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eManagement Features\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eEnterprise Remote Management: Supported\u003cbr\u003eOut-of-Band Management: Configuration Dependent\u003cbr\u003eDedicated Management Controller: Configuration Dependent\u003cbr\u003eRemote Console Access: Configuration Dependent\u003cbr\u003eRemote Power Control: Configuration Dependent\u003cbr\u003eRemote System Reset: Configuration Dependent\u003cbr\u003eRemote Firmware Updates: Supported\u003cbr\u003eRemote BIOS Configuration: Supported\u003cbr\u003eSystem Health Monitoring: Supported\u003cbr\u003eProcessor Monitoring: Supported\u003cbr\u003eGPU Monitoring: Supported\u003cbr\u003eMemory Monitoring: Supported\u003cbr\u003eStorage Monitoring: Supported\u003cbr\u003eNetwork Monitoring: Supported\u003cbr\u003eTemperature Monitoring: Supported\u003cbr\u003eFan Monitoring: Supported\u003cbr\u003eVoltage Monitoring: Supported\u003cbr\u003ePower Monitoring: Supported\u003cbr\u003eHardware Inventory: Supported\u003cbr\u003eAsset Management: Supported\u003cbr\u003eSystem Event Logging: Supported\u003cbr\u003eAlert and Notification Support: Supported\u003cbr\u003eEnterprise Fleet Management: Supported\u003cbr\u003eHP Management Software Compatibility: Configuration Dependent\u003cbr\u003eDatacentre Management Integration: Supported\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eVirtualisation Features\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eContainer-Based Virtualisation: Supported\u003cbr\u003eVirtual Machine Support: Configuration Dependent\u003cbr\u003eGPU Virtualisation: Configuration Dependent\u003cbr\u003eMulti-User AI Development: Supported\u003cbr\u003eWorkload Isolation: Supported\u003cbr\u003eContainerised Development Environments: Supported\u003cbr\u003eCloud-Native AI Workloads: Supported\u003cbr\u003ePrivate Cloud Integration: Supported\u003cbr\u003eHybrid Cloud Integration: Supported\u003cbr\u003eEnterprise Resource Scheduling: Supported\u003cbr\u003eAI Workload Orchestration: Supported\u003cbr\u003eDevelopment Sandbox Support: Supported\u003cbr\u003eDepartment-Level Resource Allocation: Supported\u003cbr\u003eEnterprise MLOps Integration: Supported\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Science Features\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eIn-Memory Data Processing\u003cbr\u003eLarge Dataset Ingestion\u003cbr\u003eGPU-Accelerated Data Preparation\u003cbr\u003eGPU-Accelerated Data Analytics\u003cbr\u003eNVIDIA RAPIDS Support\u003cbr\u003eApache Spark Integration\u003cbr\u003eDataframe Acceleration\u003cbr\u003eMachine Learning Model Development\u003cbr\u003eStatistical Analysis\u003cbr\u003eFeature Engineering\u003cbr\u003eModel Validation\u003cbr\u003eModel Optimisation\u003cbr\u003eExperiment Tracking\u003cbr\u003eInteractive Data Science\u003cbr\u003eLarge Data Lake Processing\u003cbr\u003eLocal Dataset Processing\u003cbr\u003eReduced Cloud Data Transfer Requirements\u003cbr\u003ePrivate Data Analysis\u003cbr\u003eSensitive Dataset Processing\u003cbr\u003eScientific Visualisation, Configuration Dependent\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003ePower Specifications\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003ePower Supply Type: HP Enterprise High-Efficiency Power Supply\u003cbr\u003ePower Supply Capacity: Configuration Dependent\u003cbr\u003ePower Input: Configuration Dependent\u003cbr\u003ePower Consumption: Workload and Configuration Dependent\u003cbr\u003eHigh-Load AI Workload Support: Supported\u003cbr\u003eContinuous GPU Workload Support: Supported\u003cbr\u003eRemote Power Monitoring: Configuration Dependent\u003cbr\u003eRemote Power Control: Configuration Dependent\u003cbr\u003ePower Usage Reporting: Configuration Dependent\u003cbr\u003ePower Fault Monitoring: Supported\u003cbr\u003eEnterprise Power Management: Supported\u003cbr\u003eDatacentre Power Integration: Supported\u003cbr\u003eEnergy-Efficient AI Processing: Supported\u003cbr\u003ePower Supply Redundancy: Configuration Dependent\u003cbr\u003ePower Supply Efficiency Certification: Configuration Dependent\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eCooling \u0026amp; Reliability\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eProfessional Enterprise Workstation Cooling\u003cbr\u003eHigh-Efficiency Thermal Management\u003cbr\u003eDatacentre-Class Component Cooling\u003cbr\u003eCPU Thermal Monitoring\u003cbr\u003eGPU Thermal Monitoring\u003cbr\u003eMemory Thermal Monitoring\u003cbr\u003eStorage Thermal Monitoring\u003cbr\u003eVariable-Speed Fan Control\u003cbr\u003eAutomated Fan Management\u003cbr\u003eThermal Protection\u003cbr\u003eHardware Health Alerts\u003cbr\u003eLong-Duration AI Training Support\u003cbr\u003eContinuous AI Inferencing Support\u003cbr\u003e24×7 Operational Design\u003cbr\u003eEnterprise-Grade Components\u003cbr\u003eHigh-Bandwidth Component Cooling\u003cbr\u003eOptional GPU Cooling Support\u003cbr\u003eHigh-Speed Networking Cooling Support\u003cbr\u003eServiceable Thermal Components\u003cbr\u003eAcoustic Performance: Configuration Dependent\u003cbr\u003eDedicated Facility Cooling: Not Required for Standard Deskside Deployment\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompatibility\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eCompatible AI Workloads:\u003c\/p\u003e\n\u003cp\u003eLarge Language Models\u003cbr\u003eTrillion-Parameter Model Inferencing\u003cbr\u003eFoundation Models\u003cbr\u003eGenerative AI\u003cbr\u003eAI Agents\u003cbr\u003eAgentic AI\u003cbr\u003eReasoning Models\u003cbr\u003eRetrieval-Augmented Generation\u003cbr\u003eMultimodal AI\u003cbr\u003eComputer Vision\u003cbr\u003eNatural Language Processing\u003cbr\u003eSpeech AI\u003cbr\u003eRecommendation Engines\u003cbr\u003eScientific Machine Learning\u003cbr\u003ePredictive Analytics\u003cbr\u003eDigital Twins\u003cbr\u003eAutonomous Systems\u003cbr\u003eRobotics AI\u003cbr\u003eEnterprise AI Inferencing\u003cbr\u003eModel Training\u003cbr\u003eModel Fine-Tuning\u003cbr\u003eModel Optimisation\u003cbr\u003eModel Serving\u003cbr\u003eSynthetic Data Generation\u003cbr\u003eHigh-Performance Data Analytics\u003c\/p\u003e\n\u003cp\u003eCompatible Development Frameworks:\u003c\/p\u003e\n\u003cp\u003ePyTorch\u003cbr\u003eTensorFlow\u003cbr\u003eJAX\u003cbr\u003eONNX Runtime\u003cbr\u003eHugging Face Transformers\u003cbr\u003eDeepSpeed\u003cbr\u003eMegatron-LM\u003cbr\u003evLLM\u003cbr\u003eNVIDIA NeMo\u003cbr\u003eNVIDIA TensorRT\u003cbr\u003eNVIDIA TensorRT-LLM\u003cbr\u003eNVIDIA Triton Inference Server\u003cbr\u003eNVIDIA RAPIDS\u003c\/p\u003e\n\u003cp\u003eCompatible Deployment Platforms:\u003c\/p\u003e\n\u003cp\u003eNVIDIA AI Enterprise\u003cbr\u003eNVIDIA NGC\u003cbr\u003eDocker\u003cbr\u003eKubernetes\u003cbr\u003eRed Hat OpenShift\u003cbr\u003eEnterprise MLOps Platforms\u003cbr\u003ePrivate Cloud Infrastructure\u003cbr\u003eHybrid Cloud Infrastructure\u003cbr\u003eAI Factory Infrastructure\u003cbr\u003eScientific Computing Environments\u003cbr\u003eEnterprise DevOps Environments\u003cbr\u003eDatacentre AI Infrastructure\u003c\/p\u003e\n\u003cp\u003eCompatible Network Environments:\u003c\/p\u003e\n\u003cp\u003e400G High-Speed Networks\u003cbr\u003eNVIDIA ConnectX-8 Networking\u003cbr\u003eRDMA Networks\u003cbr\u003eRoCE Networks\u003cbr\u003eHigh-Performance Storage Networks\u003cbr\u003eDistributed AI Clusters\u003cbr\u003eHigh-Performance Computing Clusters\u003cbr\u003eEnterprise Ethernet Fabrics\u003cbr\u003eAI Factory Network Fabrics\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eDesign \u0026amp; Construction\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eProfessional