{"product_id":"nvidia-dgx-spark-founders-edition-ai-supercomputer-4tb-940-54242-0009-000","title":"NVIDIA DGX Spark Founders Edition AI Supercomputer - 4TB (UK Cord)","description":"\u003cdiv\u003e\n\u003cstyle\u003e\n.pd-acc { border: 1px solid #e2e2e2; border-radius: 8px; margin: 10px 0; overflow: hidden; }\n.pd-acc summary { cursor: pointer; padding: 14px 16px; font-weight: 700; font-size: 1.05em; list-style: none; display: flex; justify-content: space-between; align-items: center; background: #f7f7f7; }\n.pd-acc[open] \u003e summary { border-bottom: 1px solid #e2e2e2; }\n.pd-acc summary::-webkit-details-marker { display: none; }\n.pd-acc summary::after { content: \"+\"; font-size: 1.4em; font-weight: 400; line-height: 1; margin-left: 12px; }\n.pd-acc[open] \u003e summary::after { content: \"\\2212\"; }\n.pd-acc .pd-acc-body { padding: 8px 16px 14px; }\n.pd-spec, .pd-spec tr, .pd-spec td { border: none !important; background: transparent !important; }\n.pd-spec { width: 100%; border-collapse: collapse !important; margin: 6px 0 18px; }\n.pd-spec td { padding: 7px 10px 7px 0 !important; border-bottom: 1px solid #ececec !important; vertical-align: top; font-size: 0.95em; text-align: left; }\n.pd-spec td:first-child { width: 38%; font-weight: 600; color: #333; }\n.pd-spec tr:last-child td { border-bottom: none !important; }\n\u003c\/style\u003e\n\u003ch2\u003e\u003cstrong\u003eNVIDIA DGX Spark Founders Edition AI Supercomputer 4TB with UK Cord (940-54242-0009-000) - 1 Year Local Warranty\u003c\/strong\u003e\u003c\/h2\u003e\n\u003ch3\u003e\u003cstrong\u003eNVIDIA DGX Spark — A Petaflop of AI Performance on Your Desk\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp\u003eThe NVIDIA DGX Spark Founders Edition puts up to 1 petaFLOP of FP4 AI compute in a 1.2 kg desktop box. Powered by the NVIDIA GB10 Grace Blackwell Superchip with 128 GB of coherent unified memory, it runs inference on models up to 200 billion parameters and fine-tunes models up to 70 billion parameters — locally, on your desk, with no cloud dependency. This UK-cord part number ships factory-bundled with a UK\/Singapore Type-G power cord, so it is plug-and-go out of the box.\u003c\/p\u003e\n\u003ch3\u003e\u003cstrong\u003eEnterprise AI Without the Cloud — Privacy, Compliance, Control\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp\u003eDGX Spark brings the NVIDIA DGX platform to enterprises, research labs and advanced developers who need on-premise AI for data privacy, compliance and IP protection — finance, healthcare, research, defense and government. The full NVIDIA AI software stack comes preloaded on DGX OS: CUDA, TensorRT, PyTorch and TensorFlow containers, NVIDIA NIM and NGC-certified containers.\u003c\/p\u003e\n\u003ch3\u003e\u003cstrong\u003eScale to 405B Parameters with Two Linked Sparks\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp\u003eThe built-in NVIDIA ConnectX-7 SmartNIC (200 Gbps, RDMA-capable) lets you link two DGX Spark units into a single system that handles models up to 405 billion parameters — pair yours with a second unit and the \u003ca href=\"\/products\/nvidia-qsfp112-400g-dac-cable-40cm-x0101g00400a\"\u003eNVIDIA QSFP112 DAC cable (X0101G00400A)\u003c\/a\u003e.\u003c\/p\u003e\n\u003ch3\u003e\u003cstrong\u003eDeployment-Ready in Singapore\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp\u003eIn stock at SourceIT with GST invoice, 1 year local warranty, and our \u003ca href=\"https:\/\/sourceit.com.sg\/blogs\/news\/nvidia-dgx-spark-setup-and-enterprise-deployment-guide\"\u003eNVIDIA DGX Spark Setup and Enterprise Deployment Guide\u003c\/a\u003e to get you running from day one.