{"id":39067,"date":"2026-07-22T20:02:47","date_gmt":"2026-07-22T18:02:47","guid":{"rendered":"https:\/\/www.chinasmartbuy.com\/blog\/nvidia-rubin-gpu-336-miliardi-transistor-hbm4-288gb\/"},"modified":"2026-07-22T20:02:48","modified_gmt":"2026-07-22T18:02:48","slug":"nvidia-rubin-gpu-336-miliardi-transistor-hbm4-288gb","status":"publish","type":"post","link":"https:\/\/www.chinasmartbuy.com\/blog\/nvidia-rubin-gpu-336-miliardi-transistor-hbm4-288gb\/","title":{"rendered":"NVIDIA Rubin GPU: 336 miliardi di transistor e AI fino a 10 volte pi\u00f9 efficiente di Blackwell"},"content":{"rendered":"\n<link href=\"https:\/\/fonts.googleapis.com\/css2?family=Bebas+Neue&amp;family=DM+Sans:ital,wght@0,300;0,400;0,500;0,600;0,700;1,400&amp;display=swap\" rel=\"stylesheet\">\n<style>\n  :root {\n    --red: #CC1B1B;\n    --red-light: rgba(204,27,27,0.08);\n    --red-mid: #e84040;\n    --accent-soft-bg: rgba(204,27,27,0.07);\n    --accent-soft-border: rgba(204,27,27,0.18);\n    --text: #1a1a1a;\n    --text-muted: #666;\n    --card: #ffffff;\n    --border: #ebebeb;\n    --page-bg: #ffffff;\n    --surface-soft: #fafafa;\n    --surface-contrast: #f0f0f0;\n    --line-soft: #f5f5f5;\n    --soft-label: #bbb;\n    --muted-label: #999;\n    --copy: #333;\n    --font-head: 'Bebas Neue', sans-serif;\n    --font-body: 'DM Sans', sans-serif;\n    --heading-spacing: 0.04em;\n    --heading-weight: 400;\n    --spec-header-spacing: 0.08em;\n    --quickfacts-shadow: 0 10px 24px rgba(15,23,42,0.06);\n  }\n  .fbp5-wrap,.fbp5-wrap * { box-sizing:border-box; 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}\n    .rh-downloadbox-link { width:100%; }\n    .rh-offerbox-head { flex-direction:column; }\n    .rh-offerbox-links { grid-template-columns:1fr; }\n    .rh-offer-inline-wrap { flex-direction:column; align-items:flex-start; }\n    .rh-offer-inline-cta { width:100%; }\n  }\n\n  \/* RH_FBP5_CARDS_CSS_V1 *\/\n  .fbp5-related-grid { display:grid; grid-template-columns:repeat(3,1fr); gap:14px; }\n  .fbp5-telegram-grid { grid-template-columns:repeat(2,1fr); }\n  .fbp5-related-card { display:block; overflow:hidden; border:1px solid var(--border,#ebebeb); border-radius:8px; background:var(--card,#fff); color:inherit !important; text-decoration:none !important; transition:transform .18s ease, box-shadow .18s ease, border-color .18s ease; }\n  .fbp5-related-card:hover { transform:translateY(-2px); border-color:rgba(204,27,27,.35); box-shadow:0 16px 36px rgba(18,18,18,.10); }\n  .fbp5-related-card img { display:block; width:100%; aspect-ratio:16\/9; object-fit:cover; background:var(--surface-soft,#fafafa); }\n  .fbp5-related-thumb-placeholder { width:100%; aspect-ratio:16\/9; display:flex; align-items:center; justify-content:center; background:linear-gradient(135deg,rgba(204,27,27,.10),rgba(204,27,27,.03)); color:var(--red,#CC1B1B); font-family:var(--font-head,'Bebas Neue',sans-serif); font-size:28px; letter-spacing:.04em; }\n  .fbp5-related-body { padding:12px; }\n  .fbp5-related-body span { display:block; margin:0 0 6px; color:var(--red,#CC1B1B); font-size:11px; font-weight:900; letter-spacing:.08em; text-transform:uppercase; }\n  .fbp5-related-body strong { display:block; font-size:15px; line-height:1.25; color:var(--text,#1a1a1a); }\n  .fbp5-related-body small { display:block; margin:7px 0 0; color:var(--text-muted,#666); font-size:13px; line-height:1.35; }\n  @media(max-width:720px) {\n    .fbp5-telegram-grid { grid-template-columns:1fr; }\n    .fbp5-related-grid:not(.fbp5-telegram-grid) { grid-template-columns:1fr; }\n    .fbp5-related-grid:not(.fbp5-telegram-grid) .fbp5-related-card { display:grid; grid-template-columns:112px minmax(0,1fr); align-items:stretch; }\n    .fbp5-related-grid:not(.fbp5-telegram-grid) .fbp5-related-card img,\n    .fbp5-related-grid:not(.fbp5-telegram-grid) .fbp5-related-thumb-placeholder { height:100%; min-height:92px; aspect-ratio:auto; }\n  }\n<\/style>\n<div class=\"fbp5-wrap rh-json-article\" id=\"rh-article-mrwe3teo-ncj9a\" data-rh-article-type=\"news\" data-rh-site-profile=\"china-smart-buy\">\n  <div class=\"fbp5-intro\">\n    \n    <p>NVIDIA ha svelato nuovi dettagli sull\u2019architettura <strong>Rubin GPU<\/strong>, la piattaforma che raccoglier\u00e0 il testimone di Blackwell nel segmento AI ad alte prestazioni. Il dato che colpisce subito \u00e8 la scala del progetto: processo produttivo TSMC a 3 nm.<\/p><p>Rubin punta chiaramente ai carichi di lavoro pi\u00f9 pesanti per data center e supercalcolo, con un pacchetto tecnico costruito attorno a interconnessioni pi\u00f9 rapide, memoria HBM4 e una revisione profonda dei Tensor Core.<\/p>\n  <\/div><div class=\"rh-inline-gallery rh-inline-gallery-cols-4\" style=\"display:grid;grid-template-columns:repeat(4,minmax(0,1fr));gap:14px;margin:18px 0;position:relative;z-index:1\"><figure class=\"wp-block-image size-large\" style=\"margin:0;position:relative;z-index:1\"><a href=\"https:\/\/www.chinasmartbuy.com\/blog\/wp-content\/uploads\/2026\/07\/nvidia-rubin-gpu-7eaa1ce8-8f33-4eaa-8502-d376-1ckto411o3.webp\" target=\"_blank\" rel=\"noopener\" style=\"display:block;width:100%;height:100%;position:relative;z-index:2;pointer-events:auto;cursor:zoom-in\"><img decoding=\"async\" src=\"https:\/\/www.chinasmartbuy.com\/blog\/wp-content\/uploads\/2026\/07\/nvidia-rubin-gpu-7eaa1ce8-8f33-4eaa-8502-d376-1ckto411o3.webp\" alt=\"\u82f1\u4f1f\u8fbe\u516c\u5f00 Rubin GPU \u7ec6\u8282\uff1a3360 \u4ebf\u6676\u4f53\u7ba1\uff0c\u667a\u80fd\u4f53 AI \u6027\u80fd\u8f83 Blackwell \u63d0\u5347 10 \u500d\" loading=\"lazy\" style=\"display:block;width:100%;height:auto;pointer-events:auto\"><\/a><\/figure><figure class=\"wp-block-image size-large\" style=\"margin:0;position:relative;z-index:1\"><a href=\"https:\/\/www.chinasmartbuy.com\/blog\/wp-content\/uploads\/2026\/07\/nvidia-rubin-gpu-b28f6d99-bf3d-4617-8e94-0223-8k1k0m93y5.webp\" target=\"_blank\" rel=\"noopener\" style=\"display:block;width:100%;height:100%;position:relative;z-index:2;pointer-events:auto;cursor:zoom-in\"><img decoding=\"async\" src=\"https:\/\/www.chinasmartbuy.com\/blog\/wp-content\/uploads\/2026\/07\/nvidia-rubin-gpu-b28f6d99-bf3d-4617-8e94-0223-8k1k0m93y5.webp\" alt=\"\u82f1\u4f1f\u8fbe\u516c\u5f00 Rubin GPU \u7ec6\u8282\uff1a3360 \u4ebf\u6676\u4f53\u7ba1\uff0c\u667a\u80fd\u4f53 AI \u6027\u80fd\u8f83 Blackwell \u63d0\u5347 10 \u500d\" loading=\"lazy\" style=\"display:block;width:100%;height:auto;pointer-events:auto\"><\/a><\/figure><figure