{"product_id":"msi-xpertstation-ws300-nvidia-dgx-station-ai-supercomputer","title":"MSI XpertStation WS300 NVIDIA DGX Station AI Supercomputer","description":"\u003ch2\u003e\u003cstrong\u003eMSI XpertStation WS300 NVIDIA DGX Station with Grace Blackwell Ultra, 748GB Coherent Memory, 1.92TB RAID 1 \u0026amp; Dual 400G ConnectX-8 Networking -  Local Warranty \u003c\/strong\u003e\u003c\/h2\u003e\n\u003ch3 data-start=\"196\" data-end=\"261\" class=\"PDq2pG_selectionAnchorContainer\"\u003e\n\u003cstrong data-start=\"196\" data-end=\"259\"\u003eNVIDIA DGX Station Performance for Enterprise AI Innovation\u003c\/strong\u003e\u003cspan aria-hidden=\"true\" class=\"PDq2pG_selectionAnchor\"\u003e\u003c\/span\u003e\n\u003c\/h3\u003e\n\u003cp data-start=\"263\" data-end=\"1027\"\u003eThe MSI XpertStation WS300 is an enterprise-class AI supercomputer built on the NVIDIA DGX Station platform, delivering breakthrough performance for artificial intelligence, machine learning, and high-performance computing. Powered by the NVIDIA Grace Blackwell Ultra (GB300) Superchip, the system provides up to \u003cstrong data-start=\"576\" data-end=\"603\"\u003e20 PFLOPS of AI compute\u003c\/strong\u003e, enabling organisations to train, fine-tune, and deploy large language models (LLMs), AI agents, generative AI applications, computer vision models, and scientific simulations directly within their own secure infrastructure. It is purpose-built for enterprises, research institutions, universities, healthcare organisations, and AI development teams seeking workstation-class performance without relying on cloud resources.\u003c\/p\u003e\n\u003ch3 data-start=\"1029\" data-end=\"1084\"\u003e\u003cstrong data-start=\"1029\" data-end=\"1082\"\u003e748GB Coherent Unified Memory for Large AI Models\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp data-start=\"1086\" data-end=\"1581\"\u003eEquipped with an exceptional \u003cstrong data-start=\"1115\" data-end=\"1151\"\u003e748GB of coherent unified memory\u003c\/strong\u003e, the MSI XpertStation WS300 enables AI models and datasets to be processed efficiently without the memory limitations of conventional GPU workstations. This advanced memory architecture accelerates large-scale inferencing, retrieval-augmented generation (RAG), AI agent frameworks, engineering simulations, financial modelling, digital twins, and complex scientific research, delivering faster insights and improved productivity.\u003c\/p\u003e\n\u003ch3 data-start=\"1583\" data-end=\"1644\"\u003e\u003cstrong data-start=\"1583\" data-end=\"1642\"\u003eEnterprise Storage and Ultra-High-Speed 400G Networking\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp data-start=\"1646\" data-end=\"2177\"\u003eThe workstation includes \u003cstrong data-start=\"1671\" data-end=\"1726\"\u003e1.92TB enterprise NVMe storage configured in RAID 1\u003c\/strong\u003e for enhanced data protection and system reliability. Dual \u003cstrong data-start=\"1785\" data-end=\"1825\"\u003eNVIDIA ConnectX®-8 400GbE networking\u003c\/strong\u003e provides ultra-low latency communication and exceptional bandwidth, allowing seamless integration into AI clusters and distributed computing environments. Whether deployed as a standalone AI workstation or connected to larger AI infrastructures, the XpertStation WS300 delivers the networking performance required for today's most demanding workloads.\u003c\/p\u003e\n\u003ch3 data-start=\"2179\" data-end=\"2230\"\u003e\u003cstrong data-start=\"2179\" data-end=\"2228\"\u003eBuilt for Continuous Enterprise AI Operations\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp data-start=\"2232\" data-end=\"2752\"\u003eDesigned for mission-critical environments, the MSI XpertStation WS300 incorporates enterprise-grade reliability, advanced thermal management, remote administration capabilities, and NVIDIA Multi-Instance GPU (MIG) support for secure multi-user workloads. It is an ideal platform for private AI clouds, AI model development, cybersecurity research, healthcare analytics, engineering design, autonomous systems, and large-scale enterprise AI deployments where performance, scalability, and data sovereignty are essential.