\u003c\/p\u003e\n\u003cdetails class=\"pd-acc\"\u003e\n\u003csummary style=\"cursor: pointer; font-weight: 700;\"\u003eNVIDIA DGX Spark Founders Edition Datasheet — Technical Specifications\u003c\/summary\u003e\n\u003cdiv class=\"pd-acc-body\"\u003e\n\u003cp\u003e\u003cstrong\u003eGeneral\u003c\/strong\u003e\u003c\/p\u003e\n\u003ctable class=\"pd-spec\"\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003eModel\u003c\/td\u003e\n\u003ctd\u003eNVIDIA DGX Spark Founders Edition AI Supercomputer — 4TB (UK Cord)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePart Number\u003c\/td\u003e\n\u003ctd\u003e940-54242-0009-000\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eCategory\u003c\/td\u003e\n\u003ctd\u003eCompact Desktop AI Supercomputer\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eWarranty\u003c\/td\u003e\n\u003ctd\u003e1 Year Local Warranty (Singapore)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e\n\u003cp\u003e\u003cstrong\u003eProcessor — NVIDIA GB10 Grace Blackwell Superchip\u003c\/strong\u003e\u003c\/p\u003e\n\u003ctable class=\"pd-spec\"\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003eArchitecture\u003c\/td\u003e\n\u003ctd\u003eCPU + GPU Unified (Grace Blackwell), NVLink-C2C Interconnect\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eCPU\u003c\/td\u003e\n\u003ctd\u003e20-Core Arm — 10 × Cortex-X925 Performance + 10 × Cortex-A725 Efficiency\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eGPU\u003c\/td\u003e\n\u003ctd\u003eNVIDIA Blackwell Architecture\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eTensor Cores\u003c\/td\u003e\n\u003ctd\u003e5th Generation (FP4 \/ FP8 Optimised)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eRT Cores\u003c\/td\u003e\n\u003ctd\u003e4th Generation\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eGB10 TDP\u003c\/td\u003e\n\u003ctd\u003e140 W\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e\n\u003cp\u003e\u003cstrong\u003eAI Performance\u003c\/strong\u003e\u003c\/p\u003e\n\u003ctable class=\"pd-spec\"\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003ePeak AI Compute\u003c\/td\u003e\n\u003ctd\u003eUp to 1 PFLOP (1,000 TOPS) FP4 with Sparsity\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eInference\u003c\/td\u003e\n\u003ctd\u003eModels Up to 200 Billion Parameters (Single Unit)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFine-Tuning\u003c\/td\u003e\n\u003ctd\u003eModels Up to 70 Billion Parameters\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eClustered (2 Units)\u003c\/td\u003e\n\u003ctd\u003eModels Up to 405 Billion Parameters via ConnectX-7\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e\n\u003cp\u003e\u003cstrong\u003eMemory \u0026amp; Storage\u003c\/strong\u003e\u003c\/p\u003e\n\u003ctable class=\"pd-spec\"\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003eSystem Memory\u003c\/td\u003e\n\u003ctd\u003e128 GB LPDDR5x Coherent Unified Memory (Shared CPU–GPU)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eMemory Interface\u003c\/td\u003e\n\u003ctd\u003e256-bit, 273 GB\/s Bandwidth\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eStorage\u003c\/td\u003e\n\u003ctd\u003e4 TB NVMe M.2 Self-Encrypting SSD\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e\n\u003cp\u003e\u003cstrong\u003eNetworking \u0026amp; I\/O\u003c\/strong\u003e\u003c\/p\u003e\n\u003ctable class=\"pd-spec\"\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003eSmartNIC\u003c\/td\u003e\n\u003ctd\u003eNVIDIA ConnectX-7 — Up to 200 Gbps, RDMA Capable, Multi-Node Clustering\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eEthernet\u003c\/td\u003e\n\u003ctd\u003e1 × 10 GbE RJ-45\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eWireless\u003c\/td\u003e\n\u003ctd\u003eWi-Fi 7, Bluetooth 5.4\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eUSB\u003c\/td\u003e\n\u003ctd\u003e4 × USB Type-C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eDisplay\u003c\/td\u003e\n\u003ctd\u003e1 × HDMI 2.1a; Up to 3 × DisplayPort via USB-C Alt Mode\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eVideo Engines\u003c\/td\u003e\n\u003ctd\u003e1 × NVENC, 1 × NVDEC\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e\n\u003cp\u003e\u003cstrong\u003eSoftware\u003c\/strong\u003e\u003c\/p\u003e\n\u003ctable class=\"pd-spec\"\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003eOperating System\u003c\/td\u003e\n\u003ctd\u003eNVIDIA DGX OS (Ubuntu LTS-Based) with Preloaded AI Stack\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAI Stack\u003c\/td\u003e\n\u003ctd\u003eNVIDIA AI Enterprise, CUDA Toolkit, TensorRT, NVIDIA NIM, PyTorch \u0026amp; TensorFlow Containers, NGC-Certified Containers\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eSecurity\u003c\/td\u003e\n\u003ctd\u003eSecure Boot (UEFI), TPM-Based Security, Self-Encrypting