class=\"wp-block-image size-large\" style=\"margin:0;position:relative;z-index:1\"><a href=\"https:\/\/www.chinasmartbuy.com\/blog\/wp-content\/uploads\/2026\/07\/nvidia-rubin-gpu-48e2ab0d-dce1-447d-bc7b-6f9a-1ptzn0v1ua.webp\" target=\"_blank\" rel=\"noopener\" style=\"display:block;width:100%;height:100%;position:relative;z-index:2;pointer-events:auto;cursor:zoom-in\"><img decoding=\"async\" src=\"https:\/\/www.chinasmartbuy.com\/blog\/wp-content\/uploads\/2026\/07\/nvidia-rubin-gpu-48e2ab0d-dce1-447d-bc7b-6f9a-1ptzn0v1ua.webp\" alt=\"\u82f1\u4f1f\u8fbe\u516c\u5f00 Rubin GPU \u7ec6\u8282\uff1a3360 \u4ebf\u6676\u4f53\u7ba1\uff0c\u667a\u80fd\u4f53 AI \u6027\u80fd\u8f83 Blackwell \u63d0\u5347 10 \u500d\" loading=\"lazy\" style=\"display:block;width:100%;height:auto;pointer-events:auto\"><\/a><\/figure><figure class=\"wp-block-image size-large\" style=\"margin:0;position:relative;z-index:1\"><a href=\"https:\/\/www.chinasmartbuy.com\/blog\/wp-content\/uploads\/2026\/07\/nvidia-rubin-gpu-a2fcc1f3-d548-41e5-b6c3-cc88-ujylc11cqh.webp\" target=\"_blank\" rel=\"noopener\" style=\"display:block;width:100%;height:100%;position:relative;z-index:2;pointer-events:auto;cursor:zoom-in\"><img decoding=\"async\" src=\"https:\/\/www.chinasmartbuy.com\/blog\/wp-content\/uploads\/2026\/07\/nvidia-rubin-gpu-a2fcc1f3-d548-41e5-b6c3-cc88-ujylc11cqh.webp\" alt=\"\u82f1\u4f1f\u8fbe\u516c\u5f00 Rubin GPU \u7ec6\u8282\uff1a3360 \u4ebf\u6676\u4f53\u7ba1\uff0c\u667a\u80fd\u4f53 AI \u6027\u80fd\u8f83 Blackwell \u63d0\u5347 10 \u500d\" loading=\"lazy\" style=\"display:block;width:100%;height:auto;pointer-events:auto\"><\/a><\/figure><\/div>\n  \n\n      <section class=\"fbp5-section\">\n        <div class=\"fbp5-section-label\">Architettura<\/div>\n        <h2>Rubin GPU alza nettamente l\u2019asticella su densit\u00e0 e <span>complessit\u00e0 del chip<\/span><\/h2>\n        <p>Rubin viene prodotta con nodo <strong>TSMC N3P a 3 nm<\/strong> e adotta una configurazione a due die di dimensioni massime da reticolo, collegati tramite interfaccia NV-HBI in un unico package. NVIDIA indica un totale di 336 miliardi di transistor, pari a un incremento del 62% rispetto al chip Blackwell GB300, un dato che rende bene la crescita della piattaforma sia in termini di densit\u00e0 sia di ambizione progettuale.<\/p><p>All\u2019interno di ogni GPU trovano posto 8 GPC, per un totale di 224 SM e 896 Tensor Core. Lo schema prevede due tipi di GPC, uno con 30 SM e uno con 26 SM. Ogni die integra inoltre 4 GPC, due grandi blocchi di cache L2 decentralizzata, un Gigathread Engine, quattro canali HBM e un\u2019interfaccia NVLink dedicata.<\/p>\n        <ul class=\"fbp5-bullet-list\"><li>Processo produttivo <strong>TSMC N3P a 3 nm<\/strong>.<\/li><li>Package con <strong>2 die<\/strong> collegati da NV-HBI.<\/li><li>Totale di 8 GPC, 224 SM e 896 Tensor Core.<\/li><li>Crescita del 62% nei transistor rispetto a Blackwell GB300.