{"id":18694,"date":"2026-09-16T20:11:11","date_gmt":"2026-09-16T13:11:11","guid":{"rendered":"https:\/\/droneth.or.th\/product\/nvidia-rtx-pro-6000-blackwell-server-edition\/"},"modified":"2026-09-16T20:11:11","modified_gmt":"2026-09-16T13:11:11","slug":"nvidia-rtx-pro-6000-blackwell-server-edition","status":"publish","type":"product","link":"https:\/\/droneth.or.th\/zh\/product\/nvidia-rtx-pro-6000-blackwell-server-edition\/","title":{"rendered":"NVIDIA RTX PRO 6000 Blackwell Server Edition"},"content":{"rendered":"<p><strong>NVIDIA RTX PRO 6000 Blackwell Server Edition<\/strong> \u0e40\u0e1b\u0e47\u0e19 Data Center GPU \/ Accelerator \u0e08\u0e32\u0e01 <strong>NVIDIA<\/strong> \u0e40\u0e2b\u0e21\u0e32\u0e30\u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e07\u0e32\u0e19 AI training, AI inference, HPC, virtual workstation \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>\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>AI training<\/li>\n<li>AI inference<\/li>\n<li>HPC<\/li>\n<li>virtual workstation<\/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>\u0e2a\u0e16\u0e32\u0e1b\u0e31\u0e15\u0e22\u0e01\u0e23\u0e23\u0e21 GPU<\/strong><\/td>\n<td>NVIDIA Blackwell Architecture<\/td>\n<\/tr>\n<tr>\n<td><strong>CUDA\u6838\u5fc3<\/strong><\/td>\n<td>24,064<\/td>\n<\/tr>\n<tr>\n<td><strong>Tensor Cores (5th Gen)<\/strong><\/td>\n<td>752<\/td>\n<\/tr>\n<tr>\n<td><strong>RT Cores (4th Gen)<\/strong><\/td>\n<td>188<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e04\u0e27\u0e32\u0e21\u0e40\u0e23\u0e47\u0e27 FP32<\/strong><\/td>\n<td>~117 TFLOPS (\u0e1a\u0e32\u0e07\u0e17\u0e35\u0e48\u0e23\u0e30\u0e1a\u0e38 120 TFLOPS)<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e1e\u0e25\u0e31\u0e07\u0e07\u0e32\u0e19\u0e2a\u0e39\u0e07\u0e2a\u0e38\u0e14 (\u0e01\u0e4d\u0e32\u0e2b\u0e19\u0e14\u0e04\u0e48\u0e32\u0e44\u0e14\u0e49)<\/strong><\/td>\n<td>Up to 600 W (configurable)<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e2b\u0e19\u0e48\u0e27\u0e22\u0e04\u0e27\u0e32\u0e21\u0e08\u0e4d\u0e32 GPU<\/strong><\/td>\n<td>96 GB GDDR7 with ECC<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e01\u0e32\u0e23\u0e40\u0e0a\u0e37\u0e48\u0e2d\u0e21\u0e15\u0e48\u0e2d\u0e2b\u0e19\u0e48\u0e27\u0e22\u0e04\u0e27\u0e32\u0e21\u0e08\u0e4d\u0e32<\/strong><\/td>\n<td>512\u2010bit<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e41\u0e1a\u0e19\u0e14\u0e4c\u0e27\u0e34\u0e14\u0e18\u0e4c\u0e2b\u0e19\u0e48\u0e27\u0e22\u0e04\u0e27\u0e32\u0e21\u0e08\u0e4d\u0e32<\/strong><\/td>\n<td>~1.6 TB\/s (1597 GB\/s)<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e01\u0e32\u0e23\u0e40\u0e0a\u0e37\u0e48\u0e2d\u0e21\u0e15\u0e48\u0e2d\u0e2b\u0e25\u0e31\u0e01<\/strong><\/td>\n<td>PCI Express Gen 5 x16<\/td>\n<\/tr>\n<tr>\n<td><strong>DisplayPort<\/strong><\/td>\n<td>4\u00d7 DisplayPort 2.1<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e23\u0e39\u0e1b\u0e41\u0e1a\u0e1a\u0e1a\u0e2d\u0e23\u0e4c\u0e14 (Form Factor)<\/strong><\/td>\n<td>4.4\u2032\u2032 H \u00d7 10.5\u2032\u2032 L, dual slot<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e23\u0e30\u0e1a\u0e1a\u0e23\u0e30\u0e1a\u0e32\u0e22\u0e04\u0e27\u0e32\u0e21\u0e23\u0e49\u0e2d\u0e19<\/strong><\/td>\n<td>Passive<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e40\u0e17\u0e04\u0e42\u0e19\u0e42\u0e25\u0e22\u0e35 MIG (Multi\u2010Instance)<\/strong><\/td>\n<td>Up to 4 instances (\u0e41\u0e15\u0e48\u0e25\u0e30\u0e15\u0e31\u0e27 24 