\u003c\/p\u003e\n\u003ch3 data-start=\"2754\" data-end=\"2796\"\u003e\u003cstrong data-start=\"2754\" data-end=\"2794\"\u003eTechnical Specifications\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp\u003e\u003cstrong\u003eGeneral\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eModel: MSI XpertStation WS300\u003cbr\u003eProduct Name: MSI XpertStation WS300 NVIDIA DGX Station with Grace Blackwell Ultra, 748GB Coherent Memory, 1.92TB RAID 1 \u0026amp; Dual 400G ConnectX-8 Networking\u003cbr\u003eManufacturer: MSI\u003cbr\u003eProduct Series: MSI XpertStation\u003cbr\u003eProduct Type: Enterprise AI Workstation \/ NVIDIA DGX Station-Class AI System\u003cbr\u003eCompute Platform: NVIDIA Grace Blackwell Ultra\u003cbr\u003eProcessor Architecture: NVIDIA Grace CPU + NVIDIA Blackwell Ultra GPU\u003cbr\u003eCPU Platform: Single NVIDIA Grace CPU Superchip\u003cbr\u003eGPU Platform: Single NVIDIA Blackwell Ultra GPU\u003cbr\u003eSystem Architecture: Unified CPU-GPU Accelerated Computing Platform\u003cbr\u003eMemory Architecture: NVIDIA Coherent Unified Memory\u003cbr\u003eTotal Coherent Memory: 748GB\u003cbr\u003eOperating System: Ubuntu 24.04 LTS\u003cbr\u003ePre-Installed Software: NVIDIA AI Developer Tools\u003cbr\u003ePrimary Storage: 1.92TB NVMe RAID 1\u003cbr\u003eStorage Expansion: 2 × PCIe 6.0 x4 M.2 2280 Slots Available\u003cbr\u003eHigh-Speed Networking: Dual NVIDIA ConnectX-8 400G QSFP112\u003cbr\u003eDedicated Management: 1000Base-T Server Management Port\u003cbr\u003eRemote Management Controller: ASPEED AST2600\u003cbr\u003eManagement Protocols: IPMI 2.0 and DMTF Redfish\u003cbr\u003eSecurity: Hardware Root of Trust and TPM 2.0\u003cbr\u003eTarget Deployment: Enterprise AI Development, AI Research, Model Training, Model Fine-Tuning, Inferencing, Scientific Computing and High-Performance Computing\u003cbr\u003eTarget Users: Enterprises, Government Agencies, Universities, Research Institutions, Data Scientists, AI Developers and Engineering Teams\u003cbr\u003eWarranty: MSI Enterprise Warranty, Configuration Dependent\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eProcessor Specifications\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eProcessor Platform: NVIDIA Grace CPU Superchip\u003cbr\u003eProcessor Quantity: 1\u003cbr\u003eCPU Architecture: Arm\u003cbr\u003eCPU Core Architecture: Arm Neoverse V2\u003cbr\u003eCPU Core Count: 72 Cores\u003cbr\u003eCPU Type: NVIDIA Grace\u003cbr\u003eSystem-on-Chip Architecture: Supported\u003cbr\u003eHigh-Bandwidth CPU-GPU Interconnect: Supported\u003cbr\u003eUnified CPU-GPU Address Space: Supported\u003cbr\u003eCoherent CPU-GPU Memory Access: Supported\u003cbr\u003eEnterprise Parallel Computing: Supported\u003cbr\u003eLarge-Scale AI Processing: Supported\u003cbr\u003eHigh-Performance Computing: Supported\u003cbr\u003eScientific Computing: Supported\u003cbr\u003eMulti-Threaded Workloads: Supported\u003cbr\u003eContinuous Enterprise Workloads: Supported\u003cbr\u003eOptimized for NVIDIA AI Software Stack\u003cbr\u003eOptimized for Generative AI Development\u003cbr\u003eOptimized for Large Language Model Processing\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eAI Performance\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eAI Compute Architecture: NVIDIA Blackwell Ultra\u003cbr\u003eAI Accelerator Quantity: 1\u003cbr\u003eGPU Type: NVIDIA Blackwell Ultra GPU\u003cbr\u003eTransformer Engine: NVIDIA Blackwell Ultra Transformer Engine\u003cbr\u003eTensor Core Acceleration: Supported\u003cbr\u003eMixed-Precision AI Computing: Supported\u003cbr\u003eFP4 AI Computing: Supported\u003cbr\u003eFP8 AI Computing: Supported\u003cbr\u003eFP16 AI Computing: Supported\u003cbr\u003eBF16 AI Computing: Supported\u003cbr\u003eINT8 Inferencing: Supported\u003cbr\u003eDynamic Precision Management: Supported\u003cbr\u003eLarge Language Model Acceleration: Supported\u003cbr\u003eFoundation Model Training: Supported\u003cbr\u003eFoundation Model Fine-Tuning: Supported\u003cbr\u003eGenerative AI Acceleration: Supported\u003cbr\u003eAI Agent Development: Supported\u003cbr\u003eReasoning Model Processing: Supported\u003cbr\u003eMultimodal AI Processing: Supported\u003cbr\u003eRetrieval-Augmented Generation: Supported\u003cbr\u003eProduction AI Inferencing: Supported\u003cbr\u003eScientific AI Processing: Supported\u003cbr\u003eDistributed AI Workloads: Supported\u003cbr\u003eEnterprise AI Development: Supported\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eAI Features\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eLarge Language Model Training\u003cbr\u003eLarge Language Model Fine-Tuning\u003cbr\u003eFoundation Model Development\u003cbr\u003eGenerative AI Applications\u003cbr\u003eAI Agent Development\u003cbr\u003eAgentic AI Workloads\u003cbr\u003eReasoning Models\u003cbr\u003eRetrieval-Augmented Generation\u003cbr\u003eMultimodal AI Processing\u003cbr\u003eNatural Language Processing\u003cbr\u003eComputer Vision\u003cbr\u003eSpeech Recognition\u003cbr\u003eSpeech Generation\u003cbr\u003eRecommendation Systems\u003cbr\u003ePredictive Analytics\u003cbr\u003eDigital Twin Simulation\u003cbr\u003eAutonomous Systems Development\u003cbr\u003eRobotics AI\u003cbr\u003eScientific Machine Learning\u003cbr\u003eHealthcare AI Research\u003cbr\u003eDrug