<\/li><\/ul>\n        <div class=\"rh-quickfacts-grid\">\n      <div class=\"rh-quickfacts-card\">\n        <div class=\"rh-quickfacts-label\">Canali memoria per die<\/div>\n        <div class=\"rh-quickfacts-value\">4 canali HBM<\/div>\n      <\/div>\n    \n      <div class=\"rh-quickfacts-card\">\n        <div class=\"rh-quickfacts-label\">Cache<\/div>\n        <div class=\"rh-quickfacts-value\">Doppio blocco L2 decentralizzato per die<\/div>\n      <\/div>\n    <\/div>\n        <div class=\"fbp5-highlight\">Il passaggio a 336 miliardi di transistor mette Rubin in una categoria ancora pi\u00f9 estrema rispetto a Blackwell, con un focus evidente sulla massima scala per AI da data center.<\/div>\n        <div class=\"fbp5-info\">La struttura a due die e l\u2019uso di interconnessioni ad alta banda indicano un progetto ottimizzato per acceleratori di fascia top, non per applicazioni consumer.<\/div>\n        \n      <div class=\"fbp5-scheda\">\n        <div class=\"fbp5-scheda-header\">Dati architetturali principali<\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">Processo<\/div>\n            <div class=\"fbp5-scheda-val\">TSMC N3P a 3 nm<\/div>\n          <\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">Transistor<\/div>\n            <div class=\"fbp5-scheda-val\">336 miliardi<\/div>\n          <\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">Numero di die<\/div>\n            <div class=\"fbp5-scheda-val\">2<\/div>\n          <\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">GPC totali<\/div>\n            <div class=\"fbp5-scheda-val\">8<\/div>\n          <\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">SM totali<\/div>\n            <div class=\"fbp5-scheda-val\">224<\/div>\n          <\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">Tensor Core<\/div>\n            <div class=\"fbp5-scheda-val\">896<\/div>\n          <\/div>\n        \n      <\/div>\n    \n      <\/section>\n    \n\n      <section class=\"fbp5-section\">\n        <div class=\"fbp5-section-label\">Prestazioni<\/div>\n        <h2>Le interconnessioni e la memoria HBM4 sono il vero perno del <span>salto generazionale<\/span><\/h2>\n        <p>Sul fronte delle comunicazioni, Rubin porta in dote NVLink 6 con <strong>3,600 GB\/s<\/strong> di banda tra GPU, mentre l\u2019interfaccia NVLink-C2C arriva a 1,800 GB\/s per il collegamento tra CPU e GPU. Per la connessione host \u00e8 previsto anche PCIe Gen6 x16 con 256 GB\/s. \u00c8 una dotazione che punta a ridurre i colli di bottiglia nei cluster AI pi\u00f9 grandi, dove la velocit\u00e0 di scambio dati conta quasi quanto la potenza di calcolo pura.<\/p><p>La memoria \u00e8 uno degli aggiornamenti pi\u00f9 importanti: Rubin usa 8 stack HBM4 12-Hi per una capacit\u00e0 totale di <strong>288 GB<\/strong> e una banda di picco di 22 TB\/s. Rispetto agli 8 TB\/s di Blackwell, il miglioramento \u00e8 pari a 1,8 volte. NVIDIA attribuisce il salto nell\u2019agentic AI soprattutto a tre elementi: Tensor Core evoluti con supporto a precisioni estese, nuovo sottosistema HBM4 e terza generazione del Transformer Engine.<\/p>\n        <ul class=\"fbp5-bullet-list\"><li>NVLink 6 fino a <strong>3,600 GB\/s<\/strong> tra GPU.<\/li><li>NVLink-C2C fino a <strong>1,800 GB<\/strong>\/s tra CPU e GPU.<\/li><li>PCIe Gen6 x16 con banda host pari a <strong>256 GB<\/strong>\/s.<\/li><li>Memoria HBM4 da 288 GB con banda di picco di <strong>22 TB\/s<\/strong>.