{"product_id":"msi-xpertstation-ws300-nvidia-dgx-station-ai-supercomputer-1","title":"MSI XpertStation WS300 NVIDIA DGX Station AI Supercomputer - ( Contact Us for Pricing )","description":"\u003cp style=\"margin:1em 0\"\u003eThe MSI XpertStation WS300 is an enterprise desktop AI supercomputer built on the NVIDIA DGX Station GB300 platform. Powered by the NVIDIA Grace Blackwell Ultra Desktop Superchip, it delivers up to 20 PFLOPS of FP4 Tensor Core performance with 748 GB of coherent unified memory, enabling local fine-tuning, simulation, and execution of AI models up to 1 trillion parameters without requiring dedicated server room infrastructure.\u003c\/p\u003e\u003cp style=\"margin:1em 0\"\u003eMemory architecture integrates 252 GB of HBM3e GPU memory running at 7.1 TB\/s alongside 496 GB of LPDDR5X CPU memory across a 900 GB\/s NVLink-C2C interconnect. This unified address space allows large language models and complex multi-modal datasets to reside concurrently in high-speed memory for streamlined multi-team development and intensive RAG pipeline deployment.\u003c\/p\u003e\u003cp style=\"margin:1em 0\"\u003eEquipped with 1.92 TB of enterprise PCIe 5.0 NVMe storage in RAID 1, the system includes dual PCIe 6.0 x4 M.2 slots for storage expansion. High-throughput networking is handled by an NVIDIA ConnectX-8 SuperNIC featuring dual 400G QSFP112 ports alongside dedicated 10 GbE and 1 GbE management connections, powered by an internal 1600 W high-efficiency workstation power architecture.\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)\"\u003eMSI\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)\"\u003eMSI XpertStation WS300 (NVIDIA DGX Station GB300 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)\"\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)\"\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)\"\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)\"\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)\"\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)\"\u003eAI Models Up 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)\"\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)\"\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)\"\u003eInstalled Storage\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)\"\u003e1.92 TB Enterprise NVMe (2 × M.2 2280 PCIe 5.0) in RAID 1\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)\"\u003eExpansion Slots\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 × PCIe 6.0 x4 M.2 2280 Slots Available (4 × M.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)\"\u003eSuperNIC\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 Networking 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 × QSFP112 (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)\"\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)\"\u003e1,600 W Enterprise High-Efficiency Power Supply\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 Architecture\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 Workstation Cooling Architecture\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\"\u003eGPU Expansion\u003c\/td\u003e\n\u003ctd style=\"border:0;padding:0.4em 0;vertical-align:top\"\u003eSupports Additional NVIDIA RTX PRO Blackwell GPU\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e","brand":"MSI","offers":[{"title":"Default Title","offer_id":48538069860610,"sku":"XpertStation WS300","price":0.0,"currency_code":"SGD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/2697\/4510\/files\/msi-xpertstation-ws300-nvidia-dgx-station-ai-supercomputer-4865915_11e03a9e-bc3c-4416-984a-4677b115f035.png?v=1790029252","url":"https:\/\/lioncityco.com\/products\/msi-xpertstation-ws300-nvidia-dgx-station-ai-supercomputer-1","provider":"Lion City Company","version":"1.0","type":"link"}