{"id":14462,"date":"2026-10-05T23:50:35","date_gmt":"2026-10-05T20:50:35","guid":{"rendered":"https:\/\/gtmteknoloji.com\/b2b\/?post_type=product&#038;p=14462"},"modified":"2026-10-05T23:50:35","modified_gmt":"2026-10-05T20:50:35","slug":"nvidia-igx-thor-developer-kit","status":"publish","type":"product","link":"https:\/\/gtmteknoloji.com\/b2b\/magaza\/edge-ai\/nvidia-igx\/nvidia-igx-thor-developer-kit\/","title":{"rendered":"NVIDIA IGX Thor Developer Kit"},"content":{"rendered":"<style>\n.gtm-product{\n  max-width:820px;\n  margin:0 auto;\n  font-family:Arial,Helvetica,sans-serif;\n  color:#263238;\n  line-height:1.65;\n}<\/p>\n<p>.gtm-product h2{\n  font-size:24px;\n  margin:32px 0 14px;\n  color:#1f2933;\n}<\/p>\n<p>.gtm-product p{\n  margin:0 0 15px;\n}<\/p>\n<p>.gtm-summary{\n  background:#f5f8f1;\n  border-left:4px solid #76B900;\n  padding:18px 20px;\n  margin:20px 0 28px;\n  border-radius:6px;\n}<\/p>\n<p>.gtm-features{\n  display:grid;\n  grid-template-columns:repeat(2,minmax(0,1fr));\n  gap:14px;\n  margin:20px 0 30px;\n}<\/p>\n<p>.gtm-feature{\n  border:1px solid #e3e7ea;\n  border-radius:8px;\n  padding:16px;\n  background:#fff;\n}<\/p>\n<p>.gtm-feature strong{\n  display:block;\n  color:#4d7f1c;\n  margin-bottom:5px;\n}<\/p>\n<p>.gtm-table-wrap{\n  width:100%;\n  overflow-x:auto;\n  margin:18px 0 30px;\n}<\/p>\n<p>.gtm-table{\n  width:100%;\n  border-collapse:collapse;\n  min-width:600px;\n}<\/p>\n<p>.gtm-table th,\n.gtm-table td{\n  padding:12px 14px;\n  border:1px solid #e2e6e9;\n  text-align:left;\n  vertical-align:top;\n}<\/p>\n<p>.gtm-table th{\n  width:34%;\n  background:#76B900;\n  color:#fff;\n  font-weight:600;\n}<\/p>\n<p>.gtm-table tr:hover td{\n  background:#f3f9eb;\n}<\/p>\n<p>.gtm-apps{\n  display:flex;\n  flex-wrap:wrap;\n  gap:8px;\n  margin:14px 0 28px;\n}<\/p>\n<p>.gtm-apps span{\n  background:#f1f6eb;\n  border:1px solid #dceacb;\n  padding:7px 11px;\n  border-radius:18px;\n  font-size:14px;\n}<\/p>\n<p>@media(max-width:640px){\n  .gtm-product{\n    padding:0 12px;\n  }<\/p>\n<p>  .gtm-features{\n    grid-template-columns:1fr;\n  }<\/p>\n<p>  .gtm-product h2{\n    font-size:21px;\n  }<\/p>\n<p>  .gtm-table th,\n  .gtm-table td{\n    padding:10px;\n    font-size:14px;\n  }\n}\n<\/style>\n<article class=\"gtm-product\">\n<div class=\"gtm-summary\">\n    <strong>NVIDIA IGX Thor Developer Kit<\/strong>, fiziksel yapay zeka ve edge AI uygulamalar\u0131 i\u00e7in geli\u015ftirilen kurumsal s\u0131n\u0131f bir platformdur. \u00d6zellikle NVIDIA Blackwell mimarili GPU, 14 \u00e7ekirdek Arm Neoverse-V3AE CPU ve 128 GB LPDDR5X bellek, y\u00fcksek i\u015flem kapasitesi sa\u011flar. Ayr\u0131ca geli\u015fmi\u015f a\u011f ve geni\u015fleme altyap\u0131s\u0131, farkl\u0131 sens\u00f6r ve AI sistemlerinin entegrasyonunu kolayla\u015ft\u0131r\u0131r. B\u00f6ylece IGX Thor, robotik ve ger\u00e7ek zamanl\u0131 fiziksel AI projeleri i\u00e7in g\u00fc\u00e7l\u00fc bir temel sunar.