Discovery\u003cbr\u003eMolecular Modelling\u003cbr\u003eFinancial Modelling\u003cbr\u003eCybersecurity AI\u003cbr\u003eManufacturing AI\u003cbr\u003eEnterprise Knowledge Assistants\u003cbr\u003ePrivate AI Deployment\u003cbr\u003eOn-Premise AI Development\u003cbr\u003eCloud-Native AI Deployment\u003cbr\u003eProduction AI Inferencing\u003cbr\u003eMulti-User AI Development\u003cbr\u003eNVIDIA AI Developer Environment\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\u003eMemory Coherency: Supported\u003cbr\u003eDirect CPU and GPU Memory Access: Supported\u003cbr\u003eHigh-Bandwidth Memory Architecture: Supported\u003cbr\u003eLow-Latency CPU-GPU Data Access: Supported\u003cbr\u003eReduced Memory Copy Operations: Supported\u003cbr\u003eLarge AI Model Loading: Supported\u003cbr\u003eLarge Context Window Processing: Supported\u003cbr\u003eMulti-Billion Parameter Model Support: Supported\u003cbr\u003eLarge Dataset Processing: Supported\u003cbr\u003eAI Model Fine-Tuning Support: Supported\u003cbr\u003eEnterprise Inferencing Support: Supported\u003cbr\u003eRetrieval-Augmented Generation Support: Supported\u003cbr\u003eVector Database Processing: Supported\u003cbr\u003eMulti-Tenant Memory Allocation: Supported\u003cbr\u003eContinuous AI Pipeline Processing: Supported\u003cbr\u003eScientific Simulation Support: Supported\u003cbr\u003eHigh-Performance Data Analytics: Supported\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eStorage Specifications\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003ePrimary Storage Technology: NVMe Solid-State Drive\u003cbr\u003ePrimary Storage Interface: PCI Express 5.0 x4\u003cbr\u003ePrimary Storage Form Factor: M.2 2280\u003cbr\u003eInstalled PCIe 5.0 M.2 Slots: 2\u003cbr\u003eInstalled Storage Configuration: 2 × M.2 2280 NVMe SSDs\u003cbr\u003eInstalled Usable RAID Capacity: 1.92TB\u003cbr\u003eRAID Configuration: RAID 1\u003cbr\u003eRAID Type: Mirrored Storage\u003cbr\u003eStorage Redundancy: Supported Through RAID 1\u003cbr\u003eData Protection: Drive Mirroring\u003cbr\u003ePrimary Storage Slot Status: Fully Populated\u003cbr\u003ePCIe 5.0 M.2 Slot Capacity: 2 × M.2 2280 NVMe PCIe 5.0 x4\u003cbr\u003ePCIe 6.0 M.2 Slot Capacity: 2 × M.2 2280 NVMe PCIe 6.0 x4\u003cbr\u003ePCIe 6.0 M.2 Slot Status: Open and Available for Expansion\u003cbr\u003eTotal M.2 Storage Slots: 4\u003cbr\u003eBoot Drive Support: Supported\u003cbr\u003eEnterprise NVMe SSD Support: Supported\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\u003eHigh-Speed Data Preprocessing: Supported\u003cbr\u003eContinuous Read and Write Workloads: Supported\u003cbr\u003eStorage Expansion: Supported\u003cbr\u003eStorage Health Monitoring: Supported\u003cbr\u003eRemote Storage Status Monitoring: Supported\u003cbr\u003eFuture PCIe 6.0 Storage Expansion: Supported\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eRAID Features\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eRAID Level: RAID 1\u003cbr\u003eRAID Configuration: Two-Drive Mirrored Array\u003cbr\u003eInstalled RAID Capacity: 1.92TB\u003cbr\u003ePrimary Purpose: Data Redundancy and Operating Continuity\u003cbr\u003eDrive Failure Protection: Supported for a Single Drive Failure\u003cbr\u003eMirrored Data Storage: Supported\u003cbr\u003eEnterprise Boot Volume Protection: Supported\u003cbr\u003eAI Development Environment Protection: Supported\u003cbr\u003eModel and Configuration Data Protection: Supported\u003cbr\u003eStorage Rebuild Support: Configuration Dependent\u003cbr\u003eRAID Monitoring: Supported\u003cbr\u003eDrive Health Monitoring: Supported\u003cbr\u003eRAID Status Reporting: Supported\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eGraphics Specifications\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eGPU Platform: NVIDIA Blackwell Ultra\u003cbr\u003eGPU Quantity: 1\u003cbr\u003eGPU Type: Enterprise AI and HPC Accelerator\u003cbr\u003eTensor Cores: NVIDIA Tensor Cores\u003cbr\u003eTransformer Engine: Supported\u003cbr\u003eCUDA Parallel Computing: Supported\u003cbr\u003eCUDA Toolkit Compatibility: Supported\u003cbr\u003eNVIDIA cuDNN Compatibility: Supported\u003cbr\u003eNVIDIA TensorRT Compatibility: Supported\u003cbr\u003eNVIDIA RAPIDS Compatibility: Supported\u003cbr\u003eNVIDIA NeMo Compatibility: Supported\u003cbr\u003eNVIDIA NGC Container Compatibility: Supported\u003cbr\u003eNVIDIA AI Enterprise Compatibility: Supported\u003cbr\u003eGPUDirect RDMA: Supported\u003cbr\u003eGPUDirect Storage: Supported\u003cbr\u003eMixed-Precision Computing: Supported\u003cbr\u003eLarge Language Model Acceleration: Supported\u003cbr\u003eGenerative AI Acceleration: Supported\u003cbr\u003eScientific Simulation Acceleration: Supported\u003cbr\u003eHigh-Performance Data Analytics: