{"id":18975,"date":"2026-09-16T20:14:25","date_gmt":"2026-09-16T13:14:25","guid":{"rendered":"https:\/\/droneth.or.th\/product\/nvidia-quadro-rtx8000\/"},"modified":"2026-09-16T20:14:25","modified_gmt":"2026-09-16T13:14:25","slug":"nvidia-quadro-rtx8000","status":"publish","type":"product","link":"https:\/\/droneth.or.th\/ja\/product\/nvidia-quadro-rtx8000\/","title":{"rendered":"NVIDIA Quadro RTX8000"},"content":{"rendered":"<p><strong>NVIDIA Quadro RTX8000<\/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>\u30bb\u30af\u30b7\u30e7\u30f3<\/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 (\u0e20\u0e32\u0e29\u0e32\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\u30b3\u30a2<\/strong><\/td>\n<td>CUDA Cores: 4,608<\/td>\n<\/tr>\n<tr>\n<td><strong>\u30c6\u30f3\u30bd\u30eb\u30b3\u30a2<\/strong><\/td>\n<td>Tensor Cores: 576<\/td>\n<\/tr>\n<tr>\n<td><strong>RT\u30b3\u30a2<\/strong><\/td>\n<td>RT Cores: 72<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e2b\u0e19\u0e48\u0e27\u0e22\u0e04\u0e27\u0e32\u0e21\u0e08\u0e4d\u0e32<\/strong><\/td>\n<td>Memory: 48 GB GDDR6 with ECC<\/td>\n<\/tr>\n<tr>\n<td><strong>\u30e1\u30e2\u30ea\u5e2f\u57df\u5e45<\/strong><\/td>\n<td>Memory Bandwidth: up to 672 GB\/s<\/td>\n<\/tr>\n<tr>\n<td><strong>FP32 Performance<\/strong><\/td>\n<td>FP32 Performance: ~16.3 TFLOPS<\/td>\n<\/tr>\n<tr>\n<td><strong>FP16 Performance<\/strong><\/td>\n<td>FP16 Performance: ~32.6 TFLOPS<\/td>\n<\/tr>\n<tr>\n<td><strong>INT8 Performance<\/strong><\/td>\n<td>INT8 Performance: ~65.8 TOPS<\/td>\n<\/tr>\n<tr>\n<td><strong>Deep Learning Perf.<\/strong><\/td>\n<td>Tensor TFLOPS: ~130.5<\/td>\n<\/tr>\n<tr>\n<td><strong>RTX-OPS &amp; Ray Casting<\/strong><\/td>\n<td>RTX-OPS: 84T; Rays Cast: ~11 Giga Rays\/sec<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e01\u0e32\u0e23\u0e40\u0e0a\u0e37\u0e48\u0e2d\u0e21\u0e15\u0e48\u0e2d\u0e23\u0e30\u0e1a\u0e1a<\/strong><\/td>\n<td>Interface: PCI Express 3.0 x16<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e01\u0e32\u0e23\u0e40\u0e0a\u0e37\u0e48\u0e2d\u0e21\u0e15\u0e48\u0e2d\u0e08\u0e2d\u0e41\u0e2a\u0e14\u0e07\u0e1c\u0e25<\/strong><\/td>\n<td>Display: 4\u00d7 DisplayPort 1.4 + 1\u00d7 VirtualLink<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e01\u0e32\u0e23\u0e1a\u0e23\u0e34\u0e42\u0e20\u0e04\u0e1e\u0e25\u0e31\u0e07\u0e07\u0e32\u0e19\u0e2a\u0e39\u0e07\u0e2a\u0e38\u0e14<\/strong><\/td>\n<td>Max Power: ~295 W (board), ~260 W (graphics)<\/td>\n<\/tr>\n<tr>\n<td><strong>NVLink \u0e23\u0e2d\u0e07\u0e23\u0e31\u0e1a<\/strong><\/td>\n<td>NVLink: up to 100 GB\/s (multi\u2010GPU)<\/td>\n<\/tr>\n<tr>\n<td><strong>\u0e02\u0e19\u0e32\u0e14\u0e01\u0e32\u0e23\u0e4c\u0e14<\/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>\u0e01\u0e32\u0e23\u0e23\u0e2d\u0e07\u0e23\u0e31\u0e1a VR \u0e41\u0e25\u0e30 Mosaic<\/strong><\/td>\n<td>VR Ready + Mosaic multi-display support<\/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>48GB GDDR6 Memory<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>Up to 672GB\/s Memory Bandwidth<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>16.3 TFLOPS FP32 Performance<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>32.6 TFLOPS FP16 Performance<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>65.8 TOPS INT8 Performance<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>130.5 TFLOPS of Tensor Operation<\/td>\n<\/tr>\n<tr>\n<td><strong>Max. Power Consumption<\/strong><\/td>\n<td>295W<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>4x DisplayPort 1.4<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>NVIDIA Quadro RTX 8000 \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 \u0e1c\u0e2a\u0e32\u0e19\u0e40\u0e17\u0e04\u0e42\u0e19\u0e42\u0e25\u0e22\u0e35 RT Cores \u0e2a\u0e4d\u0e32\u0e2b\u0e23\u0e31\u0e1a\u0e01\u0e32\u0e23\u0e40\u0e25\u0e47\u0e07\u0e41\u0e2a\u0e07 (ray tracing) \u0e41\u0e1a\u0e1a\u0e40\u0e23\u0e35\u0e22\u0e25\u0e44\u0e17\u0e21\u0e4c, Tensor Cores \u0e2a\u0e4d\u0e32\u0e2b\u0e23\u0e31\u0e1a\u0e07\u0e32\u0e19 AI \u0e41\u0e25\u0e30\u0e2b\u0e19\u0e48\u0e27\u0e22\u0e1b\u0e23\u0e30\u0e21\u0e27\u0e25\u0e1c\u0e25 CUDA \u0e08\u0e4d\u0e32\u0e19\u0e27\u0e19\u0e21\u0e32\u0e01 \u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e21\u0e2d\u0e1a\u0e1b\u0e23\u0e30\u0e2a\u0e34\u0e17\u0e18\u0e34\u0e20\u0e32\u0e1e\u0e17\u0e31\u0e49\u0e07\u0e14\u0e49\u0e32\u0e19\u0e01\u0e23\u0e32\u0e1f\u0e34\u0e01\u0e41\u0e25\u0e30\u0e01\u0e32\u0e23\u0e40\u0e23\u0e35\u0e22\u0e19\u0e23\u0e39\u0e49\u0e40\u0e0a\u0e34\u0e07\u0e25\u0e36\u0e01\u0e1e\u0e23\u0e49\u0e2d\u0e21\u0e2b\u0e19\u0e48\u0e27\u0e22\u0e04\u0e27\u0e32\u0e21\u0e08\u0e4d\u0e32 GDDR6 \u0e02\u0e19\u0e32\u0e14\u0e21\u0e2b\u0e32\u0e28\u0e32\u0e25 48 GB (\u0e1e\u0e23\u0e49\u0e2d\u0e21 ECC) \u0e1e\u0e23\u0e49\u0e2d\u0e21\u0e23\u0e2d\u0e07\u0e23\u0e31\u0e1a\u0e01\u0e32\u0e23\u0e02\u0e22\u0e32\u0e22\u0e27\u0e34\u0e2a\u0e31\u0e22\u0e17\u0e31\u0e28\u0e19\u0e4c\u0e1c\u0e48\u0e32\u0e19 NVLink \u0e41\u0e25\u0e30 VirtualLink \u0e2a\u0e4d\u0e32\u0e2b\u0e23\u0e31\u0e1a\u0e07\u0e32\u0e19 VR \u0e04\u0e27\u0e32\u0e21\u0e25\u0e30\u0e40\u0e2d\u0e35\u0e22\u0e14\u0e2a\u0e39\u0e07<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>The NVIDIA Quadro RTX 8000 is a professional-grade graphics card built on the Turing architecture, featuring dedicated RT Cores for real-time ray tracing, Tensor Cores for AI acceleration, and the parallel power of CUDA. It boasts a massive 48 GB of ECC GDDR6 memory and supports expansion through NVLink and VirtualLink for high-resolution VR and multi-GPU workloads<\/td>\n<\/tr>\n<tr>\n<td><strong>Technical detail<\/strong><\/td>\n<td>The Quadro RTX 8000 stands as the ultimate professional GPU, combining the power of Turing architecture with dedicated RT Cores for real-time ray tracing, Tensor Cores for AI computations, and robust CUDA capabilities. It shines in rendering, AI, and massive data processing tasks, backed by 48GB ECC GDDR6 memory, NVLink for scalable multi-GPU setups, and VirtualLink for high-resolution VR support. This full-featured configuration makes the Quadro RTX 8000 a top-tier choice for professionals demanding unmatched performance and reliability<\/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 RTX8000<\/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":19220,"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-18975","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\/ja\/wp-json\/wp\/v2\/product\/18975","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/droneth.or.th\/ja\/wp-json\/wp\/v2\/product"}],"about":[{"href":"https:\/\/droneth.or.th\/ja\/wp-json\/wp\/v2\/types\/product"}],"replies":[{"embeddable":true,"href":"https:\/\/droneth.or.th\/ja\/wp-json\/wp\/v2\/comments?post=18975"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/droneth.or.th\/ja\/wp-json\/wp\/v2\/media\/19220"}],"wp:attachment":[{"href":"https:\/\/droneth.or.th\/ja\/wp-json\/wp\/v2\/media?parent=18975"}],"wp:term":[{"taxonomy":"product_brand","embeddable":true,"href":"https:\/\/droneth.or.th\/ja\/wp-json\/wp\/v2\/product_brand?post=18975"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/droneth.or.th\/ja\/wp-json\/wp\/v2\/product_cat?post=18975"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/droneth.or.th\/ja\/wp-json\/wp\/v2\/product_tag?post=18975"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}