SSD\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e\n\u003cp\u003e\u003cstrong\u003ePower \u0026amp; Physical\u003c\/strong\u003e\u003c\/p\u003e\n\u003ctable class=\"pd-spec\"\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003ePower Supply\u003c\/td\u003e\n\u003ctd\u003e240 W External Adapter\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eDimensions\u003c\/td\u003e\n\u003ctd\u003e150 mm × 150 mm × 50.5 mm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eWeight\u003c\/td\u003e\n\u003ctd\u003eApproximately 1.2 kg\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePower Cord\u003c\/td\u003e\n\u003ctd\u003eUK Type-G Power Cord Included (Factory-Bundled UK Cord Variant)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e\n\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"pd-acc\"\u003e\n\u003csummary style=\"cursor: pointer; font-weight: 700;\"\u003eWorkloads \u0026amp; Use Cases\u003c\/summary\u003e\n\u003cdiv class=\"pd-acc-body\"\u003e\n\u003cp\u003e\u003cstrong\u003ePrimary:\u003c\/strong\u003e LLM training, fine-tuning and large-scale inference — faster experimentation, shorter training cycles and real-time deployment for business-critical workloads.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eAlso ideal for:\u003c\/strong\u003e generative AI (image, video, multimodal), RAG systems and vector databases, agentic AI development, data science and embeddings, computer vision, scientific computing\/HPC research, and edge AI with low-latency local inference.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eRegulated industries:\u003c\/strong\u003e keeps sensitive data on-premise for finance, healthcare, research, defense and government deployments where public cloud is not an option.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"pd-acc\"\u003e\n\u003csummary style=\"cursor: pointer; font-weight: 700;\"\u003eOrdering Information — AI Supercomputers at SourceIT\u003c\/summary\u003e\n\u003cdiv class=\"pd-acc-body\"\u003e\n\u003ctable class=\"pd-spec\"\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA DGX Spark Founders Edition 4TB (UK Cord)\u003c\/td\u003e\n\u003ctd\u003e940-54242-0009-000 (This Product)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA DGX Spark 4TB (US Cord + UK Cord by SourceIT)\u003c\/td\u003e\n\u003ctd\u003e\u003ca href=\"\/products\/nvidia-dgx-spark-ai-supercomputer-4tb-940-54242-0007-000\"\u003e940-54242-0007-000 — In Stock\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eASUS Ascent GX10 1TB (GB10 Platform)\u003c\/td\u003e\n\u003ctd\u003e\u003ca href=\"\/products\/asus-ascent-gx10-compact-desktop-ai-supercomputer-1tb-gx10-gg0007bn\"\u003eGX10-GG0007BN — In Stock\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eASUS Ascent GX10 2TB (GB10 Platform)\u003c\/td\u003e\n\u003ctd\u003e\u003ca href=\"\/products\/asus-ascent-gx10-compact-desktop-ai-supercomputer-2tb-gx10-gg0030bn\"\u003eGX10-GG0030BN — In Stock\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eASUS Ascent GX10 4TB (GB10 Platform)\u003c\/td\u003e\n\u003ctd\u003e\u003ca href=\"\/products\/asus-ascent-gx10-compact-desktop-ai-supercomputer-4tb-gx10-gg0007bn\"\u003eGX10-GG0031BN — In Stock\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA QSFP112 400G DAC Cable (Links 2 Units)\u003c\/td\u003e\n\u003ctd\u003e\u003ca href=\"\/products\/nvidia-qsfp112-400g-dac-cable-40cm-x0101g00400a\"\u003eX0101G00400A — In Stock\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eMSI XpertStation WS300 (DGX Station GB300, 748GB)\u003c\/td\u003e\n\u003ctd\u003e\u003ca href=\"\/products\/msi-xpertstation-ws300-nvidia-dgx-station-ai-supercomputer\"\u003eIn Stock — Enquire\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eHP ZGX Fury G1n GB300 AI Workstation\u003c\/td\u003e\n\u003ctd\u003e\u003ca href=\"\/products\/hp-zgx-fury-g1n-gb300-ai-workstation-with-nvidia-blackwell-ultra\"\u003eEnquire\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e\n\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"pd-acc\"\u003e\n\u003csummary style=\"cursor: pointer; font-weight: 700;\"\u003eDatasheet, Downloads \u0026amp; Setup Guide\u003c\/summary\u003e\n\u003cdiv class=\"pd-acc-body\"\u003e\n\u003cp\u003e• \u003ca href=\"https:\/\/www.nvidia.com\/en-us\/products\/workstations\/dgx-spark\/\" rel=\"noopener\" target=\"_blank\"\u003eNVIDIA