Enterprise AI Workstation Design\u003cbr\u003eDeskside AI Supercomputer Architecture\u003cbr\u003eRack-Ready Deployment: Configuration Dependent\u003cbr\u003eHigh-Density Compute Platform\u003cbr\u003eDatacentre-Class Internal Architecture\u003cbr\u003eEnterprise Cable Management\u003cbr\u003eHigh-Speed Expansion Architecture\u003cbr\u003eServiceable Internal Components\u003cbr\u003eContinuous 24×7 Operational Design\u003cbr\u003eRemote Serviceability\u003cbr\u003eEnterprise Laboratory Deployment Ready\u003cbr\u003eDatacentre Integration Ready\u003cbr\u003eOffice and Engineering Workspace Ready\u003cbr\u003eAI Research Environment Ready\u003cbr\u003eProfessional HP Z Workstation Engineering\u003cbr\u003eTool-Less Service Access: Configuration Dependent\u003cbr\u003eChassis Security: Configuration Dependent\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eEnvironmental Specifications\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eOperating Environment: Enterprise Office, Research Laboratory or Datacentre\u003cbr\u003eOperating Temperature: Configuration Dependent\u003cbr\u003eStorage Temperature: Configuration Dependent\u003cbr\u003eOperating Humidity: Configuration Dependent\u003cbr\u003eStorage Humidity: Configuration Dependent\u003cbr\u003eMaximum Operating Altitude: Configuration Dependent\u003cbr\u003eThermal Monitoring: Supported\u003cbr\u003eEnvironmental Monitoring: Supported\u003cbr\u003eContinuous Operation: Supported\u003cbr\u003eENERGY STAR Certification: Configuration Dependent\u003cbr\u003eEPEAT Registration: Region and Configuration Dependent\u003cbr\u003eTCO Certification: Configuration Dependent\u003cbr\u003eRoHS Compliance: Region Dependent\u003cbr\u003eLow-Halogen Materials: Configuration Dependent\u003cbr\u003eSustainable Material Content: Configuration Dependent\u003cbr\u003eCompliance and Certifications: Region and Configuration Dependent\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhysical Specifications\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eProduct Type: Enterprise AI Workstation\u003cbr\u003eForm Factor: Deskside AI Supercomputer\u003cbr\u003eRack-Ready Capability: Configuration Dependent\u003cbr\u003eChassis Colour: Black, Configuration Dependent\u003cbr\u003eDimensions: Configuration Dependent\u003cbr\u003eSystem Weight: Configuration Dependent\u003cbr\u003eInstalled Weight: Configuration Dependent\u003cbr\u003eService Access: Enterprise Workstation Service Design\u003cbr\u003eInternal Expansion Access: Supported\u003cbr\u003eOptional GPU Access: Supported\u003cbr\u003eHigh-Speed Network Access: Dual 400G Connections\u003cbr\u003eRack Mounting Kit: Configuration Dependent\u003cbr\u003eCable Management Accessories: Configuration Dependent\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003ePackage Contents\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eHP ZGX Fury G1n AI Workstation\u003cbr\u003eNVIDIA GB300 Grace Blackwell Ultra Desktop Superchip\u003cbr\u003eNVIDIA Grace 72-Core CPU\u003cbr\u003eNVIDIA Blackwell Ultra GPU\u003cbr\u003e748GB Coherent Unified Memory\u003cbr\u003eDual NVIDIA ConnectX-8 400G Networking\u003cbr\u003ePre-Installed Operating System, Configuration Dependent\u003cbr\u003eNVIDIA AI Software Environment, Configuration Dependent\u003cbr\u003eHP Keyboard: Configuration Dependent\u003cbr\u003eHP Mouse: Configuration Dependent\u003cbr\u003ePower Cable\u003cbr\u003eQuick Installation Guide\u003cbr\u003eSafety Documentation\u003cbr\u003eWarranty Documentation\u003cbr\u003eHP Enterprise Support Information\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eKey Features\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eNVIDIA GB300 Grace Blackwell Ultra Desktop Superchip\u003cbr\u003eSingle NVIDIA Grace CPU\u003cbr\u003e72 Arm Neoverse V2 CPU Cores\u003cbr\u003eSingle