{"id":116412,"date":"2026-01-02T20:52:09","date_gmt":"2026-01-02T20:52:09","guid":{"rendered":"https:\/\/ekamu.net\/?p=116412"},"modified":"2026-01-02T20:52:09","modified_gmt":"2026-01-02T20:52:09","slug":"nvidia-gb200-nvl72-amdye-gore-buyuk-performans-farki-sagliyor","status":"publish","type":"post","link":"https:\/\/ekamu.net\/index.php\/2026\/01\/02\/nvidia-gb200-nvl72-amdye-gore-buyuk-performans-farki-sagliyor\/","title":{"rendered":"Nvidia GB200 NVL72, AMD\u2019ye g\u00f6re b\u00fcy\u00fck performans fark\u0131 sa\u011fl\u0131yor"},"content":{"rendered":"<p><figure> <span> <img decoding=\"async\" src=\"https:\/\/ekamu.net\/wp-content\/uploads\/2026\/01\/nvidia-gb200-nvl72-amdye-gore-buyuk-performans-farki-sagliyor-0-ruutEuat.jpg\"\/> <\/span> Yapay zeka d\u00fcnyas\u0131nda <strong>Mixture of Experts<\/strong> (MoE) mimarisine ge\u00e7i\u015f h\u0131z kazan\u0131rken bu alandaki donan\u0131m rekabeti de giderek sertle\u015fiyor. Signal65 taraf\u0131ndan yay\u0131mlanan ve SemiAnalysis\u2019in InferenceMAX \u00f6l\u00e7\u00fcmlerine dayanan yeni bir analiz, <strong>Nvidia<\/strong>\u2019n\u0131n Blackwell tabanl\u0131 <strong>GB200 NVL72<\/strong> raf sistemlerinin <strong>AMD<\/strong>\u2019nin <strong>Instinct MI355X<\/strong> \u00e7\u00f6z\u00fcmlerine k\u0131yasla dikkat \u00e7ekici bir \u00fcst\u00fcnl\u00fck sa\u011flad\u0131\u011f\u0131n\u0131 ortaya koydu. Test sonu\u00e7lar\u0131na g\u00f6re Nvidia, MoE i\u015f y\u00fcklerinde GPU ba\u015f\u0131na <strong>28 kata varan performans<\/strong> art\u0131\u015f\u0131 sunuyor. <\/figure>\n<p>Yapay zeka modelleri, kaynak kullan\u0131m\u0131n\u0131 daha verimli hale getirdi\u011fi i\u00e7in h\u0131zla MoE odakl\u0131 bir yap\u0131ya evriliyor. Bu yakla\u015f\u0131mda model, \u201cuzman\u201d olarak adland\u0131r\u0131lan ayr\u0131 alt a\u011flara b\u00f6l\u00fcn\u00fcyor ve her sorguda yaln\u0131zca ilgili uzmanlar \u00e7al\u0131\u015ft\u0131r\u0131l\u0131yor. Ancak bu yap\u0131da \u00f6l\u00e7ek b\u00fcy\u00fcd\u00fck\u00e7e d\u00fc\u011f\u00fcmler aras\u0131 yo\u011fun veri aktar\u0131m\u0131, gecikme ve bant geni\u015fli\u011fi bask\u0131s\u0131 gibi sorunlar da art\u0131yor. Bu nedenle Amazon Web Services (AWS), Google Cloud, Microsoft Azure ve Oracle Cloud gibi \u2018hiper\u00f6l\u00e7ekleyiciler\u201d yaln\u0131zca ham performansa de\u011fil, performans ba\u015f\u0131na maliyet dengesine de odaklan\u0131yor. Signal65\u2019in de\u011ferlendirmesine g\u00f6re, mevcut tabloda bu dengeyi en iyi sa\u011flayan \u00e7\u00f6z\u00fcm Nvidia GB200 NVL72 olarak \u00f6ne \u00e7\u0131k\u0131yor.<\/p>\n<p><b>72 \u00e7ip ve 30 TB payla\u015f\u0131ml\u0131 bellek<\/b><\/p>\n<figure> <span> <img decoding=\"async\" src=\"https:\/\/ekamu.net\/wp-content\/uploads\/2026\/01\/nvidia-gb200-nvl72-amdye-gore-buyuk-performans-farki-sagliyor-1-JZdewzM7.jpg\"\/> <\/span> Analizin dikkat \u00e7eken noktalar\u0131ndan biri, Nvidia\u2019n\u0131n performans fark\u0131n\u0131 nas\u0131l yaratt\u0131\u011f\u0131na dair teknik detaylar. \u015eirket, MoE \u00f6l\u00e7ekleme darbo\u011fazlar\u0131n\u0131 a\u015fmak i\u00e7in \u201cExtreme Co-Design\u201d ad\u0131n\u0131 verdi\u011fi bir yakla\u015f\u0131m benimsiyor. Bu strateji kapsam\u0131nda <strong>72 adet GB200 \u00e7ip, 30 TB<\/strong> y\u00fcksek h\u0131zl\u0131 <strong>payla\u015f\u0131ml\u0131 bellek<\/strong> ile tek bir raf sistemi i\u00e7inde entegre \u015fekilde \u00e7al\u0131\u015f\u0131yor. Bu mimarinin <strong>gecikmeleri ciddi \u015fekilde azaltt\u0131\u011f\u0131<\/strong> ifade ediliyor. Sonu\u00e7 olarak InferenceMAX verilerine g\u00f6re Nvidia\u2019n\u0131n