DGX Spark — Official Product Page \u0026amp; Specifications\u003c\/a\u003e\u003cbr\u003e\n• \u003ca href=\"https:\/\/sourceit.com.sg\/blogs\/news\/nvidia-dgx-spark-setup-and-enterprise-deployment-guide\"\u003eNVIDIA DGX Spark Setup and Enterprise Deployment Guide — SourceIT\u003c\/a\u003e\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"pd-acc\"\u003e\n\u003csummary style=\"cursor: pointer; font-weight: 700;\"\u003eFrequently Asked Questions — NVIDIA DGX Spark Founders Edition\u003c\/summary\u003e\n\u003cdiv class=\"pd-acc-body\"\u003e\n\u003cp\u003e\u003cstrong\u003eWhat is the difference between part numbers 940-54242-0009-000 and 940-54242-0007-000?\u003c\/strong\u003e\u003cbr\u003e\nSame NVIDIA DGX Spark Founders Edition hardware — GB10 Grace Blackwell, 128 GB unified memory, 4 TB SSD. The 0009-000 (this listing) ships factory-bundled with a UK Type-G power cord; the \u003ca href=\"\/products\/nvidia-dgx-spark-ai-supercomputer-4tb-940-54242-0007-000\"\u003e0007-000\u003c\/a\u003e ships with a US cord, and SourceIT supplies a UK cord separately.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat AI models can the DGX Spark run?\u003c\/strong\u003e\u003cbr\u003e\nA single DGX Spark handles inference on models up to 200 billion parameters and fine-tuning up to 70 billion parameters — think Llama, Qwen, DeepSeek, Mistral and Flux-class models locally. Two linked units scale to 405 billion parameters.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eHow do I connect two DGX Spark units?\u003c\/strong\u003e\u003cbr\u003e\nVia the built-in ConnectX-7 SmartNIC using the \u003ca href=\"\/products\/nvidia-qsfp112-400g-dac-cable-40cm-x0101g00400a\"\u003eNVIDIA QSFP112 400G DAC cable\u003c\/a\u003e — a direct connection that turns two Sparks into one system for larger models and distributed training.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat is the difference between the NVIDIA DGX Spark and the ASUS Ascent GX10?\u003c\/strong\u003e\u003cbr\u003e\nBoth are built on the same NVIDIA GB10 Grace Blackwell platform with 128 GB unified memory and up to 1 PFLOP FP4. The DGX Spark is NVIDIA's first-party unit with 4 TB storage; the \u003ca href=\"\/products\/asus-ascent-gx10-compact-desktop-ai-supercomputer-1tb-gx10-gg0007bn\"\u003eASUS GX10\u003c\/a\u003e offers 1 TB, 2 TB and 4 TB tiers at different price points with onsite warranty.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eDo I need special power or cooling?\u003c\/strong\u003e\u003cbr\u003e\nNo. The DGX Spark draws just 240 W from a standard wall socket with an external adapter and enterprise-grade active cooling — it runs on a desk, not a data centre. This UK-cord variant plugs straight into Singapore sockets.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat software comes preinstalled?\u003c\/strong\u003e\u003cbr\u003e\nNVIDIA DGX OS with the full NVIDIA AI stack: CUDA, TensorRT, NVIDIA NIM, PyTorch\/TensorFlow containers and NGC-certified containers — ready for development on day one. See our \u003ca href=\"https:\/\/sourceit.com.sg\/blogs\/news\/nvidia-dgx-spark-setup-and-enterprise-deployment-guide\"\u003esetup and deployment guide\u003c\/a\u003e.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eIs the DGX Spark covered by local warranty in Singapore?\u003c\/strong\u003e\u003cbr\u003e\nYes. Every DGX Spark sold by SourceIT comes with 1 year local warranty and a GST invoice. Volume and enterprise procurement enquiries are welcome.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cp\u003e\u003ciframe title=\"Sparking Something Big: NVIDIA DGX Spark Has Arrived\" src=\"https:\/\/www.youtube.com\/embed\/AvgZscNZzYw\" height=\"315\" width=\"560\" allowfullscreen\u003e\u003c\/iframe\u003e\u003c\/p\u003e\n\u003c\/div\u003e","brand":"Nvidia","offers":[{"title":"Default Title","offer_id":54288707715236,"sku":"940-54242-0009-000","price":8096.0,"currency_code":"SGD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0605\/0136\/0804\/files\/nvidia-dgx-spark-ai-supercomputer-4tb-4080342.jpg?v=1782950834","url":"https:\/\/sourceit.com.sg\/products\/nvidia-dgx-spark-founders-edition-ai-supercomputer-4tb-940-54242-0009-000","provider":"SourceIT ","version":"1.0","type":"link"}