<\/li><li>Prestazioni per watt nell\u2019agentic AI fino a 10 volte superiori a Blackwell.<\/li><\/ul>\n        <div class=\"rh-quickfacts-grid\">\n      <div class=\"rh-quickfacts-card\">\n        <div class=\"rh-quickfacts-label\">Stack HBM4<\/div>\n        <div class=\"rh-quickfacts-value\">8 stack da 36 GB ciascuno<\/div>\n      <\/div>\n    \n      <div class=\"rh-quickfacts-card\">\n        <div class=\"rh-quickfacts-label\">Altezza stack<\/div>\n        <div class=\"rh-quickfacts-value\">12-Hi<\/div>\n      <\/div>\n    \n      <div class=\"rh-quickfacts-card\">\n        <div class=\"rh-quickfacts-label\">Banda Blackwell di riferimento<\/div>\n        <div class=\"rh-quickfacts-value\">8 TB\/s<\/div>\n      <\/div>\n    <\/div>\n        <div class=\"fbp5-highlight\">Il mix tra HBM4, NVLink 6 e nuovi Tensor Core spiega perch\u00e9 Rubin venga presentata come una piattaforma molto pi\u00f9 adatta ai modelli con contesti ampi, alta concorrenza e generazione token intensiva.<\/div>\n        <div class=\"fbp5-info\">Il guadagno dichiarato di 10 volte nell\u2019agentic AI riguarda il throughput per unit\u00e0 di energia rispetto a Blackwell, quindi l\u2019enfasi \u00e8 sull\u2019efficienza operativa oltre che sulla velocit\u00e0 assoluta.<\/div>\n        \n      <div class=\"fbp5-scheda\">\n        <div class=\"fbp5-scheda-header\">Connettivit\u00e0 e memoria<\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">NVLink 6<\/div>\n            <div class=\"fbp5-scheda-val\">3,600 GB\/s<\/div>\n          <\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">NVLink-C2C<\/div>\n            <div class=\"fbp5-scheda-val\">1,800 GB\/s<\/div>\n          <\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">PCIe<\/div>\n            <div class=\"fbp5-scheda-val\">Gen6 x16,256 GB\/s<\/div>\n          <\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">Memoria<\/div>\n            <div class=\"fbp5-scheda-val\">HBM4<\/div>\n          <\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">Capacit\u00e0 totale<\/div>\n            <div class=\"fbp5-scheda-val\">288 GB<\/div>\n          <\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">Banda memoria<\/div>\n            <div class=\"fbp5-scheda-val\">22 TB\/s<\/div>\n          <\/div>\n        \n      <\/div>\n    \n      <\/section>\n    \n\n      <section class=\"fbp5-section\">\n        <div class=\"fbp5-section-label\">Scenario<\/div>\n        <h2>Rubin conferma la direzione di NVIDIA verso cluster AI sempre pi\u00f9 <span>grandi e costosi<\/span><\/h2>\n        <p>Anche senza dettagli su prezzo e disponibilit\u00e0 commerciale della singola GPU, Rubin mostra con chiarezza la traiettoria della gamma NVIDIA per il data center: pi\u00f9 transistor, pi\u00f9 banda, pi\u00f9 memoria e una forte ottimizzazione per inferenza avanzata e agenti AI.<\/p><p>Per ora i dati diffusi servono soprattutto a inquadrare il livello tecnico della piattaforma. Il valore reale di Rubin si misurer\u00e0 quando arriveranno configurazioni complete, benchmark indipendenti e dettagli sui sistemi che la adotteranno, ma gi\u00e0 oggi le specifiche raccontano un salto molto marcato rispetto a Blackwell.