Supported\u003cbr\u003eAI Training: Supported\u003cbr\u003eAI Fine-Tuning: Supported\u003cbr\u003eProduction Inferencing: Supported\u003cbr\u003eMulti-Modal AI Processing: Supported\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eNetworking Specifications\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eHigh-Speed Network Controller: NVIDIA ConnectX-8 SuperNIC\u003cbr\u003eHigh-Speed Network Controller Quantity: 2\u003cbr\u003eHigh-Speed Network Ports: 2 × 400G QSFP112\u003cbr\u003eConnector Type: QSFP112\u003cbr\u003eMaximum Per-Port Bandwidth: Up to 400Gbps\u003cbr\u003eMaximum Aggregate Network Bandwidth: Up to 800Gbps\u003cbr\u003eEthernet Support: Supported\u003cbr\u003eRDMA Support: Supported\u003cbr\u003eRoCE Support: Supported\u003cbr\u003eGPUDirect RDMA: Supported\u003cbr\u003eGPUDirect Storage: Supported\u003cbr\u003eUltra-Low-Latency Networking: Supported\u003cbr\u003eDistributed AI Training: Supported\u003cbr\u003eAI Cluster Interconnect: Supported\u003cbr\u003eHigh-Speed Storage Fabric: Supported\u003cbr\u003eScale-Out AI Infrastructure: Supported\u003cbr\u003eEnterprise AI Fabric Integration: Supported\u003cbr\u003eMulti-Node Model Training: Supported\u003cbr\u003eHigh-Performance Computing Cluster Support: Supported\u003cbr\u003eLow-Latency Data Transfer: Supported\u003cbr\u003eHigh-Throughput Model Distribution: Supported\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eDedicated Management Networking\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eDedicated Management Port: 1 × 1000Base-T\u003cbr\u003eManagement Network Speed: 1GbE\u003cbr\u003eConnector Type: RJ-45\u003cbr\u003eManagement Port Function: Dedicated Out-of-Band Server Management\u003cbr\u003eManagement Network Isolation: Supported\u003cbr\u003eRemote Management Without Host Operating System: Supported\u003cbr\u003eRemote Power Control: Supported\u003cbr\u003eRemote Console Access: Supported\u003cbr\u003eRemote Firmware Management: Supported\u003cbr\u003eSystem Health Monitoring: Supported\u003cbr\u003eEvent Logging: Supported\u003cbr\u003eEnterprise Datacentre Integration: Supported\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003ePorts \u0026amp; Expansion\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e2 × 400G QSFP112 Ports with NVIDIA ConnectX-8 SuperNICs\u003cbr\u003e1 × 1000Base-T Dedicated Server Management Port\u003cbr\u003e2 × M.2 2280 PCIe 5.0 x4 NVMe Slots, Populated\u003cbr\u003e2 × M.2 2280 PCIe 6.0 x4 NVMe Slots, Available for Expansion\u003cbr\u003e3 × PCIe 5.0 Expansion Slots\u003cbr\u003eEnterprise Network Expansion Support\u003cbr\u003eHigh-Speed Storage Expansion Support\u003cbr\u003eAdditional Accelerator Expansion: Configuration Dependent\u003cbr\u003eFuture PCIe Device Expansion: Supported\u003cbr\u003eDedicated BMC Management Interface: Supported\u003cbr\u003eDatacentre Network Integration: Supported\u003cbr\u003eAI Cluster Expansion: Supported\u003cbr\u003eHigh-Performance Storage Connectivity: Supported\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003ePCIe Expansion Specifications\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003ePCIe Expansion Slot Count: 3\u003cbr\u003ePCIe Generation: PCI Express 5.0\u003cbr\u003eExpansion Use Cases: High-Speed Networking, Storage Controllers, Data Acquisition, Additional Accelerators and Enterprise I\/O\u003cbr\u003ePCIe 5.0 Device Support: Supported\u003cbr\u003eEnterprise Add-In Card Support: Supported\u003cbr\u003eHigh-Bandwidth Peripheral Support: Supported\u003cbr\u003eLow-Latency Expansion: Supported\u003cbr\u003eFuture Hardware Expansion: Supported\u003cbr\u003eGPU and Accelerator Expansion: Configuration Dependent\u003cbr\u003eStorage Controller Expansion: Supported\u003cbr\u003eNetwork Interface Expansion: Supported\u003cbr\u003eSpecialized AI Hardware Expansion: Supported\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eOperating System\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003ePre-Installed Operating System: Ubuntu 24.04 LTS\u003cbr\u003eOperating System Type: 64-Bit Linux\u003cbr\u003eLong-Term Support Release: Supported\u003cbr\u003eEnterprise Linux Environment: Supported\u003cbr\u003eNVIDIA Driver Stack: Pre-Installed\u003cbr\u003eNVIDIA AI Developer Tools: Pre-Installed\u003cbr\u003eCUDA Development Environment: Pre-Installed or Ready\u003cbr\u003eNVIDIA Container Toolkit: Supported\u003cbr\u003eDocker Support: Supported\u003cbr\u003eKubernetes Support: Supported\u003cbr\u003ePython AI 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\u003eLong-Term Software Maintenance: Supported\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003ePre-Installed NVIDIA AI Developer Tools\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eNVIDIA GPU