NVIDIA Blackwell Ultra GPU\u003cbr\u003eFifth-Generation NVIDIA Tensor Cores\u003cbr\u003eSecond-Generation NVIDIA Transformer Engine\u003cbr\u003eUp to 20 PetaFLOPS FP4 AI Performance\u003cbr\u003e748GB Coherent Unified Memory\u003cbr\u003eUnified CPU-GPU Address Space\u003cbr\u003eNVIDIA NVLink-C2C Interconnect\u003cbr\u003eSupport for AI Models Up to 1 Trillion Parameters\u003cbr\u003eDual 400G NVIDIA ConnectX-8 Networking\u003cbr\u003eUp to 800Gbps Aggregate High-Speed Network Bandwidth\u003cbr\u003eNVIDIA GPUDirect RDMA Support\u003cbr\u003eNVIDIA GPUDirect Storage Support\u003cbr\u003eOptional NVIDIA RTX PRO Blackwell GPU Support\u003cbr\u003eNVIDIA AI Enterprise Ready\u003cbr\u003eNVIDIA CUDA-X Ready\u003cbr\u003eNVIDIA NGC Container Support\u003cbr\u003eLarge Language Model Training and Inferencing\u003cbr\u003eGenerative AI Development\u003cbr\u003eAgentic AI Development\u003cbr\u003eAI Reasoning Workloads\u003cbr\u003eEnterprise Data Science\u003cbr\u003eHigh-Performance Computing\u003cbr\u003eDeskside AI Supercomputer Design\u003cbr\u003eRack-Ready Deployment, Configuration Dependent\u003cbr\u003ePrivate and On-Premise AI Development\u003cbr\u003eEnterprise HP Security and Management\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003ePerformance \u0026amp; Features\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eThe HP ZGX Fury G1n is an enterprise AI workstation powered by the NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip. It integrates a 72-core NVIDIA Grace CPU based on the Arm Neoverse V2 architecture with an NVIDIA Blackwell Ultra GPU, creating a tightly coupled accelerated computing platform for large-scale artificial intelligence, data science and high-performance computing workloads.\u003c\/p\u003e\n\u003cp\u003eThe system delivers up to 20 petaFLOPS of FP4 AI compute performance through fifth-generation NVIDIA Tensor Cores and the second-generation NVIDIA Transformer Engine. Support for advanced low-precision data formats improves throughput for generative AI, agentic AI, reasoning models, large language model inferencing and other compute-intensive AI workloads.\u003c\/p\u003e\n\u003cp\u003eA total of 748GB coherent unified memory allows the NVIDIA Grace CPU and Blackwell Ultra GPU to access a shared memory pool through the NVIDIA NVLink-C2C interconnect. This architecture reduces unnecessary data movement between separate CPU and GPU memory spaces, improves processing efficiency and enables substantially larger AI models and datasets to run locally.\u003c\/p\u003e\n\u003cp\u003eThe large coherent memory pool enables the HP ZGX Fury G1n to support AI models containing up to one trillion parameters. This makes the workstation suitable for developing, fine-tuning and inferencing large language models, multimodal models, foundation models and autonomous AI agents without relying entirely on remote cloud infrastructure.\u003c\/p\u003e\n\u003cp\u003eDual NVIDIA ConnectX-8 400G network interfaces provide up to 800Gbps of aggregate high-speed connectivity. Support for RDMA, RoCE, NVIDIA GPUDirect RDMA and GPUDirect Storage enables low-latency communication between compute systems, storage platforms and GPU resources in distributed AI and high-performance computing environments.\u003c\/p\u003e\n\u003cp\u003eThe high-speed networking architecture allows the workstation to operate as an individual deskside AI system or as part of a larger AI development cluster. Organisations can use multiple systems for distributed model training, high-throughput dataset processing, model serving and collaborative AI research.\u003c\/p\u003e\n\u003cp\u003eOptional support for an additional NVIDIA RTX PRO Blackwell Generation GPU allows organisations to combine datacentre-class AI computing with professional graphics, ray-traced rendering, simulation, digital twins and advanced visualisation. Final optional GPU support depends on the selected HP system configuration.