{"id":18997,"date":"2026-09-16T20:14:34","date_gmt":"2026-09-16T13:14:34","guid":{"rendered":"https:\/\/droneth.or.th\/product\/nvidia-rtx-pro-6000-blackwell-max-q-workstation-edition\/"},"modified":"2026-09-16T20:14:34","modified_gmt":"2026-09-16T13:14:34","slug":"nvidia-rtx-pro-6000-blackwell-max-q-workstation-edition","status":"publish","type":"product","link":"https:\/\/droneth.or.th\/en\/product\/nvidia-rtx-pro-6000-blackwell-max-q-workstation-edition\/","title":{"rendered":"NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition"},"content":{"rendered":"<p><strong>NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition<\/strong> \u0e40\u0e1b\u0e47\u0e19 Professional GPU \u0e08\u0e32\u0e01 <strong>NVIDIA<\/strong> \u0e40\u0e2b\u0e21\u0e32\u0e30\u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e07\u0e32\u0e19 professional visualization, AI inference, CAD, content creation \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>professional visualization<\/li>\n<li>AI inference<\/li>\n<li>CAD<\/li>\n<li>content creation<\/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>section<\/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 \/ GPU Architecture<\/strong><\/td>\n<td>NVIDIA Blackwell | NVIDIA Blackwell<\/td>\n<\/tr>\n<tr>\n<td><strong>CUDA Cores<\/strong><\/td>\n<td>24,064 | 24,064<\/td>\n<\/tr>\n<tr>\n<td><strong>Tensor Cores<\/strong><\/td>\n<td>752 (\u0e40\u0e08\u0e40\u0e19\u0e2d\u0e40\u0e23\u0e0a\u0e31\u0e19\u0e17\u0e35\u0e48 5) | 752 (5th\u2010Gen)<\/td>\n<\/tr>\n<tr>\n<td><strong>RT Cores<\/strong><\/td>\n<td>188 (\u0e40\u0e08\u0e40\u0e19\u0e2d\u0e40\u0e23\u0e0a\u0e31\u0e19\u0e17\u0e35\u0e48 4) | 188 (4th\u2010Gen)<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e2b\u0e19\u0e48\u0e27\u0e22\u0e04\u0e27\u0e32\u0e21\u0e08\u0e4d\u0e32 \/ Memory<\/strong><\/td>\n<td>96 GB GDDR7 (ECC), 512\u2010bit, 1,792 GB\/s bandwidth | 96 GB GDDR7 (ECC), 512\u2010bit, 1,792 GB\/s<\/td>\n<\/tr>\n<tr>\n<td><strong>AI Performance<\/strong><\/td>\n<td>3,511 TOPS | 3,511 TOPS<\/td>\n<\/tr>\n<tr>\n<td><strong>FP32 \/ Single\u2010Precision<\/strong><\/td>\n<td>~110 TFLOPS | ~110 TFLOPS<\/td>\n<\/tr>\n<tr>\n<td><strong>RT Performance<\/strong><\/td>\n<td>~333 TFLOPS | ~333 TFLOPS<\/td>\n<\/tr>\n<tr>\n<td><strong>NVENC \/ NVDEC<\/strong><\/td>\n<td>9th\u2010Gen NVENC (4x) \/ 6th\u2010Gen NVDEC (4x) | 9th\u2010Gen NVENC (4x) \/ 6th\u2010Gen NVDEC (4x)<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e1a\u0e31\u0e2a\u0e40\u0e0a\u0e37\u0e48\u0e2d\u0e21\u0e15\u0e48\u0e2d \/ Bus Interface<\/strong><\/td>\n<td>PCIe Gen5 x16 | PCIe Gen5 x16<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e1e\u0e2d\u0e23\u0e4c\u0e15\u0e41\u0e2a\u0e14\u0e07\u0e1c\u0e25 \/ Outputs<\/strong><\/td>\n<td>4\u00d7 DisplayPort 2.1 | 4\u00d7 DisplayPort 2.1<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e01\u0e32\u0e23\u0e43\u0e0a\u0e49\u0e1e\u0e25\u0e31\u0e07\u0e07\u0e32\u0e19 \/ Power<\/strong><\/td>\n<td>\u0e2a\u0e39\u0e07\u0e2a\u0e38\u0e14 300 W | Max 300 W<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e23\u0e39\u0e1b\u0e41\u0e1a\u0e1a \/ Form Factor<\/strong><\/td>\n<td>4.4\u201d H \u00d7 10.5\u201d L, dual\u2010slot, blower cooling | 4.4\u201d H \u00d7 10.5\u201d L, dual\u2010slot, blower cooling<\/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>Display Connectors<\/strong><\/td>\n<td>DP 2.1 (4)<\/td>\n<\/tr>\n<tr>\n<td><strong>Max. Power Consumption<\/strong><\/td>\n<td>300W<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>NVIDIA RTX PRO 6000 Blackwell Max\u2010Q Workstation Edition \u0e04\u0e37\u0e2d\u0e01\u0e23\u0e32\u0e1f\u0e34\u0e01\u0e01\u0e32\u0e23\u0e4c\u0e14\u0e23\u0e30\u0e14\u0e31\u0e1a\u0e21\u0e37\u0e2d\u0e2d\u0e32\u0e0a\u0e35\u0e1e\u0e1a\u0e19\u0e2a\u0e16\u0e32\u0e1b\u0e31\u0e15\u0e22\u0e01\u0e23\u0e23\u0e21 Blackwell \u0e08\u0e32\u0e01 NVIDIA \u0e17\u0e35\u0e48\u0e2d\u0e2d\u0e01\u0e41\u0e1a\u0e1a\u0e21\u0e32\u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e40\u0e04\u0e23\u0e37\u0e48\u0e2d\u0e07\u0e40\u0e27\u0e34\u0e23\u0e4c\u0e01\u0e2a\u0e40\u0e15\u0e0a\u0e31\u0e19\u0e04\u0e27\u0e32\u0e21\u0e2b\u0e19\u0e32\u0e41\u0e19\u0e48\u0e19\u0e2a\u0e39\u0e07 (\u0e2a\u0e39\u0e07\u0e2a\u0e38\u0e14 4 \u0e01\u0e32\u0e23\u0e4c\u0e14\u0e43\u0e19\u0e40\u0e04\u0e23\u0e37\u0e48\u0e2d\u0e07\u0e40\u0e14\u0e35\u0e22\u0e27) \u0e42\u0e14\u0e14\u0e40\u0e14\u0e48\u0e19\u0e14\u0e49\u0e32\u0e19 AI, rendering \u0e41\u0e25\u0e30\u0e01\u0e32\u0e23\u0e1b\u0e23\u0e30\u0e21\u0e27\u0e25\u0e1c\u0e25\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25\u0e02\u0e19\u0e32\u0e14\u0e43\u0e2b\u0e0d\u0e48 \u0e14\u0e49\u0e27\u0e22\u0e2b\u0e19\u0e48\u0e27\u0e22\u0e04\u0e27\u0e32\u0e21\u0e08\u0e4d\u0e32 96 GB GDDR7 ECC \u0e41\u0e25\u0e30\u0e2d\u0e2d\u0e01\u0e41\u0e1a\u0e1a\u0e43\u0e2b\u0e49\u0e21\u0e35\u0e1b\u0e23\u0e30\u0e2a\u0e34\u0e17\u0e18\u0e34\u0e20\u0e32\u0e1e\u0e15\u0e48\u0e2d\u0e27\u0e31\u0e15\u0e15\u0e4c\u0e2a\u0e39\u0e07 \u0e40\u0e2b\u0e21\u0e32\u0e30\u0e01\u0e31\u0e1a\u0e07\u0e32\u0e19\u0e23\u0e30\u0e14\u0e31\u0e1a\u0e2d\u0e07\u0e04\u0e4c\u0e01\u0e23\u0e17\u0e35\u0e48\u0e15\u0e49\u0e2d\u0e07\u0e01\u0e32\u0e23\u0e04\u0e27\u0e32\u0e21\u0e41\u0e23\u0e07\u0e41\u0e25\u0e30\u0e04\u0e27\u0e32\u0e21\u0e40\u0e2a\u0e16\u0e35\u0e22\u0e23\u0e2a\u0e39\u0e07\u0e2a\u0e38\u0e14<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>The NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition is a professional-grade workstation GPU built on NVIDIA\u2019s Blackwell architecture. Designed for dense multi\u2010GPU systems (up to four cards), it excels in AI, rendering, and large\u2010scale data processing tasks. It features 96 GB GDDR7 ECC memory and an efficiency\u2010optimized Max\u2010Q design, making it ideal for enterprise workloads requiring both power and reliability.<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>The RTX PRO 6000 Blackwell Max\u2010Q is a high-end professional GPU optimized for dense workstation configurations. It offers a massive 96 GB of GDDR7 ECC memory, delivering stability and speed for heavy workloads involving AI, rendering, and simulation of large datasets or models. With full complement of CUDA, Tensor, and RT cores, it handles demanding tasks with ease while being power-efficient at just 300 W. Its compact and scalable Max\u2010Q design allows multi\u2010GPU setups in a single system, offering both performance and flexibility for professional environments.<\/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 Max-Q Workstation Edition<\/strong> \u0e40\u0e1b\u0e47\u0e19 Professional GPU \u0e08\u0e32\u0e01 <strong>NVIDIA<\/strong> \u0e40\u0e2b\u0e21\u0e32\u0e30\u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e07\u0e32\u0e19 professional visualization, AI inference, CAD, content creation \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":19261,"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":[392,384],"product_tag":[237,397,396],"class_list":{"0":"post-18997","1":"product","2":"type-product","3":"status-publish","4":"has-post-thumbnail","6":"product_cat-professional-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\/en\/wp-json\/wp\/v2\/product\/18997","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/droneth.or.th\/en\/wp-json\/wp\/v2\/product"}],"about":[{"href":"https:\/\/droneth.or.th\/en\/wp-json\/wp\/v2\/types\/product"}],"replies":[{"embeddable":true,"href":"https:\/\/droneth.or.th\/en\/wp-json\/wp\/v2\/comments?post=18997"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/droneth.or.th\/en\/wp-json\/wp\/v2\/media\/19261"}],"wp:attachment":[{"href":"https:\/\/droneth.or.th\/en\/wp-json\/wp\/v2\/media?parent=18997"}],"wp:term":[{"taxonomy":"product_brand","embeddable":true,"href":"https:\/\/droneth.or.th\/en\/wp-json\/wp\/v2\/product_brand?post=18997"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/droneth.or.th\/en\/wp-json\/wp\/v2\/product_cat?post=18997"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/droneth.or.th\/en\/wp-json\/wp\/v2\/product_tag?post=18997"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}