Drivers\u003cbr\u003eNVIDIA CUDA Toolkit\u003cbr\u003eNVIDIA Container Toolkit\u003cbr\u003eNVIDIA NGC Container Support\u003cbr\u003eNVIDIA TensorRT\u003cbr\u003eNVIDIA cuDNN\u003cbr\u003eNVIDIA Triton Inference Server Support\u003cbr\u003eNVIDIA NeMo Support\u003cbr\u003eNVIDIA RAPIDS Support\u003cbr\u003ePyTorch Support\u003cbr\u003eTensorFlow Support\u003cbr\u003eJAX Support\u003cbr\u003eONNX Runtime Support\u003cbr\u003eHugging Face Transformers Support\u003cbr\u003eDocker Container Support\u003cbr\u003eKubernetes Integration Support\u003cbr\u003eAI Model Development Tools\u003cbr\u003eAI Model Optimization Tools\u003cbr\u003eAI Model Serving Tools\u003cbr\u003eEnterprise AI Deployment Tools\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eManagement Controller\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eManagement Controller: ASPEED AST2600\u003cbr\u003eManagement Type: Integrated Baseboard Management Controller\u003cbr\u003eOut-of-Band Management: Supported\u003cbr\u003eIPMI Version: IPMI 2.0\u003cbr\u003eDMTF Redfish Support: Supported\u003cbr\u003eRemote KVM Access: Supported\u003cbr\u003eRemote Console Access: Supported\u003cbr\u003eRemote Power On: Supported\u003cbr\u003eRemote Power Off: Supported\u003cbr\u003eRemote Power Cycle: Supported\u003cbr\u003eRemote System Reset: Supported\u003cbr\u003eRemote Firmware Updates: Supported\u003cbr\u003eRemote BIOS Configuration: Supported\u003cbr\u003eVirtual Media Support: Configuration Dependent\u003cbr\u003eSystem Event Log: Supported\u003cbr\u003eSensor 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\u003eEnterprise Fleet Management: Supported\u003cbr\u003eManagement API Integration: Supported\u003cbr\u003eAutomated Datacentre Management: Supported\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eIPMI 2.0 Features\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eRemote Hardware Monitoring\u003cbr\u003eOut-of-Band System Management\u003cbr\u003eRemote Power Control\u003cbr\u003eSystem Event Logging\u003cbr\u003eSensor Data Monitoring\u003cbr\u003eHardware Alerting\u003cbr\u003eIndependent Management Processor\u003cbr\u003eManagement Without Host OS Access\u003cbr\u003eRemote Troubleshooting\u003cbr\u003eEnterprise Management Platform Integration\u003cbr\u003eUser and Role Management\u003cbr\u003eSecure Management Sessions\u003cbr\u003eHardware Status Reporting\u003cbr\u003eAutomated Alert Generation\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eDMTF Redfish Features\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eRESTful Management API\u003cbr\u003eStandards-Based Server Management\u003cbr\u003eRemote Hardware Inventory\u003cbr\u003eRemote Power Management\u003cbr\u003eRemote Firmware Management\u003cbr\u003eSystem Health Reporting\u003cbr\u003eStorage Monitoring\u003cbr\u003eNetwork Monitoring\u003cbr\u003eThermal Monitoring\u003cbr\u003ePower Consumption Monitoring\u003cbr\u003eAutomation and Orchestration Support\u003cbr\u003eDatacentre Management Software Integration\u003cbr\u003eEnterprise Fleet Management Integration\u003cbr\u003eScripted Management Operations\u003cbr\u003eSecure API-Based Administration\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eSecurity Features\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eHardware Root of Trust\u003cbr\u003eTrusted Platform Module 2.0\u003cbr\u003eSecure Boot Support\u003cbr\u003eFirmware Integrity Protection\u003cbr\u003eHardware-Based Platform Validation\u003cbr\u003eSecure Firmware Update Support\u003cbr\u003eBIOS Security Support\u003cbr\u003eBMC User Authentication\u003cbr\u003eRole-Based Access Control\u003cbr\u003eSecure Remote Management\u003cbr\u003eEncrypted Management Sessions\u003cbr\u003eManagement Network Isolation\u003cbr\u003eSystem Event Logging\u003cbr\u003eAudit Logging\u003cbr\u003eSecure Boot Chain\u003cbr\u003ePlatform Integrity Verification\u003cbr\u003eEnterprise Authentication Integration\u003cbr\u003eData-at-Rest Protection: Drive Dependent\u003cbr\u003eRAID 1 Data Redundancy\u003cbr\u003eSecure Operating System Environment\u003cbr\u003eUbuntu Security Updates\u003cbr\u003eNVIDIA Driver Security Updates\u003cbr\u003ePhysical Security Features: Configuration Dependent\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eHardware Root of Trust\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eHardware-Based Boot Validation\u003cbr\u003eFirmware Authenticity Verification\u003cbr\u003ePlatform Integrity Checking\u003cbr\u003eProtection Against Unauthorized Firmware\u003cbr\u003eSecure Firmware Recovery Support\u003cbr\u003eTrusted Startup Process\u003cbr\u003eBMC Firmware Security\u003cbr\u003eBIOS Integrity Protection\u003cbr\u003eEnterprise Platform Attestation\u003cbr\u003eSecure