\u003c\/p\u003e\n\u003cp\u003eThe workstation supports the NVIDIA AI software platform, including CUDA, CUDA-X libraries, TensorRT, TensorRT-LLM, Triton Inference Server, NeMo, RAPIDS, NGC containers and NVIDIA AI Enterprise. It is compatible with commonly used frameworks such as PyTorch, TensorFlow, JAX, ONNX Runtime, Hugging Face Transformers and DeepSpeed.\u003c\/p\u003e\n\u003cp\u003eIts deskside form factor provides datacentre-class AI capabilities without requiring a specialised liquid-cooled rack installation. This allows AI development teams, researchers and data scientists to build and test large models locally while maintaining direct control over sensitive datasets, intellectual property and model assets.\u003c\/p\u003e\n\u003cp\u003eThe HP ZGX Fury G1n is designed to support a local-to-datacentre-to-cloud AI workflow. Models and applications can be developed and validated locally before being deployed to compatible NVIDIA-accelerated datacentre infrastructure or cloud platforms.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eTypical Use Cases\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eTrillion-Parameter Model Inferencing\u003cbr\u003eLarge Language Model Training\u003cbr\u003eLarge Language Model Fine-Tuning\u003cbr\u003eLarge Language Model Optimisation\u003cbr\u003eFoundation Model Development\u003cbr\u003eGenerative AI Application Development\u003cbr\u003eAI Agent Development\u003cbr\u003eAgentic AI Deployment\u003cbr\u003eAutonomous Long-Running AI Agents\u003cbr\u003eAI Reasoning Model Processing\u003cbr\u003eRetrieval-Augmented Generation\u003cbr\u003eMultimodal AI\u003cbr\u003eProduction AI Inferencing\u003cbr\u003eMachine Learning\u003cbr\u003eDeep Learning\u003cbr\u003eComputer Vision\u003cbr\u003eNatural Language Processing\u003cbr\u003eSpeech Recognition\u003cbr\u003eSpeech Generation\u003cbr\u003eRecommendation Systems\u003cbr\u003eEnterprise Knowledge Assistants\u003cbr\u003eCybersecurity AI\u003cbr\u003eFinancial Services AI\u003cbr\u003eFraud Detection\u003cbr\u003eHealthcare AI Research\u003cbr\u003eMedical Imaging Analysis\u003cbr\u003eDrug Discovery\u003cbr\u003eMolecular Simulation\u003cbr\u003eGenomics Research\u003cbr\u003eScientific Computing\u003cbr\u003eHigh-Performance Computing\u003cbr\u003eDigital Twin Simulation\u003cbr\u003eManufacturing AI\u003cbr\u003eAutonomous Systems Development\u003cbr\u003eRobotics Research\u003cbr\u003eSynthetic Data Generation\u003cbr\u003eGPU-Accelerated Data Science\u003cbr\u003eLarge Dataset Analytics\u003cbr\u003eUniversity Research Laboratories\u003cbr\u003eGovernment AI Infrastructure\u003cbr\u003ePrivate AI Development\u003cbr\u003eSovereign AI Infrastructure\u003cbr\u003eOn-Premise AI Deployment\u003cbr\u003eHybrid Cloud AI Development\u003cbr\u003eEnterprise MLOps\u003cbr\u003eMulti-User AI Development\u003cbr\u003eDistributed AI Training\u003cbr\u003eHigh-Speed AI Cluster Nodes\u003cbr\u003eEnterprise AI Factories\u003cbr\u003eProfessional Visualisation\u003cbr\u003eEngineering Simulation\u003cbr\u003eAI-Assisted Content Creation\u003c\/p\u003e\n\u003cp\u003e\u003ciframe title=\"YouTube video player\" src=\"https:\/\/www.youtube.com\/embed\/Yw98-kKYgfU?si=uzScSycLHz70uUv2\" height=\"315\" width=\"560\"\u003e\u003c\/iframe\u003e\u003c\/p\u003e","brand":"HP","offers":[{"title":"Default Title","offer_id":51421432807588,"sku":"ZGX Fury GB300","price":138000.0,"currency_code":"SGD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0605\/0136\/0804\/files\/HP_ZGX_Fury_G1n_GB300_AI_Workstation_with_NVIDIA_Blackwell_Ultra_4.png?v=1785228882","url":"https:\/\/sourceit.com.sg\/products\/hp-zgx-fury-g1n-gb300-ai-workstation-with-nvidia-blackwell-ultra","provider":"SourceIT ","version":"1.0","type":"link"}