{"id":18945,"date":"2026-09-16T20:14:17","date_gmt":"2026-09-16T13:14:17","guid":{"rendered":"https:\/\/droneth.or.th\/product\/nvidia-dgx-spark-founders-edition\/"},"modified":"2026-09-16T20:14:17","modified_gmt":"2026-09-16T13:14:17","slug":"nvidia-dgx-spark-founders-edition","status":"publish","type":"product","link":"https:\/\/droneth.or.th\/zh\/product\/nvidia-dgx-spark-founders-edition\/","title":{"rendered":"NVIDIA DGX Spark Founders Edition"},"content":{"rendered":"<p><strong>NVIDIA DGX Spark Founders Edition<\/strong> \u0e40\u0e1b\u0e47\u0e19 Personal AI Supercomputer \u0e08\u0e32\u0e01 <strong>NVIDIA<\/strong> \u0e40\u0e2b\u0e21\u0e32\u0e30\u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e07\u0e32\u0e19 local LLM, AI development, prototyping, fine-tuning \u0e23\u0e2d\u0e07\u0e23\u0e31\u0e1a\u0e01\u0e32\u0e23\u0e43\u0e0a\u0e49\u0e07\u0e32\u0e19\u0e23\u0e30\u0e14\u0e31\u0e1a\u0e2d\u0e07\u0e04\u0e4c\u0e01\u0e23 \u0e28\u0e39\u0e19\u0e22\u0e4c\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25 \u0e41\u0e25\u0e30\u0e07\u0e32\u0e19\u0e27\u0e34\u0e08\u0e31\u0e22\u0e14\u0e49\u0e32\u0e19 AI\/HPC<\/p>\n<p><strong>\u0e04\u0e33\u0e2d\u0e18\u0e34\u0e1a\u0e32\u0e22\u0e08\u0e32\u0e01\u0e1c\u0e39\u0e49\u0e1c\u0e25\u0e34\u0e15:<\/strong> Run autonomous AI agents from your desktop.<\/p>\n<p><strong>\u0e01\u0e32\u0e23\u0e43\u0e0a\u0e49\u0e07\u0e32\u0e19\u0e17\u0e35\u0e48\u0e40\u0e2b\u0e21\u0e32\u0e30\u0e2a\u0e21<\/strong><\/p>\n<ul>\n<li>local LLM<\/li>\n<li>AI development<\/li>\n<li>prototyping<\/li>\n<li>fine-tuning<\/li>\n<\/ul>\n<p><strong>\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25\u0e17\u0e32\u0e07\u0e40\u0e17\u0e04\u0e19\u0e34\u0e04 (Product Specifications)<\/strong><\/p>\n<table style=\"width:100%\">\n<thead>\n<tr>\n<td><strong>\u90e8\u5206<\/strong><\/td>\n<td><strong>\u0e23\u0e32\u0e22\u0e25\u0e30\u0e40\u0e2d\u0e35\u0e22\u0e14\u0e2a\u0e40\u0e1b\u0e04<\/strong><\/td>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>\u0e0a\u0e34\u0e1b\u0e2b\u0e25\u0e31\u0e01<\/strong><\/td>\n<td>GB10 Grace Blackwell Superchip<\/td>\n<\/tr>\n<tr>\n<td><strong>CPU<\/strong><\/td>\n<td>Arm 20\u2010\u0e04\u0e2d\u0e23\u0e4c (10x X925 + 10x A725)<\/td>\n<\/tr>\n<tr>\n<td><strong>GPU<\/strong><\/td>\n<td>\u5e03\u83b1\u514b\u97e6\u5c14\u67b6\u6784<\/td>\n<\/tr>\n<tr>\n<td><strong>\u5f20\u91cf\u6838\u5fc3<\/strong><\/td>\n<td>\u0e40\u0e08\u0e19 5<\/td>\n<\/tr>\n<tr>\n<td><strong>\u5149\u7ebf\u8ffd\u8e2a\u6838\u5fc3<\/strong><\/td>\n<td>\u0e40\u0e08\u0e19 4<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e1b\u0e23\u0e30\u0e2a\u0e34\u0e17\u0e18\u0e34\u0e20\u0e32\u0e1e AI<\/strong><\/td>\n<td>1,000 TOPS (FP4, sparsity)<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e2b\u0e19\u0e48\u0e27\u0e22\u0e04\u0e27\u0e32\u0e21\u0e08\u0e4d\u0e32\u0e23\u0e30\u0e1a\u0e1a<\/strong><\/td>\n<td>128 GB LPDDR5x, unified<\/td>\n<\/tr>\n<tr>\n<td><strong>\u5185\u5b58\u63a5\u53e3<\/strong><\/td>\n<td>256\u2010bit<\/td>\n<\/tr>\n<tr>\n<td><strong>\u5185\u5b58\u5e26\u5bbd<\/strong><\/td>\n<td>273 GB\/\u79d2<\/td>\n<\/tr>\n<tr>\n<td><strong>\u5b58\u50a8<\/strong><\/td>\n<td>1\/4 TB NVMe SSD (self\u2010encrypt)<\/td>\n<\/tr>\n<tr>\n<td><strong>\u8fde\u63a5\u6027<\/strong><\/td>\n<td>HDMI 2.1a, 10 GbE, Wi\u2010Fi 7, BT 5.3, USB4\u00d74<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e40\u0e04\u0e23\u0e37\u0e2d\u0e02\u0e48\u0e32\u0e22\u0e1e\u0e34\u0e40\u0e28\u0e29<\/strong><\/td>\n<td>ConnectX\u20107 SmartNIC (chaining for 405B models)<\/td>\n<\/tr>\n<tr>\n<td><strong>OS<\/strong><\/td>\n<td>NVIDIA DGX OS (Ubuntu\u2010based)<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e02\u0e19\u0e32\u0e14 \/ \u0e19\u0e49\u0e4d\u0e32\u0e2b\u0e19\u0e31\u0e01<\/strong><\/td>\n<td>150 \u00d7 150 \u00d7 50.5 mm, 1.2 kg<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e1e\u0e25\u0e31\u0e07\u0e07\u0e32\u0e19\u0e17\u0e35\u0e48\u0e43\u0e0a\u0e49<\/strong><\/td>\n<td>~170 W<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>Powered by the GB10 Superchip<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>1,000 TOPS of AI performance using FP4<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>NVIDIA Blackwell GPU with fifth-generation Tensor Core technology<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>NVIDIA Grace CPU implementation with 20-core high-performance Arm architecture<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>128 GB of coherent, unified memory<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>Up to 4 TB of NVMe storage<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>Support for up to 200B-parameter large language models<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>Connectivity with NVIDIA Connect-X networking to link two DGX Spark units for up to 405B-parameter models<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>NVIDIA DGX Spark Founders Edition \u0e04\u0e37\u0e2d\u0e0b\u0e39\u0e40\u0e1b\u0e2d\u0e23\u0e4c\u0e04\u0e2d\u0e21\u0e1e\u0e34\u0e27\u0e40\u0e15\u0e2d\u0e23\u0e4c AI \u0e02\u0e19\u0e32\u0e14\u0e40\u0e14\u0e2a\u0e01\u0e4c\u0e17\u0e47\u0e2d\u0e1b\u0e17\u0e35\u0e48\u0e17\u0e23\u0e07\u0e1e\u0e25\u0e31\u0e07 \u0e2d\u0e34\u0e07\u0e08\u0e32\u0e01 GB10 Grace Blackwell Superchip \u0e17\u0e35\u0e48\u0e23\u0e27\u0e21 CPU Arm 20\u2010\u0e04\u0e2d\u0e23\u0e4c \u0e41\u0e25\u0e30 GPU Blackwell \u0e1e\u0e23\u0e49\u0e2d\u0e21\u0e40\u0e17\u0e04\u0e42\u0e19\u0e42\u0e25\u0e22\u0e35 Tensor Core \u0e23\u0e38\u0e48\u0e19\u0e17\u0e35\u0e48 5 \u0e41\u0e25\u0e30 RT Core \u0e23\u0e38\u0e48\u0e19\u0e17\u0e35\u0e48 4 \u0e21\u0e32\u0e44\u0e27\u0e49\u0e43\u0e19\u0e40\u0e04\u0e23\u0e37\u0e48\u0e2d\u0e07\u0e40\u0e14\u0e35\u0e22\u0e27 \u0e14\u0e49\u0e27\u0e22\u0e1e\u0e25\u0e31\u0e07 AI \u0e2a\u0e39\u0e07\u0e2a\u0e38\u0e14 1,000 TOPS (FP4) \u0e1e\u0e23\u0e49\u0e2d\u0e21\u0e2b\u0e19\u0e48\u0e27\u0e22\u0e04\u0e27\u0e32\u0e21\u0e08\u0e4d\u0e32\u0e41\u0e1a\u0e1a unified \u0e02\u0e19\u0e32\u0e14 128 GB \u0e08\u0e36\u0e07\u0e2a\u0e32\u0e21\u0e32\u0e23\u0e16\u0e43\u0e0a\u0e49\u0e07\u0e32\u0e19\u0e42\u0e1b\u0e23\u0e42\u0e15\u0e44\u0e17\u0e1b\u0e4c \u0e1b\u0e23\u0e31\u0e1a\u0e41\u0e15\u0e48\u0e07 \u0e41\u0e25\u0e30\u0e23\u0e31\u0e19\u0e42\u0e21\u0e40\u0e14\u0e25 AI \u0e02\u0e19\u0e32\u0e14\u0e43\u0e2b\u0e0d\u0e48\u0e1a\u0e19\u0e01\u0e32\u0e23\u0e13\u0e4c\u0e27\u0e32\u0e07\u0e42\u0e1b\u0e23\u0e41\u0e01\u0e23\u0e21\u0e44\u0e14\u0e49\u0e42\u0e14\u0e22\u0e15\u0e23\u0e07\u0e1a\u0e19\u0e42\u0e15\u0e4a\u0e30\u0e17\u0e4d\u0e32\u0e07\u0e32\u0e19<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>The NVIDIA DGX Spark Founders Edition is a compact AI supercomputer designed for desktop use. Powered by the GB10 Grace Blackwell Superchip, it combines a 20-core Arm CPU and Blackwell GPU with 5th-gen Tensor Cores and 4th-gen RT Cores. Delivering up to 1,000 AI TOPS at FP4 precision and featuring 128 GB of unified memory, it enables on-desk prototyping, fine-tuning, and inference of large AI models.<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>The NVIDIA DGX Spark Founders Edition brings supercomputing to your workspace, blending CPU, GPU, Tensor, and RT cores into a compact platform with unmatched performance. Its unified 128 GB memory lets developers tackle models with hundreds of billions of parameters directly on the desk. With expandable networking via ConnectX\u20107 SmartNIC, it scales to larger workloads seamlessly. A powerhouse AI development tool for researchers and teams looking to start big without a full server setup.