{"id":18974,"date":"2026-09-16T20:14:25","date_gmt":"2026-09-16T13:14:25","guid":{"rendered":"https:\/\/droneth.or.th\/product\/nvidia-quadro-rtx6000-passive\/"},"modified":"2026-09-16T20:14:25","modified_gmt":"2026-09-16T13:14:25","slug":"nvidia-quadro-rtx6000-passive","status":"publish","type":"product","link":"https:\/\/droneth.or.th\/zh\/product\/nvidia-quadro-rtx6000-passive\/","title":{"rendered":"NVIDIA Quadro RTX6000 Passive"},"content":{"rendered":"<p><strong>NVIDIA Quadro RTX6000 Passive<\/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>\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>\u0e04\u0e38\u0e13\u0e2a\u0e21\u0e1a\u0e31\u0e15\u0e34 (\u0e44\u0e17\u0e22)<\/strong><\/td>\n<td>Feature (English)<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e2a\u0e16\u0e32\u0e1b\u0e31\u0e15\u0e22\u0e01\u0e23\u0e23\u0e21 GPU<\/strong><\/td>\n<td>GPU Architecture: Turing<\/td>\n<\/tr>\n<tr>\n<td><strong>CUDA\u6838\u5fc3<\/strong><\/td>\n<td>4608 CUDA Cores<\/td>\n<\/tr>\n<tr>\n<td><strong>\u5f20\u91cf\u6838\u5fc3<\/strong><\/td>\n<td>576 Tensor Cores<\/td>\n<\/tr>\n<tr>\n<td><strong>\u5149\u7ebf\u8ffd\u8e2a\u6838\u5fc3<\/strong><\/td>\n<td>72 RT Cores<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e2b\u0e19\u0e48\u0e27\u0e22\u0e04\u0e27\u0e32\u0e21\u0e08\u0e4d\u0e32<\/strong><\/td>\n<td>24 GB GDDR6 \u0e1e\u0e23\u0e49\u0e2d\u0e21 ECC (Error\u2010Correcting Code)<\/td>\n<\/tr>\n<tr>\n<td><strong>\u5185\u5b58\u5e26\u5bbd<\/strong><\/td>\n<td>Memory Bandwidth: 624\u2013672 GB\/s<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e1b\u0e23\u0e30\u0e2a\u0e34\u0e17\u0e18\u0e34\u0e20\u0e32\u0e1e FP32 (\u0e04\u0e23\u0e48\u0e32\u0e27\u0e46)<\/strong><\/td>\n<td>FP32 Performance: ~14.9 TFLOPS<\/td>\n<\/tr>\n<tr>\n<td><strong>RTX-OPS \/ Ray Tracing<\/strong><\/td>\n<td>RTX\u2010OPS: ~80T; Rays Cast: 10 Giga Rays\/sec<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e2d\u0e34\u0e19\u0e40\u0e17\u0e2d\u0e23\u0e4c\u0e40\u0e1f\u0e0b\u0e23\u0e30\u0e1a\u0e1a<\/strong><\/td>\n<td>PCI Express 3.0 x16<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e01\u0e4d\u0e32\u0e25\u0e31\u0e07\u0e44\u0e1f\u0e2a\u0e39\u0e07\u0e2a\u0e38\u0e14<\/strong><\/td>\n<td>Max Power Consumption: ~250 W<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e01\u0e32\u0e23\u0e23\u0e30\u0e1a\u0e32\u0e22\u0e04\u0e27\u0e32\u0e21\u0e23\u0e49\u0e2d\u0e19<\/strong><\/td>\n<td>Thermal Solution: Passive Heatsink<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e01\u0e32\u0e23\u0e40\u0e0a\u0e37\u0e48\u0e2d\u0e21\u0e15\u0e48\u0e2d NVLink<\/strong><\/td>\n<td>NVLink Interconnect: 100 GB\/s (\u0e2a\u0e4d\u0e32\u0e2b\u0e23\u0e31\u0e1a 2\u2010\u0e01\u0e32\u0e23\u0e4c\u0e14)<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e02\u0e19\u0e32\u0e14\u0e01\u0e32\u0e23\u0e4c\u0e14 (\u0e1b\u0e23\u0e30\u0e21\u0e32\u0e13)<\/strong><\/td>\n<td>Form Factor: Dual-slot, ~4.4\u2032\u2032 H \u00d7 10.5\u2032\u2032 L<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e23\u0e2d\u0e07\u0e23\u0e31\u0e1a\u0e01\u0e32\u0e23\u0e43\u0e0a\u0e49\u0e07\u0e32\u0e19 Quadro vDWS<\/strong><\/td>\n<td>\u0e23\u0e2d\u0e07\u0e23\u0e31\u0e1a Quadro Virtual Data Center Workstation (vDWS)<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e23\u0e2d\u0e07\u0e23\u0e31\u0e1a\u0e23\u0e30\u0e1a\u0e1a\u0e1b\u0e0f\u0e34\u0e1a\u0e31\u0e15\u0e34\u0e01\u0e32\u0e23<\/strong><\/td>\n<td>Windows (\u0e2b\u0e25\u0e32\u0e22\u0e40\u0e27\u0e2d\u0e23\u0e4c\u0e0a\u0e31\u0e19) \u0e41\u0e25\u0e30 Linux 64\u2010bit<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>Turing GPU<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>4,608 NVIDIA CUDA Cores<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>576 NVIDIA Tensor Cores<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>72 NVIDIA RT Cores<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>24GB GDDR6 Memory<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>Up to 624GB\/s Memory Bandwidth<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>14.9 TFLOPS FP32 