{"id":1621,"date":"2025-08-29T10:20:19","date_gmt":"2025-08-29T09:20:19","guid":{"rendered":"https:\/\/shyuxinpc.com\/?post_type=product&#038;p=1621"},"modified":"2025-09-12T07:33:19","modified_gmt":"2025-09-12T06:33:19","slug":"leadtek-nvidia-rtx-a1000-8gb-ddr6","status":"publish","type":"product","link":"https:\/\/shyuxinpc.com\/cn\/product\/leadtek-nvidia-rtx-a1000-8gb-ddr6\/","title":{"rendered":"LEADTEK NVIDIA RTX A1000 8GB DDR6"},"content":{"rendered":"<h3 class=\"title-large text-NV text-center\">Unleash the Power of RTX. Now for Every Workstation.<\/h3>\n<div class=\"intro-large-text text-center\">\n<p>The NVIDIA RTX\u2122 A1000 desktop GPU, powered by NVIDIA Ampere GPU architecture, combines powerful graphics, rendering, ray tracing, and AI capabilities that far exceed what desktop workstations with CPU-based integrated graphics can provide.<\/p>\n<p>The RTX A1000 features 8GB of memory to empower professionals to maximize their productivity with the latest graphics-intensive software, AI-accelerated tools, and multi-app workflows from the desktop. It also enables an expansive visual workspace with quad display outputs. With 50% faster graphics performance than the previous generation, RTX A1000 GPUs provide full professional performance in a small form factor.<\/p>\n<h4 class=\"media-heading text-NV\">NVIDIA Ampere Architecture<\/h4>\n<p>NVIDIA RTX A1000 is the most powerful, single slot, low profile, professional solution for CAD, DCC, financial service industry (FSI) and visualization professionals looking to reach excellent performance in a compact and efficient form factor. Building upon the major SM enhancements from the Turing GPU, the NVIDIA Ampere architecture enhances ray tracing operations, tensor matrix operations, and concurrent executions of FP32 and INT32 operations.<\/p>\n<h4 class=\"media-heading text-NV\">CUDA Cores<\/h4>\n<p>The NVIDIA Ampere architecture-based CUDA cores bring up to 2.7X the single-precision floating point (FP32) throughput compared to the previous generation, providing significant performance improvements for graphics and rendering workflows such as 2D graphics, 3D model development, basic photo and video editing and compute for workloads such as data analysis and general productivity. RTX A1000 enables two FP32 primary data paths, doubling the peak FP32 operations.<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"<table class=\"table table-bordered newtable\">\n<tbody>\n<tr class=\"odd-row\">\n<td class=\"first\">GPU Architecture<\/td>\n<td class=\"last\">NVIDIA Ampere Architecture<\/td>\n<\/tr>\n<tr>\n<td class=\"first\">CUDA Parallel Processing cores<\/td>\n<td class=\"last\">2,304<\/td>\n<\/tr>\n<tr class=\"odd-row\">\n<td class=\"first\">NVIDIA Tensor Corese<\/td>\n<td class=\"last\">72<\/td>\n<\/tr>\n<tr>\n<td class=\"first\">NVIDIA RT Cores<\/td>\n<td class=\"last\">18<\/td>\n<\/tr>\n<tr class=\"odd-row\">\n<td class=\"first\">Single-Precision Performance<sup>1<\/sup><\/td>\n<td class=\"last\">6.74 TFLOPS<\/td>\n<\/tr>\n<tr>\n<td class=\"first\">RT Core Performance<sup>1<\/sup><\/td>\n<td class=\"last\">13.2 TFLOPS<\/td>\n<\/tr>\n<tr class=\"odd-row\">\n<td class=\"first\">FP16 Tensor Performance<sup>1<\/sup><\/td>\n<td class=\"last\">53.8 TFLOPS<sup>2<\/sup><\/td>\n<\/tr>\n<tr>\n<td class=\"first\">GPU Memory<\/td>\n<td class=\"last\">8GB GDDR6<\/td>\n<\/tr>\n<tr class=\"odd-row\">\n<td class=\"first\">Memory Interface<\/td>\n<td class=\"last\">128-bit<\/td>\n<\/tr>\n<tr>\n<td class=\"first\">Memory Bandwidth<\/td>\n<td class=\"last\">192 GB\/s<\/td>\n<\/tr>\n<tr class=\"odd-row\">\n<td class=\"first\">Max Power Consumption<\/td>\n<td class=\"last\">50W<\/td>\n<\/tr>\n<tr>\n<td class=\"first\">Graphics Bus<\/td>\n<td class=\"last\">PPCI Express 4.0 x8\u00a0<sup>3<\/sup><\/td>\n<\/tr>\n<tr class=\"odd-row\">\n<td class=\"first\">Display Connectors<\/td>\n<td class=\"last\">mDP 1.4 (4)<\/td>\n<\/tr>\n<tr>\n<td class=\"first\">Form Factor<\/td>\n<td class=\"last\">2.7\u201d H x 6.4\u201d L Single Slot<\/td>\n<\/tr>\n<tr class=\"odd-row\">\n<td class=\"first\">Product Weight<\/td>\n<td class=\"last\">140 g (Low Profile Bracket)<br \/>\n146 g (ATX Bracket)<\/td>\n<\/tr>\n<tr>\n<td class=\"first\">Thermal Solution<\/td>\n<td class=\"last\">Active<\/td>\n<\/tr>\n<tr class=\"odd-row\">\n<td class=\"first\">NVENC | NVDEC<\/td>\n<td class=\"last\">1x | 2x (+AV1 encode &amp; decode)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>","protected":false},"featured_media":1622,"comment_status":"open","ping_status":"closed","template":"","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0},"product_brand":[],"product_cat":[49],"product_tag":[],"class_list":{"0":"post-1621","1":"product","2":"type-product","3":"status-publish","4":"has-post-thumbnail","6":"product_cat-gpu","8":"first","9":"instock","10":"sale","11":"taxable","12":"shipping-taxable","13":"purchasable","14":"product-type-simple"},"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/shyuxinpc.com\/cn\/wp-json\/wp\/v2\/product\/1621","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/shyuxinpc.com\/cn\/wp-json\/wp\/v2\/product"}],"about":[{"href":"https:\/\/shyuxinpc.com\/cn\/wp-json\/wp\/v2\/types\/product"}],"replies":[{"embeddable":true,"href":"https:\/\/shyuxinpc.com\/cn\/wp-json\/wp\/v2\/comments?post=1621"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/shyuxinpc.com\/cn\/wp-json\/wp\/v2\/media\/1622"}],"wp:attachment":[{"href":"https:\/\/shyuxinpc.com\/cn\/wp-json\/wp\/v2\/media?parent=1621"}],"wp:term":[{"taxonomy":"product_brand","embeddable":true,"href":"https:\/\/shyuxinpc.com\/cn\/wp-json\/wp\/v2\/product_brand?post=1621"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/shyuxinpc.com\/cn\/wp-json\/wp\/v2\/product_cat?post=1621"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/shyuxinpc.com\/cn\/wp-json\/wp\/v2\/product_tag?post=1621"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}