<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>Condition &amp; Warranty<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>\u2714 Fully tested and 100% working \u2714 Secure packaging for safe shipping \u2714 Warranty available (subject to store policy)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25\u0e2d\u0e49\u0e32\u0e07\u0e2d\u0e34\u0e07\u0e08\u0e32\u0e01\u0e1c\u0e39\u0e49\u0e1c\u0e25\u0e34\u0e15: <a href=\"https:\/\/www.nvidia.com\/en-us\/products\/workstations\/dgx-spark\/\" target=\"_blank\" rel=\"nofollow noopener\">NVIDIA<\/a><\/p>\n<p>\u0e2a\u0e19\u0e43\u0e08\u0e2a\u0e2d\u0e1a\u0e16\u0e32\u0e21\u0e23\u0e32\u0e04\u0e32 \u0e2a\u0e40\u0e1b\u0e04 \u0e2b\u0e23\u0e37\u0e2d\u0e02\u0e2d\u0e43\u0e1a\u0e40\u0e2a\u0e19\u0e2d\u0e23\u0e32\u0e04\u0e32 \u0e15\u0e34\u0e14\u0e15\u0e48\u0e2d\u0e44\u0e14\u0e49\u0e17\u0e35\u0e48 <strong>LINE: @metaxr<\/strong><\/p>","protected":false},"excerpt":{"rendered":"<p><strong>NVIDIA DGX Spark Founders Edition<\/strong> \u0e40\u0e1b\u0e47\u0e19 Personal AI Supercomputer \u0e08\u0e32\u0e01 <strong>NVIDIA<\/strong> \u0e40\u0e2b\u0e21\u0e32\u0e30\u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e07\u0e32\u0e19 local LLM, AI development, prototyping, fine-tuning \u0e23\u0e2d\u0e07\u0e23\u0e31\u0e1a\u0e01\u0e32\u0e23\u0e43\u0e0a\u0e49\u0e07\u0e32\u0e19\u0e23\u0e30\u0e14\u0e31\u0e1a\u0e2d\u0e07\u0e04\u0e4c\u0e01\u0e23 \u0e28\u0e39\u0e19\u0e22\u0e4c\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25 \u0e41\u0e25\u0e30\u0e07\u0e32\u0e19\u0e27\u0e34\u0e08\u0e31\u0e22\u0e14\u0e49\u0e32\u0e19 AI\/HPC<\/p>\n<div style=\"width: 100%; text-align: center; padding: 24px 0;\"><a style=\"display: inline-block; background-color: #06c755; color: #ffffff; font-size: 16px; font-weight: bold; text-decoration: none; padding: 14px 32px; border-radius: 50px; box-shadow: 0 4px 12px rgba(6,199,85,0.4); white-space: nowrap;\" href=\"https:\/\/page.line.me\/682mqqmh?openQrModal=true\" target=\"_blank\" rel=\"noopener\">\u0e2a\u0e2d\u0e1a\u0e16\u0e32\u0e21\u0e23\u0e32\u0e04\u0e32 \/ \u0e2a\u0e31\u0e48\u0e07\u0e0b\u0e37\u0e49\u0e2d LINE: @metaxr<\/a><\/div>","protected":false},"featured_media":18946,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}}},"product_brand":[],"product_cat":[389,148,384],"product_tag":[237,403,396],"class_list":{"0":"post-18945","1":"product","2":"type-product","3":"status-publish","4":"has-post-thumbnail","6":"product_cat-edge-ai-inference","7":"product_cat-ai-edge-computing","8":"product_cat-gpu-ai-server","9":"product_tag-ai-","10":"product_tag-edge-ai","11":"product_tag-nvidia","12":"desktop-align-left","13":"tablet-align-left","14":"mobile-align-left","16":"first","17":"instock","18":"shipping-taxable","19":"product-type-simple"},"acf":[],"_links":{"self":[{"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/product\/18945","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/product"}],"about":[{"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/types\/product"}],"replies":[{"embeddable":true,"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/comments?post=18945"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/media\/18946"}],"wp:attachment":[{"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/media?parent=18945"}],"wp:term":[{"taxonomy":"product_brand","embeddable":true,"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/product_brand?post=18945"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/product_cat?post=18945"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/product_tag?post=18945"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}