Performance<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>29.9 TFLOPS FP16 Performance<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>238.9 TOPS INT8 Performance<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>119.4 TFLOPS of Tensor Operation<\/td>\n<\/tr>\n<tr>\n<td><strong>Max. Power Consumption<\/strong><\/td>\n<td>250W<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>Support Quadro vDWS<\/td>\n<\/tr>\n<tr>\n<td><strong>Max. Virtual Display Head Resolution<\/strong><\/td>\n<td>4096 x 2160<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>NVIDIA Quadro RTX 6000 Passive \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\u0e17\u0e35\u0e48\u0e43\u0e0a\u0e49\u0e2a\u0e16\u0e32\u0e1b\u0e31\u0e15\u0e22\u0e01\u0e23\u0e23\u0e21 Turing \u0e41\u0e25\u0e30\u0e2d\u0e2d\u0e01\u0e41\u0e1a\u0e1a\u0e14\u0e49\u0e27\u0e22\u0e23\u0e30\u0e1a\u0e1a\u0e23\u0e30\u0e1a\u0e32\u0e22\u0e04\u0e27\u0e32\u0e21\u0e23\u0e49\u0e2d\u0e19\u0e41\u0e1a\u0e1a\u0e1e\u0e32\u0e2a\u0e0b\u0e35\u0e1f (\u0e44\u0e21\u0e48\u0e21\u0e35\u0e1e\u0e31\u0e14\u0e25\u0e21) \u0e23\u0e38\u0e48\u0e19\u0e19\u0e35\u0e49\u0e44\u0e14\u0e49\u0e23\u0e31\u0e1a\u0e01\u0e32\u0e23\u0e1e\u0e31\u0e12\u0e19\u0e32\u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e43\u0e0a\u0e49\u0e07\u0e32\u0e19\u0e43\u0e19\u0e28\u0e39\u0e19\u0e22\u0e4c\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25\u0e41\u0e25\u0e30\u0e23\u0e30\u0e1a\u0e1a\u0e17\u0e35\u0e48\u0e15\u0e49\u0e2d\u0e07\u0e01\u0e32\u0e23\u0e04\u0e27\u0e32\u0e21\u0e40\u0e07\u0e35\u0e22\u0e1a\u0e41\u0e25\u0e30\u0e04\u0e27\u0e32\u0e21\u0e40\u0e0a\u0e37\u0e48\u0e2d\u0e16\u0e37\u0e2d\u0e2a\u0e39\u0e07 \u0e21\u0e32\u0e1e\u0e23\u0e49\u0e2d\u0e21\u0e01\u0e31\u0e1a CUDA, Tensor, \u0e41\u0e25\u0e30 RT Cores \u0e0a\u0e48\u0e27\u0e22\u0e43\u0e2b\u0e49\u0e23\u0e2d\u0e07\u0e23\u0e31\u0e1a\u0e07\u0e32\u0e19\u0e14\u0e49\u0e32\u0e19 AI, \u0e01\u0e32\u0e23\u0e40\u0e23\u0e19\u0e40\u0e14\u0e2d\u0e23\u0e4c, \u0e41\u0e25\u0e30 ray tracing \u0e41\u0e1a\u0e1a\u0e40\u0e23\u0e35\u0e22\u0e25\u0e44\u0e17\u0e21\u0e4c\u0e44\u0e14\u0e49\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e21\u0e35\u0e1b\u0e23\u0e30\u0e2a\u0e34\u0e17\u0e18\u0e34\u0e20\u0e32\u0e1e<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>The NVIDIA Quadro RTX 6000 Passive is a professional-grade graphics card based on the Turing architecture, featuring a fan-less (passive) cooling design tailored for data center and server environments that demand silent and reliable performance. Equipped with CUDA, Tensor, and RT cores, it excels in AI workflows, rendering, and real-time ray tracing tasks.<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>The Quadro RTX 6000 Passive delivers top-tier GPU and AI performance in a silent, reliable form factor. It houses powerful CUDA, Tensor, and RT cores, 24GB of ECC GDDR6 memory, and NVLink support for scalable multi-GPU systems. Despite the absence of fans, it supports real-time ray tracing, rendering, and AI inference with dependable stability\u2014perfect for professional data center environments that demand high performance without acoustic noise.<\/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 Quadro RTX6000 Passive<\/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":19219,"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-18974","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\/zh\/wp-json\/wp\/v2\/product\/18974","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=18974"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/media\/19219"}],"wp:attachment":[{"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/media?parent=18974"}],"wp:term":[{"taxonomy":"product_brand","embeddable":true,"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/product_brand?post=18974"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/product_cat?post=18974"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/droneth.or.th\/zh\/wp-json\/wp\/v2\/product_tag?post=18974"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}