\n  <\/div>\n<h2>\u00d6ne \u00c7\u0131kan \u00d6zellikler<\/h2>\n<div class=\"gtm-features\">\n<div class=\"gtm-feature\">\n      <strong>NVIDIA Blackwell GPU<\/strong><br \/>\n      Entegre NVIDIA Blackwell GPU, 2.560 CUDA \u00e7ekirde\u011fi ve 96 adet 5. nesil Tensor Core sunar. B\u00f6ylece geli\u015fmi\u015f yapay zeka modelleri do\u011frudan edge ortam\u0131nda \u00e7al\u0131\u015ft\u0131r\u0131labilir.\n    <\/div>\n<div class=\"gtm-feature\">\n      <strong>14 \u00c7ekirdek Arm CPU<\/strong><br \/>\n      Arm Neoverse-V3AE tabanl\u0131 64-bit CPU, 14 \u00e7ekirdek ve 2.6 GHz&#8217;e kadar \u00e7al\u0131\u015fma frekans\u0131 sunar. Ayr\u0131ca g\u00fc\u00e7l\u00fc CPU altyap\u0131s\u0131, GPU tabanl\u0131 i\u015f y\u00fcklerini tamamlar.\n    <\/div>\n<div class=\"gtm-feature\">\n      <strong>128 GB LPDDR5X<\/strong><br \/>\n      Sistem, 128 GB LPDDR5X bellek ve 256-bit bellek aray\u00fcz\u00fc kullan\u0131r. Bu sayede 273 GB\/s bant geni\u015fli\u011fiyle yo\u011fun AI ve sens\u00f6r i\u015fleme g\u00f6revleri desteklenir.\n    <\/div>\n<div class=\"gtm-feature\">\n      <strong>Y\u00fcksek H\u0131zl\u0131 A\u011f<\/strong><br \/>\n      IGX Thor, y\u00fcksek bant geni\u015fli\u011fi gerektiren end\u00fcstriyel ve robotik sistemleri hedefler. Ayr\u0131ca a\u011f altyap\u0131s\u0131, b\u00fcy\u00fck veri ak\u0131\u015flar\u0131n\u0131n d\u00fc\u015f\u00fck gecikmeyle aktar\u0131lmas\u0131na yard\u0131mc\u0131 olur.\n    <\/div>\n<div class=\"gtm-feature\">\n      <strong>PCIe Gen5<\/strong><br \/>\n      PCIe Gen5 x8 ve x16 geni\u015fleme ba\u011flant\u0131lar\u0131 bulunur. B\u00f6ylece ek GPU, a\u011f adapt\u00f6r\u00fc veya farkl\u0131 h\u0131zland\u0131r\u0131c\u0131lar sisteme entegre edilebilir.\n    <\/div>\n<div class=\"gtm-feature\">\n      <strong>Fiziksel AI Odakl\u0131 Tasar\u0131m<\/strong><br \/>\n      Platform, yapay zeka \u00e7\u0131kar\u0131m\u0131 ile ger\u00e7ek zamanl\u0131 sens\u00f6r verilerini ayn\u0131 sistem \u00fczerinde i\u015flemek i\u00e7in geli\u015ftirilmi\u015ftir. \u00d6zellikle robotik ve end\u00fcstriyel otomasyon projelerini hedefler.\n    <\/div>\n<\/p><\/div>\n<h2>T\u00fcm \u00d6zellikler<\/h2>\n<div class=\"gtm-table-wrap\">\n<table class=\"gtm-table\">\n<tbody>\n<tr>\n<th>Marka<\/th>\n<td>NVIDIA<\/td>\n<\/tr>\n<tr>\n<th>\u00dcr\u00fcn Ailesi<\/th>\n<td>NVIDIA IGX<\/td>\n<\/tr>\n<tr>\n<th>Model<\/th>\n<td>IGX Thor Developer Kit<\/td>\n<\/tr>\n<tr>\n<th>Platform<\/th>\n<td>NVIDIA IGX Thor<\/td>\n<\/tr>\n<tr>\n<th>GPU Mimarisi<\/th>\n<td>NVIDIA Blackwell<\/td>\n<\/tr>\n<tr>\n<th>Entegre GPU<\/th>\n<td>2.560 CUDA \u00e7ekirde\u011fi<\/td>\n<\/tr>\n<tr>\n<th>Tensor Core<\/th>\n<td>96x 5. Nesil Tensor Core<\/td>\n<\/tr>\n<tr>\n<th>Multi-Instance GPU<\/th>\n<td>MIG, 10 TPC<\/td>\n<\/tr>\n<tr>\n<th>iGPU Maksimum Frekans<\/th>\n<td>1.57 GHz<\/td>\n<\/tr>\n<tr>\n<th>CPU<\/th>\n<td>14 \u00c7ekirdek Arm Neoverse-V3AE 64-bit<\/td>\n<\/tr>\n<tr>\n<th>CPU L2 \u00d6nbellek<\/th>\n<td>\u00c7ekirdek ba\u015f\u0131na 1 MB<\/td>\n<\/tr>\n<tr>\n<th>CPU L3 \u00d6nbellek<\/th>\n<td>16 MB Payla\u015f\u0131lan Sistem L3<\/td>\n<\/tr>\n<tr>\n<th>CPU Maksimum Frekans<\/th>\n<td>2.6 GHz<\/td>\n<\/tr>\n<tr>\n<th>Vision Accelerator<\/th>\n<td>1x PVA v3<\/td>\n<\/tr>\n<tr>\n<th>Bellek<\/th>\n<td>128 GB LPDDR5X<\/td>\n<\/tr>\n<tr>\n<th>Bellek Veri Yolu<\/th>\n<td>256-bit<\/td>\n<\/tr>\n<tr>\n<th>Bellek Bant Geni\u015fli\u011fi<\/th>\n<td>273 GB\/s<\/td>\n<\/tr>\n<tr>\n<th>Depolama<\/th>\n<td>M.2 Key M, PCIe Gen5 x2<\/td>\n<\/tr>\n<tr>\n<th>Video Encode<\/th>\n<td>2x NVEncode (iGPU)<\/td>\n<\/tr>\n<tr>\n<th>Video Decode<\/th>\n<td>2x NVDecode (iGPU)<\/td>\n<\/tr>\n<tr>\n<th>PCIe<\/th>\n<td>2x PCIe Gen5 (x8, x16)<\/td>\n<\/tr>\n<tr>\n<th>USB<\/th>\n<td>1x USB 3.2 Type-C, 4x USB 3.2 Type-A<\/td>\n<\/tr>\n<tr>\n<th>G\u00f6r\u00fcnt\u00fc \u00c7\u0131k\u0131\u015f\u0131<\/th>\n<td>DisplayPort 1.4a<\/td>\n<\/tr>\n<tr>\n<th>Opsiyonel dGPU<\/th>\n<td>NVIDIA RTX PRO Blackwell dGPU deste\u011fi<\/td>\n<\/tr>\n<\/tbody>\n<\/table><\/div>\n<h2>Fiziksel AI ve Edge Uygulamalar\u0131<\/h2>\n<p>\n    NVIDIA IGX Thor Developer Kit, ger\u00e7ek zamanl\u0131 yapay zeka \u00e7\u0131kar\u0131m\u0131 ve sens\u00f6r i\u015fleme g\u00f6revlerini edge ortam\u0131nda ger\u00e7ekle\u015ftirmek i\u00e7in geli\u015ftirilmi\u015ftir. \u00d6zellikle Blackwell tabanl\u0131 GPU, g\u00f6r\u00fcnt\u00fc ve sens\u00f6r verilerinin do\u011frudan sistem \u00fczerinde i\u015flenmesine yard\u0131mc\u0131 olur.\n  <\/p>\n<p>\n    Bununla birlikte, 14 \u00e7ekirdek Arm Neoverse-V3AE CPU genel sistem i\u015f y\u00fcklerini y\u00f6netir. Ayr\u0131ca 128 GB LPDDR5X bellek, b\u00fcy\u00fck AI modelleri ve y\u00fcksek veri yo\u011funlu\u011funa sahip uygulamalar i\u00e7in geni\u015f \u00e7al\u0131\u015fma alan\u0131 sa\u011flar.\n  <\/p>\n<p>\n    Bellek altyap\u0131s\u0131 273 GB\/s bant geni\u015fli\u011fi sunar. Bu sayede kamera, sens\u00f6r ve di\u011fer ger\u00e7ek zamanl\u0131 veri kaynaklar\u0131ndan gelen bilgiler h\u0131zl\u0131 \u015fekilde i\u015flenebilir.\n  <\/p>\n<p>\n    Ayr\u0131ca PCIe Gen5 ba\u011flant\u0131lar\u0131, sistemin farkl\u0131 h\u0131zland\u0131r\u0131c\u0131larla geni\u015fletilmesini sa\u011flar. B\u00f6ylece platform, projenin performans ve ba\u011flant\u0131 ihtiya\u00e7lar\u0131na g\u00f6re \u00f6l\u00e7eklenebilir.\n  <\/p>\n<h2>Blackwell ile Y\u00fcksek AI Performans\u0131<\/h2>\n<p>\n    NVIDIA Blackwell mimarisi, yeni nesil Tensor Core altyap\u0131s\u0131yla fiziksel AI i\u015f y\u00fcklerini h\u0131zland\u0131r\u0131r. \u00d6zellikle 96 adet 5. nesil Tensor Core, \u00fcretken AI ve geli\u015fmi\u015f \u00e7\u0131kar\u0131m senaryolar\u0131na y\u00f6nelik i\u015flem kapasitesi sunar.