{"id":1218,"date":"2026-08-27T08:05:14","date_gmt":"2026-08-27T05:05:14","guid":{"rendered":"https:\/\/www.tayfnews.tech\/tr\/?p=1218"},"modified":"2026-08-27T08:05:14","modified_gmt":"2026-08-27T05:05:14","slug":"qwen3-8-flash-next-nvidia-gb300-nvl72-altyapisinda-test-edildi","status":"publish","type":"post","link":"https:\/\/www.tayfnews.tech\/tr\/technology\/qwen3-8-flash-next-nvidia-gb300-nvl72-altyapisinda-test-edildi\/","title":{"rendered":"Qwen3.8-Flash-Next, NVIDIA GB300 NVL72 Altyap\u0131s\u0131nda Test Edildi"},"content":{"rendered":"<p>Alibaba, yakla\u015fan <strong>Qwen4 mimarisi<\/strong> i\u00e7in geli\u015ftiricilere erken bir \u00f6nizleme ve de\u011ferlendirme arac\u0131 sunan <strong>Qwen3.8-Flash-Next<\/strong> model a\u011f\u0131rl\u0131klar\u0131n\u0131 resmi olarak yay\u0131nlad\u0131. Karma\u015f\u0131k hesaplama ve \u00fcretken i\u015f ak\u0131\u015flar\u0131n\u0131 ele almak \u00fczere tasarlanan bu \u00e7ok modlu model, \u00f6zellikle geli\u015fmi\u015f ajan tabanl\u0131 kodlama g\u00f6revleri i\u00e7in uyarlanm\u0131\u015f olan <strong>NVIDIA GB300 NVL72<\/strong> altyap\u0131s\u0131ndan yararlanan \u00fcst d\u00fczey donan\u0131m test konfig\u00fcrasyonlar\u0131yla birlikte geliyor.<\/p>\n<h2>Mimari At\u0131l\u0131mlar ve Uzmanlar Kar\u0131\u015f\u0131m\u0131 Tasar\u0131m\u0131<\/h2>\n<p>Yeni tan\u0131t\u0131lan \u00f6nizleme modeli, ham performans\u0131 y\u00fcr\u00fctme verimlili\u011fiyle dengelemek i\u00e7in tasarlanm\u0131\u015f geli\u015fmi\u015f bir <strong>\u00e7ok modlu uzmanlar kar\u0131\u015f\u0131m\u0131 (MoE)<\/strong> mimarisinden yararlan\u0131r. Toplam parametre \u00f6l\u00e7e\u011fini aktif token ba\u015f\u0131na hesaplamadan ay\u0131ran model, yasaklay\u0131c\u0131 gecikme cezalar\u0131 getirmeden zorlu ak\u0131l y\u00fcr\u00fctme d\u00f6ng\u00fclerini y\u00f6netir.<\/p>\n<ul>\n<li><strong>Ana Model \u00d6l\u00e7e\u011fi:<\/strong> Temel \u00e7ekirde\u011fi olu\u015fturan 125 milyar parametre.<\/li>\n<li><strong>N-gram G\u00f6mmeleri:<\/strong> Yap\u0131sal verimlili\u011fe adanm\u0131\u015f ek 51 milyar parametre.<\/li>\n<li><strong>Aktif Parametreler:<\/strong> \u00c7\u0131kar\u0131m s\u0131ras\u0131nda token ba\u015f\u0131na yaln\u0131zca 6 milyar parametre etkinle\u015ftirilir.<\/li>\n<li><strong>Yerel Ba\u011flam Penceresi:<\/strong> Devasa bir 262.144 token yerel ba\u011flam kapasitesi.<\/li>\n<li><strong>Geni\u015fletilmi\u015f Ba\u011flam:<\/strong> Uzun bi\u00e7imli depo analizi i\u00e7in 1.000.000 tokene kadar \u00f6l\u00e7eklenebilir.<\/li>\n<\/ul>\n<h2>NVIDIA GB300 NVL72 \u00dczerinde Ajan Tabanl\u0131 Kodlamaya G\u00fc\u00e7 Vermek<\/h2>\n<p>Yaz\u0131l\u0131m m\u00fchendisli\u011fi otomasyonu otonom ajan i\u015f ak\u0131\u015flar\u0131na do\u011fru kayarken, b\u00fcy\u00fck dil modelleri t\u00fcm kod tabanlar\u0131n\u0131, dok\u00fcmantasyon k\u00fct\u00fcphanelerini ve \u00e7al\u0131\u015fma zaman\u0131 geri bildirim d\u00f6ng\u00fclerini ayn\u0131 anda i\u015flemelidir. Qwen3.8-Flash-Next ile NVIDIA&#8217;n\u0131n son teknoloji GB300 NVL72 platformunun birle\u015fimi, bu \u00e7ok ad\u0131ml\u0131 ajan eylemlerini kesintisiz olarak s\u00fcrd\u00fcrmek i\u00e7in gereken y\u00fcksek bant geni\u015flikli belle\u011fi ve paralel i\u015fleme g\u00fcc\u00fcn\u00fc sa\u011flar.<\/p>\n<p>Qwen4 mimarisi \u00f6nizlemesinin yeteneklerini ke\u015ffetmek isteyen geli\u015ftiriciler ve ara\u015ft\u0131rmac\u0131lar, a\u011f\u0131r i\u015f y\u00fckleri alt\u0131nda kod \u00fcretimi, hata d\u00fczeltme ve otonom yaz\u0131l\u0131m navigasyonunu k\u0131yaslamak i\u00e7in model a\u011f\u0131rl\u0131klar\u0131na eri\u015febilir.<\/p>\n<p><em>Kaynak: <a href=\"https:\/\/developer.nvidia.com\/blog\/experiment-with-qwen3-8-flash-next-on-nvidia-gb300-nvl72-for-agentic-coding\/\" target=\"_blank\" rel=\"noopener noreferrer\">Orijinal Makale<\/a><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Alibaba&#8217;n\u0131n ajan tabanl\u0131 kodlama i\u00e7in geli\u015ftirdi\u011fi Qwen3.8-Flash-Next model \u00f6nizlemesini ve NVIDIA GB300 NVL72 donan\u0131m\u0131ndaki testlerini ke\u015ffedin.<\/p>\n","protected":false},"author":1,"featured_media":1217,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"googlesitekit_rrm_CAowrrDMDA:productID":"","tayfnews_source_url":"","footnotes":"","rank_math_focus_keyword":"Qwen3.8-Flash-Next, NVIDIA GB300 NVL72, Qwen4 mimarisi, Donan\u0131m, Yapay Zeka Modelleri, Teknoloji","rank_math_title":"Qwen3.8-Flash-Next, NVIDIA GB300 NVL72 Altyap\u0131s\u0131nda Test Edildi","rank_math_description":"Alibaba'n\u0131n ajan tabanl\u0131 kodlama i\u00e7in geli\u015ftirdi\u011fi Qwen3.8-Flash-Next model \u00f6nizlemesini ve NVIDIA GB300 NVL72 donan\u0131m\u0131ndaki testlerini ke\u015ffedin."},"categories":[2],"tags":[],"class_list":["post-1218","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology"],"_links":{"self":[{"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/posts\/1218","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/comments?post=1218"}],"version-history":[{"count":1,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/posts\/1218\/revisions"}],"predecessor-version":[{"id":1219,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/posts\/1218\/revisions\/1219"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/media\/1217"}],"wp:attachment":[{"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/media?parent=1218"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/categories?post=1218"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/tags?post=1218"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}