Blackwell tabanl\u0131 AI sunucular\u0131, GPU ba\u015f\u0131na saniyede 75 token i\u015fleyerek benzer k\u00fcme yap\u0131land\u0131rmas\u0131ndaki AMD MI355X sistemlerini a\u00e7\u0131k ara geride b\u0131rak\u0131yor. <\/figure>\n<figure> <span> <img decoding=\"async\" src=\"https:\/\/ekamu.net\/wp-content\/uploads\/2026\/01\/nvidia-gb200-nvl72-amdye-gore-buyuk-performans-farki-sagliyor-2-Y9Kn9R6R.jpg\"\/> <\/span> Yaln\u0131zca performans de\u011fil, toplam sahip olma maliyeti (TCO) taraf\u0131nda da Nvidia\u2019n\u0131n belirgin bir avantaj\u0131 bulunuyor. Signal65, Oracle Cloud fiyatland\u0131rmalar\u0131n\u0131 referans alarak yapt\u0131\u011f\u0131 hesaplamada, GB200 NVL72 raflar\u0131n\u0131n token ba\u015f\u0131na g\u00f6reli maliyetinin 15\u2019te 1 seviyesine kadar d\u00fc\u015ft\u00fc\u011f\u00fcn\u00fc belirtiyor. Bu tablo, Nvidia\u2019n\u0131n donan\u0131m y\u0131\u011f\u0131n\u0131n\u0131n neden bulut sa\u011flay\u0131c\u0131lar\u0131 ve b\u00fcy\u00fck \u00f6l\u00e7ekli AI geli\u015ftiricileri taraf\u0131ndan bu kadar yayg\u0131n tercih edildi\u011fini net bi\u00e7imde ortaya koyuyor. <\/figure>\n<p>Elbette bu veriler, AMD ile Nvidia aras\u0131ndaki rekabetin tamam\u0131n\u0131 temsil etmiyor. AMD\u2019nin MI355X Instinct \u00e7\u00f6z\u00fcmleri, \u00f6zellikle y\u00fcksek HBM3e bellek kapasitesi sayesinde yo\u011fun ve s\u0131k\u0131\u015ft\u0131r\u0131lm\u0131\u015f ortamlarda agresif bir alternatif olmaya devam ediyor. Ancak mevcut nesilde, MoE i\u015f y\u00fckleri \u00f6zelinde \u00fcst\u00fcnl\u00fc\u011f\u00fcn Nvidia taraf\u0131nda oldu\u011fu g\u00f6r\u00fcl\u00fcyor. <strong>\u00d6n\u00fcm\u00fczdeki d\u00f6nemde<\/strong> <strong>Helios ve Vera Rubin<\/strong> gibi yeni raf \u00f6l\u00e7ekli \u00e7\u00f6z\u00fcmlerle rekabetin daha da k\u0131z\u0131\u015fmas\u0131 bekleniyor.<\/p>\n\n<p><span style=\"display: block; width: 343.125px; color: rgb(55, 58, 60); font-size: 14px; background-color: rgb(255, 249, 236);\"><\/span><\/p>\n<p>Kaynak :\u00a0<span style=\"background-color: rgb(255, 249, 236); color: rgb(55, 58, 60); font-size: 14px;\">https:\/\/www.donanimhaber.com\/nvidia-gb200-nvl72-amd-ye-gore-buyuk-performans-farki-sagliyor&#8211;200403<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Yapay zeka d\u00fcnyas\u0131nda Mixture of Experts (MoE) mimarisine ge\u00e7i\u015f h\u0131z kazan\u0131rken bu alandaki donan\u0131m rekabeti de giderek sertle\u015fiyor. Signal65 taraf\u0131ndan yay\u0131mlanan ve SemiAnalysis\u2019in InferenceMAX \u00f6l\u00e7\u00fcmlerine dayanan yeni bir analiz, Nvidia\u2019n\u0131n &#8230;<\/p>\n","protected":false},"author":1,"featured_media":116413,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[8],"tags":[6959,189],"class_list":["post-116412","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-teknoloji","tag-moe","tag-performans"],"_links":{"self":[{"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/posts\/116412","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/comments?post=116412"}],"version-history":[{"count":1,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/posts\/116412\/revisions"}],"predecessor-version":[{"id":116417,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/posts\/116412\/revisions\/116417"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/media\/116413"}],"wp:attachment":[{"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/media?parent=116412"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/categories?post=116412"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/tags?post=116412"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}