\n  <\/p>\n<p>\n    Bunun yan\u0131nda Multi-Instance GPU deste\u011fi, GPU kaynaklar\u0131n\u0131n farkl\u0131 i\u015f y\u00fckleri aras\u0131nda b\u00f6l\u00fc\u015ft\u00fcr\u00fclmesine olanak tan\u0131r. B\u00f6ylece ayn\u0131 platform \u00fczerinde birden fazla AI uygulamas\u0131 daha esnek \u015fekilde y\u00f6netilebilir.\n  <\/p>\n<h2>Geni\u015fletilebilir Platform<\/h2>\n<p>\n    IGX Thor Developer Kit, yaln\u0131zca entegre GPU ile s\u0131n\u0131rl\u0131 de\u011fildir. Ayr\u0131ca PCIe Gen5 altyap\u0131s\u0131 \u00fczerinden NVIDIA RTX PRO Blackwell s\u0131n\u0131f\u0131 ayr\u0131k GPU se\u00e7enekleriyle geni\u015fletilebilir.\n  <\/p>\n<p>\n    Bu nedenle kullan\u0131c\u0131lar, temel edge AI uygulamalar\u0131ndan daha yo\u011fun grafik ve yapay zeka i\u015f y\u00fcklerine kadar farkl\u0131 sistem yap\u0131land\u0131rmalar\u0131 olu\u015fturabilir. Sonu\u00e7 olarak platform, geli\u015ftirme a\u015famas\u0131ndan \u00fcretim ortam\u0131na kadar farkl\u0131 kullan\u0131m senaryolar\u0131na uyarlanabilir.\n  <\/p>\n<h2>Kullan\u0131m Alanlar\u0131<\/h2>\n<div class=\"gtm-apps\">\n    <span>Robotik<\/span><br \/>\n    <span>Fiziksel AI<\/span><br \/>\n    <span>End\u00fcstriyel AI<\/span><br \/>\n    <span>Medikal AI<\/span><br \/>\n    <span>G\u00f6rsel AI<\/span><br \/>\n    <span>Sens\u00f6r \u0130\u015fleme<\/span><br \/>\n    <span>Edge AI<\/span><br \/>\n    <span>Ak\u0131ll\u0131 Makineler<\/span>\n  <\/div>\n<\/article>\n","protected":false},"excerpt":{"rendered":"<p>NVIDIA IGX Thor Developer Kit, fiziksel yapay zeka ve edge AI uygulamalar\u0131 i\u00e7in geli\u015ftirilen kurumsal s\u0131n\u0131f bir geli\u015ftirme platformudur. NVIDIA Blackwell mimarili entegre GPU, 14 \u00e7ekirdek Arm Neoverse-V3AE CPU, 128 GB LPDDR5X bellek ve NVIDIA ConnectX-7 a\u011f altyap\u0131s\u0131yla robotik, end\u00fcstriyel otomasyon ve medikal AI uygulamalar\u0131n\u0131 destekler.<\/p>\n","protected":false},"featured_media":14463,"comment_status":"open","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":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-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":"","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-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":"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":""},"mobile":{"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":""}}},"product_brand":[22],"product_cat":[1010,2643],"product_tag":[],"gtm_use_case":[],"class_list":["post-14462","product","type-product","status-publish","has-post-thumbnail","product_brand-nvidia","product_cat-edge-ai","product_cat-nvidia-igx","desktop-align-left","tablet-align-left","mobile-align-left","first","instock","taxable","shipping-taxable","product-type-simple"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>NVIDIA IGX Thor Developer Kit | Edge AI Platformu<\/title>\n<meta name=\"description\" content=\"NVIDIA IGX Thor Developer Kit; 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