Component Authentication\u003cbr\u003eProtection Against Low-Level System Tampering\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrusted Platform Module\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eTPM Version: TPM 2.0\u003cbr\u003eHardware-Backed Cryptographic Storage\u003cbr\u003ePlatform Identity Protection\u003cbr\u003eSecure Key Storage\u003cbr\u003eMeasured Boot Support\u003cbr\u003eDevice Authentication Support\u003cbr\u003eDisk Encryption Integration\u003cbr\u003eOperating System Security Integration\u003cbr\u003eEnterprise Certificate Support\u003cbr\u003eSecure Credential Protection\u003cbr\u003ePlatform Integrity Measurement\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eVirtualisation \u0026amp; Container Support\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eDocker Support\u003cbr\u003eKubernetes Support\u003cbr\u003eNVIDIA Container Toolkit\u003cbr\u003eNVIDIA NGC Containers\u003cbr\u003eContainerised AI Development\u003cbr\u003eContainerised Model Training\u003cbr\u003eContainerised Inferencing\u003cbr\u003eVirtual Machine Support: Configuration Dependent\u003cbr\u003eCloud-Native AI Deployment\u003cbr\u003eEnterprise MLOps Platforms\u003cbr\u003eWorkload Orchestration\u003cbr\u003eMulti-User Development Environments\u003cbr\u003eResource Scheduling\u003cbr\u003eAI Development Sandboxes\u003cbr\u003eDevOps and MLOps Integration\u003cbr\u003ePrivate Cloud Integration\u003cbr\u003eHybrid Cloud Integration\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eSoftware \u0026amp; AI Framework Support\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eNVIDIA CUDA Toolkit\u003cbr\u003eNVIDIA cuDNN\u003cbr\u003eNVIDIA TensorRT\u003cbr\u003eNVIDIA Triton Inference Server\u003cbr\u003eNVIDIA NeMo\u003cbr\u003eNVIDIA RAPIDS\u003cbr\u003eNVIDIA NGC Containers\u003cbr\u003ePyTorch\u003cbr\u003eTensorFlow\u003cbr\u003eJAX\u003cbr\u003eONNX Runtime\u003cbr\u003eHugging Face Transformers\u003cbr\u003eDeepSpeed\u003cbr\u003eMegatron-LM\u003cbr\u003eDocker\u003cbr\u003eKubernetes\u003cbr\u003eMLflow\u003cbr\u003eRay\u003cbr\u003eApache Spark\u003cbr\u003eVector Database Platforms\u003cbr\u003eEnterprise MLOps Platforms\u003cbr\u003eAI Model Serving Frameworks\u003cbr\u003eDistributed Training Frameworks\u003cbr\u003eScientific Computing Libraries\u003cbr\u003ePython Development Tools\u003cbr\u003eC++ CUDA Development Tools\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eCooling \u0026amp; Reliability\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eEnterprise Workstation Cooling Architecture\u003cbr\u003eHigh-Efficiency Thermal Management\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\u003eContinuous AI Workload Support\u003cbr\u003eLong-Duration AI Training Support\u003cbr\u003eEnterprise-Grade Components\u003cbr\u003e24×7 Operational Design\u003cbr\u003eHigh-Bandwidth Component Cooling\u003cbr\u003ePCIe Expansion Cooling Support\u003cbr\u003eHigh-Speed NVMe Cooling Support\u003cbr\u003eDatacentre and Laboratory Deployment Ready\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003ePower Specifications\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003ePower Supply Type: Enterprise High-Efficiency Power Supply\u003cbr\u003ePower Supply Capacity: Configuration Dependent\u003cbr\u003eInput Voltage: Configuration Dependent\u003cbr\u003ePower Consumption: Workload and Configuration Dependent\u003cbr\u003eRemote Power Monitoring: Supported\u003cbr\u003eRemote Power Control: Supported\u003cbr\u003ePower Usage Reporting: Supported\u003cbr\u003ePower Fault Monitoring: Supported\u003cbr\u003eContinuous High-Performance Operation: Supported\u003cbr\u003eHigh-Load GPU Workload Support: Supported\u003cbr\u003eEnterprise Power Management: Supported\u003cbr\u003eDatacentre Power Monitoring Integration: Supported\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\u003eFoundation Models\u003cbr\u003eGenerative AI\u003cbr\u003eAI Agents\u003cbr\u003eAgentic AI\u003cbr\u003eRetrieval-Augmented Generation\u003cbr\u003eReasoning Models\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\u003eEnterprise AI Inferencing\u003cbr\u003eModel Training\u003cbr\u003eModel Fine-Tuning\u003cbr\u003eModel Optimization\u003cbr\u003eModel Serving\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\u003eNVIDIA NeMo\u003cbr\u003eNVIDIA TensorRT\u003cbr\u003eNVIDIA Triton Inference Server\u003cbr\u003eNVIDIA RAPIDS\u003c\/p\u003e\n\u003cp\u003eCompatible Deployment Platforms:\u003c\/p\u003e\n\u003cp\u003eUbuntu 24.04 LTS\u003cbr\u003eDocker\u003cbr\u003eKubernetes\u003cbr\u003eNVIDIA NGC\u003cbr\u003eEnterprise MLOps Platforms\u003cbr\u003ePrivate Cloud Infrastructure\u003cbr\u003eHybrid Cloud Infrastructure\u003cbr\u003eAI Factory