{"id":1932,"date":"2025-12-14T13:24:19","date_gmt":"2025-12-14T13:24:19","guid":{"rendered":"https:\/\/pckumar.in\/datacenters\/product\/nvidia-dgx-spark\/"},"modified":"2026-06-15T09:46:51","modified_gmt":"2026-06-15T09:46:51","slug":"nvidia-dgx-spark-grace-blackwell-gb10-4tb-desktop-ai-supercomputer-india","status":"publish","type":"product","link":"https:\/\/pckumar.in\/datacenters\/product\/nvidia-dgx-spark-grace-blackwell-gb10-4tb-desktop-ai-supercomputer-india\/","title":{"rendered":"Nvidia DGX Spark Grace Blackwell (GB10) 4TB Desktop AI Supercomputer india"},"content":{"rendered":"<p>[et_pb_section fb_built=&#8221;1&#8243; admin_label=&#8221;Product&#8221; _builder_version=&#8221;4.22.0&#8243; _module_preset=&#8221;default&#8221; collapsed=&#8221;off&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_row _builder_version=&#8221;4.22.0&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;0px||0px||true|false&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; 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Form Factor: Desktop &#8220;AI Supercomputer&#8221;,Processor: NVIDIA Grace Blackwell (GB10),Memory: Unified High-Bandwidth Memory,Cooling: Quiet, Office-Friendly Design,Use Case: Local AI Dev &amp; Prototyping<\/p>\n","protected":false},"featured_media":91,"comment_status":"open","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"<h1><strong>Nvidia DGX Spark Grace Blackwell GB10<\/strong><\/h1>\r\nNVIDIA DGX Spark is a compact, liquid-cooled \"desktop supercomputer\" designed for data scientists and AI researchers. Powered by the NVIDIA Grace Blackwell (GB10) Superchip, it brings data-center-class architecture to the edge or office desk. It features unified memory that allows developers to run and fine-tune large generative AI models locally without needing immediate access to a cloud cluster. It serves as the perfect \"sandbox\" environment, ensuring that code developed locally scales seamlessly to larger DGX clouds.\r\n<h2><strong>Specifications<\/strong><\/h2>\r\n<table style=\"height: 641px\" width=\"522\" cellspacing=\"0\" cellpadding=\"0\">\r\n<tbody>\r\n<tr>\r\n<td style=\"width: 200.385px\">Architecture<\/td>\r\n<td style=\"width: 317.615px\">NVIDIA Grace Blackwell<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">GPU<\/td>\r\n<td style=\"width: 317.615px\">Blackwell Architecture<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">CPU<\/td>\r\n<td style=\"width: 317.615px\">20 core Arm, 10 Cortex-X925 + 10 Cortex-A725 Arm<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">CUDA Cores<\/td>\r\n<td style=\"width: 317.615px\">Blackwell Generation<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">Tensor Cores<\/td>\r\n<td style=\"width: 317.615px\">5th Generation<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">RT Cores<\/td>\r\n<td style=\"width: 317.615px\">4th Generation<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">Tensor Performance<sup>1<\/sup><\/td>\r\n<td style=\"width: 317.615px\">1 PFLOP<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">System Memory<\/td>\r\n<td style=\"width: 317.615px\">128 GB LPDDR5x, coherent unified system memory<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">Memory Interface<\/td>\r\n<td style=\"width: 317.615px\">256-bit<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">Memory Bandwidth<\/td>\r\n<td style=\"width: 317.615px\">273 GB\/s<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">Storage<\/td>\r\n<td style=\"width: 317.615px\">4 TB NVME.M2 with self-encryption<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">USB<\/td>\r\n<td style=\"width: 317.615px\">4x USB TypeC<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">Ethernet<\/td>\r\n<td style=\"width: 317.615px\">1x RJ-45 connector\r\n10 GbE<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">NIC<\/td>\r\n<td style=\"width: 317.615px\">ConnectX-7 NIC @ 200 Gbps<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">Wi-Fi<\/td>\r\n<td style=\"width: 317.615px\">WiFi 7<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">Bluetooth<\/td>\r\n<td style=\"width: 317.615px\">BT 5.4<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">Audio-output<\/td>\r\n<td style=\"width: 317.615px\">HDMI multichannel audio output<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">Power Supply<\/td>\r\n<td style=\"width: 317.615px\">240 W<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">GB10 TDP<sup>2<\/sup><\/td>\r\n<td style=\"width: 317.615px\">140 W<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">Display Connectors<\/td>\r\n<td style=\"width: 317.615px\">1x HDMI 2.1a<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">NVENC | NVDEC<\/td>\r\n<td style=\"width: 317.615px\">1x | 1x<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">OS<\/td>\r\n<td style=\"width: 317.615px\">NVIDIA DGX<sup>\u2122<\/sup>\u00a0OS<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">System Dimensions<\/td>\r\n<td style=\"width: 317.615px\">150 mm L x 150 mm W x 50.5 mm H<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 200.385px\">System Weight<\/td>\r\n<td style=\"width: 317.615px\">1.2 kg<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>","_et_gb_content_width":""},"product_brand":[50],"product_cat":[37],"product_tag":[52,51],"class_list":["post-1932","product","type-product","status-publish","has-post-thumbnail","product_brand-nvidia","product_cat-nvidia","product_tag-grace-blackwell-gb10","product_tag-nvidia-dgx-spark","first","instock","sale","sold-individually","shipping-taxable","purchasable","product-type-simple"],"_links":{"self":[{"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/product\/1932","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/product"}],"about":[{"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/types\/product"}],"replies":[{"embeddable":true,"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/comments?post=1932"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/media\/91"}],"wp:attachment":[{"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/media?parent=1932"}],"wp:term":[{"taxonomy":"product_brand","embeddable":true,"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/product_brand?post=1932"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/product_cat?post=1932"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/product_tag?post=1932"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}