GB)<\/td>\n<\/tr>\n<tr>\n<td><strong>NVENC \/ NVDEC \/ JPEG<\/strong><\/td>\n<td>4\u00d7 \/ 4\u00d7 \/ 4\u00d7<\/td>\n<\/tr>\n<tr>\n<td><strong>Confidential Compute<\/strong><\/td>\n<td>Supported<\/td>\n<\/tr>\n<tr>\n<td><strong>Secure Boot with Root of Trust<\/strong><\/td>\n<td>Yes<\/td>\n<\/tr>\n<tr>\n<td><strong>Power Connector<\/strong><\/td>\n<td>1\u00d7 PCIe CEM5 16\u2010pin<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>96GB GDDR7 Memory with ECC<\/td>\n<\/tr>\n<tr>\n<td><strong>Graphics Bus<\/strong><\/td>\n<td>PCI-E 5.0 x16<\/td>\n<\/tr>\n<tr>\n<td><strong>Multi-Instance GPU<\/strong><\/td>\n<td>Up to 600W (Configurable)<\/td>\n<\/tr>\n<tr>\n<td><strong>Max. Power Consumption<\/strong><\/td>\n<td>Up to 600W (Configurable)<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>Support Confidential Compute<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>The NVIDIA RTX PRO 6000 Blackwell Server Edition is a data\u2010center GPU built on NVIDIA\u2019s Blackwell architecture, designed to accelerate enterprise\u2010level AI and visual computing workloads, from rendering and data analytics to high\u2010throughput model inference.<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>The NVIDIA RTX PRO 6000 Blackwell Server Edition is engineered for the next era of enterprise compute. Leveraging the latest Blackwell architecture, it combines massive 96 GB of GDDR7 memory with cutting\u2010edge compute units (CUDA, Tensor, RT), MIG isolation, and robust security features such as Confidential Compute and Secure Boot. These capabilities make it ideal for multi\u2010workload environments\u2014from high\u2010throughput AI inference to 3D rendering and data analytics\u2014delivering scalable, efficient, and secure performance for data\u2010center deployments.<\/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>\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 RTX PRO 6000 Blackwell Server Edition<\/strong> \u0e40\u0e1b\u0e47\u0e19 Data Center GPU \/ Accelerator \u0e08\u0e32\u0e01 <strong>NVIDIA<\/strong> \u0e40\u0e2b\u0e21\u0e32\u0e30\u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e07\u0e32\u0e19 AI training, AI inference, HPC, virtual workstation \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":19188,"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":[388,384],"product_tag":[237,397,396],"class_list":{"0":"post-18694","1":"product","2":"type-product","3":"status-publish","4":"has-post-thumbnail","6":"product_cat-data-center-gpu","7":"product_cat-gpu-ai-server","8":"product_tag-ai-","9":"product_tag-gpu","10":"product_tag-nvidia","11":"desktop-align-left","12":"tablet-align-left","13":"mobile-align-left","15":"first","16":"instock","17":"shipping-taxable","18":"product-type-simple"},"acf":[],"_links":{"self":[{"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/product\/18694","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=18694"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/media\/19188"}],"wp:attachment":[{"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/media?parent=18694"}],"wp:term":[{"taxonomy":"product_brand","embeddable":true,"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/product_brand?post=18694"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/product_cat?post=18694"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/product_tag?post=18694"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}