Infrastructure\u003cbr\u003eScientific Computing Environments\u003cbr\u003eEnterprise DevOps Environments\u003c\/p\u003e\n\u003cp\u003eCompatible Network Environments:\u003c\/p\u003e\n\u003cp\u003e400G Ethernet Fabrics\u003cbr\u003eNVIDIA ConnectX-8 Networking\u003cbr\u003eQSFP112 Infrastructure\u003cbr\u003eRDMA Networks\u003cbr\u003eRoCE Networks\u003cbr\u003eHigh-Performance Storage Networks\u003cbr\u003eDistributed AI Clusters\u003cbr\u003eHigh-Performance Computing Clusters\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eDesign \u0026amp; Construction\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eEnterprise AI Workstation Design\u003cbr\u003eProfessional NVIDIA DGX Station-Class Architecture\u003cbr\u003eHigh-Density Compute Platform\u003cbr\u003eHigh-Bandwidth Internal Architecture\u003cbr\u003eServiceable Internal Components\u003cbr\u003eEnterprise Cable Management\u003cbr\u003eDedicated Management Controller\u003cbr\u003eHigh-Speed Expansion Architecture\u003cbr\u003eContinuous 24×7 Operational Design\u003cbr\u003eRemote Serviceability\u003cbr\u003eEnterprise Laboratory Deployment Ready\u003cbr\u003eDatacentre Integration Ready\u003cbr\u003eAI Research Environment Ready\u003cbr\u003eOffice and Engineering Workspace Deployment Ready\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\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: Professional AI Station\u003cbr\u003eChassis Colour: Configuration Dependent\u003cbr\u003eDimensions: Configuration Dependent\u003cbr\u003eSystem Weight: Configuration Dependent\u003cbr\u003eService Access: Enterprise Service Design\u003cbr\u003eExpansion Access: Supported\u003cbr\u003eInternal M.2 Access: Supported\u003cbr\u003ePCIe Expansion Access: Supported\u003cbr\u003eManagement Port Access: Dedicated Rear I\/O\u003cbr\u003eHigh-Speed Network Port Access: Dual QSFP112\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003ePackage Contents\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eMSI XpertStation WS300 AI System\u003cbr\u003eNVIDIA Grace CPU Superchip\u003cbr\u003eNVIDIA Blackwell Ultra GPU\u003cbr\u003e748GB Coherent Unified Memory\u003cbr\u003e1.92TB RAID 1 NVMe Storage Configuration\u003cbr\u003eUbuntu 24.04 LTS\u003cbr\u003eNVIDIA AI Developer Tools\u003cbr\u003ePower Cable\u003cbr\u003eQuick Installation Guide\u003cbr\u003eSafety Documentation\u003cbr\u003eWarranty Documentation\u003cbr\u003eEnterprise Support Information\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eKey Features\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eSingle NVIDIA Grace CPU Superchip\u003cbr\u003e72 Arm Neoverse V2 CPU Cores\u003cbr\u003eSingle NVIDIA Blackwell Ultra GPU\u003cbr\u003e748GB Coherent Unified Memory\u003cbr\u003eUnified CPU-GPU Memory Architecture\u003cbr\u003e2 × M.2 2280 PCIe 5.0 x4 NVMe Slots\u003cbr\u003eInstalled 1.92TB RAID 1 Storage\u003cbr\u003e2 × M.2 2280 PCIe 6.0 x4 NVMe Expansion Slots\u003cbr\u003e3 × PCIe 5.0 Expansion Slots\u003cbr\u003eUbuntu 24.04 LTS Pre-Installed\u003cbr\u003eNVIDIA AI Developer Tools Pre-Installed\u003cbr\u003e2 × 400G QSFP112 Network Ports\u003cbr\u003eDual NVIDIA ConnectX-8 SuperNICs\u003cbr\u003eUp to 800Gbps Aggregate High-Speed Networking\u003cbr\u003e1 × Dedicated 1000Base-T Management Port\u003cbr\u003eASPEED AST2600 BMC\u003cbr\u003eIPMI 2.0 Support\u003cbr\u003eDMTF Redfish Support\u003cbr\u003eHardware Root of Trust\u003cbr\u003eTPM 2.0 Support\u003cbr\u003eEnterprise Remote Management\u003cbr\u003eAI Training and Fine-Tuning Ready\u003cbr\u003eProduction Inferencing Ready\u003cbr\u003eHigh-Performance Computing Ready\u003cbr\u003eEnterprise AI Development Platform\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003ePerformance \u0026amp; Features\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eThe MSI XpertStation WS300 is an enterprise AI workstation built around the NVIDIA Grace Blackwell Ultra platform. It combines a single NVIDIA Grace CPU Superchip featuring 72 Arm Neoverse V2 cores with a single NVIDIA Blackwell Ultra GPU, providing a tightly integrated computing architecture for large-scale AI development, model training, fine-tuning, inferencing and scientific computing.\u003c\/p\u003e\n\u003cp\u003eThe system includes 748GB of coherent unified memory, allowing the NVIDIA Grace CPU and Blackwell Ultra GPU to access a shared memory pool. This architecture reduces the need to copy data between separate processor and graphics memory spaces, enabling more efficient processing of large language models, long-context workloads, multimodal models, vector databases and memory-intensive scientific applications.\u003c\/p\u003e\n\u003cp\u003ePrimary storage is configured with two M.2 2280 NVMe PCIe 5.0 x4 drives in a 1.92TB RAID 1 array. RAID 1 mirrors data across both drives to improve storage resilience and protect the operating system, AI development tools, model configurations and application data against the failure of a single drive.\u003c\/p\u003e\n\u003cp\u003eFor future storage expansion, the workstation includes two additional M.2 2280 NVMe PCIe 6.0 x4 slots. These slots are open and available for high-speed storage upgrades, enabling organisations to expand capacity for AI datasets, model checkpoints, vector databases, container images and local inference repositories.\u003c\/p\u003e\n\u003cp\u003eThree PCIe 5.0 expansion slots provide additional flexibility for enterprise networking adapters, storage controllers, specialist data acquisition cards and other high-bandwidth PCIe devices. This allows the workstation to be adapted for different AI, engineering, research and high-performance computing environments.\u003c\/p\u003e\n\u003cp\u003eThe MSI XpertStation WS300 includes dual NVIDIA ConnectX-8 SuperNICs with two 400G QSFP112 ports. The network interfaces provide up to 800Gbps of aggregate high-speed connectivity for distributed AI training, cluster communication, high-performance storage fabrics and low-latency data transfer between AI systems.\u003c\/p\u003e\n\u003cp\u003eA dedicated 1000Base-T server management port connects directly to the integrated ASPEED AST2600 baseboard management controller. This provides independent out-of-band access for remote power control, hardware monitoring, system event logging, diagnostics, firmware management and remote administration even when the main operating system is unavailable.\u003c\/p\u003e\n\u003cp\u003eSupport for IPMI 2.0 and DMTF Redfish enables integration with enterprise datacentre management platforms, automation tools and infrastructure monitoring systems. Administrators can use standards-based interfaces to manage hardware inventory, monitor system health, automate lifecycle operations and remotely troubleshoot the workstation.\u003c\/p\u003e\n\u003cp\u003eHardware Root of Trust and TPM 2.0 provide hardware-backed platform protection, firmware validation, secure key storage, measured boot and operating system security integration. These capabilities help protect the workstation against unauthorised firmware changes and support enterprise security requirements.\u003c\/p\u003e\n\u003cp\u003eUbuntu 24.04 LTS is pre-installed together with NVIDIA AI Developer Tools, providing a ready-to-use software environment for CUDA development, AI framework deployment, containerised workloads, model optimisation and production inference. The platform supports leading AI frameworks including PyTorch, TensorFlow, JAX, Hugging Face Transformers, TensorRT, Triton Inference Server, NeMo and RAPIDS.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eTypical Use Cases\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eLarge Language Model Training\u003cbr\u003eLarge Language Model Fine-Tuning\u003cbr\u003eFoundation Model Development\u003cbr\u003eGenerative AI Application Development\u003cbr\u003eAI Agent Development\u003cbr\u003eAgentic AI Deployment\u003cbr\u003eRetrieval-Augmented Generation\u003cbr\u003eReasoning Model Processing\u003cbr\u003eMultimodal AI\u003cbr\u003eProduction AI Inferencing\u003cbr\u003eMachine Learning\u003cbr\u003eDeep Learning\u003cbr\u003eComputer Vision\u003cbr\u003eNatural Language Processing\u003cbr\u003eSpeech AI\u003cbr\u003eRecommendation Systems\u003cbr\u003eEnterprise Knowledge Assistants\u003cbr\u003eCybersecurity AI\u003cbr\u003eFinancial Services AI\u003cbr\u003eHealthcare AI Research\u003cbr\u003eDrug Discovery\u003cbr\u003eMolecular Simulation\u003cbr\u003eScientific Computing\u003cbr\u003eHigh-Performance Computing\u003cbr\u003eDigital Twin Simulation\u003cbr\u003eManufacturing AI\u003cbr\u003eAutonomous Systems Development\u003cbr\u003eRobotics Research\u003cbr\u003eUniversity Research Laboratories\u003cbr\u003eGovernment AI Infrastructure\u003cbr\u003ePrivate AI Development\u003cbr\u003eOn-Premise AI Deployment\u003cbr\u003eHybrid Cloud AI Development\u003cbr\u003eEnterprise MLOps\u003cbr\u003eMulti-User AI Development\u003cbr\u003eHigh-Speed AI Cluster Nodes\u003cbr\u003eDistributed AI Training\u003cbr\u003eEnterprise AI Factories\u003c\/p\u003e","brand":"Nvidia","offers":[{"title":"Default Title","offer_id":51421413441700,"sku":"XpertStation WS300","price":138000.0,"currency_code":"SGD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0605\/0136\/0804\/files\/MSIXpertStationWS300NVIDIADGXStationAISupercomputer.png?v=1785226724","url":"https:\/\/sourceit.com.sg\/products\/msi-xpertstation-ws300-nvidia-dgx-station-ai-supercomputer","provider":"SourceIT ","version":"1.0","type":"link"}