<\/p>\n        <ul class=\"fbp5-bullet-list\"><li>Nessun prezzo ufficiale comunicato per la GPU nel dettaglio disponibile.<\/li><li>Nessuna data precisa di commercializzazione indicata nei dati pubblicati.<\/li><li>Focus evidente su AI da data center, cluster e carichi di lavoro ad altissima intensit\u00e0.<\/li><\/ul>\n        <div class=\"rh-quickfacts-grid\">\n      <div class=\"rh-quickfacts-card\">\n        <div class=\"rh-quickfacts-label\">Segmento<\/div>\n        <div class=\"rh-quickfacts-value\">Acceleratori AI per data center<\/div>\n      <\/div>\n    \n      <div class=\"rh-quickfacts-card\">\n        <div class=\"rh-quickfacts-label\">Obiettivo tecnico<\/div>\n        <div class=\"rh-quickfacts-value\">Pi\u00f9 efficienza e pi\u00f9 banda nei carichi AI complessi<\/div>\n      <\/div>\n    <\/div>\n        <div class=\"fbp5-highlight\">Rubin non \u00e8 ancora una proposta da valutare sul prezzo, ma una piattaforma da osservare perch\u00e9 anticipa il prossimo standard NVIDIA nel calcolo AI di fascia altissima.<\/div>\n        <div class=\"fbp5-info\">Le specifiche diffuse sono gi\u00e0 sufficienti per capire che il collo di bottiglia non sar\u00e0 soltanto la potenza di calcolo, ma anche il costo e la complessit\u00e0 dell\u2019infrastruttura necessaria per sfruttarla.<\/div>\n        \n      <div class=\"fbp5-scheda\">\n        <div class=\"fbp5-scheda-header\">Stato attuale delle informazioni<\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">Posizionamento<\/div>\n            <div class=\"fbp5-scheda-val\">Fascia top per infrastrutture AI<\/div>\n          <\/div>\n        \n      <\/div>\n    \n      <\/section>\n    \n<section class=\"fbp5-section\" 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16px;border-radius:16px;background:linear-gradient(135deg,#fff7ed,#ffedd5);color:#c2410c;text-decoration:none;font-size:11px;font-weight:900;letter-spacing:.08em;text-transform:uppercase;border:1px solid rgba(249,115,22,.20);box-shadow:0 8px 22px rgba(249,115,22,.08)\">Via<\/a><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"<p>NVIDIA ha svelato Rubin GPU: 3 nm, 336 miliardi di transistor, HBM4 da 288 GB e un forte salto nell\u2019efficienza AI rispetto a Blackwell.<\/p>\n","protected":false},"author":10,"featured_media":39066,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_exactmetrics_skip_tracking":false,"_yoast_wpseo_focuskw_text_input":"NVIDIA Rubin GPU","footnotes":""},"categories":[480],"tags":[933,1084],"class_list":["post-39067","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","tag-ai","tag-notebook"],"blocksy_meta":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>NVIDIA Rubin GPU: 336 miliardi di transistor e AI fino a 10 volte pi\u00f9 efficiente di Blackwell<\/title>\n<meta name=\"description\" content=\"NVIDIA pubblica i dettagli di Rubin GPU: 3 nm, 336 miliardi di transistor, HBM4 da 288 GB e fino a 10 volte pi\u00f9 efficienza nell\u2019agentic AI rispetto a Blackwell.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.chinasmartbuy.com\/blog\/nvidia-rubin-gpu-336-miliardi-transistor-hbm4-288gb\/\" \/>\n<meta property=\"og:locale\" content=\"it_IT\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"NVIDIA Rubin GPU: 336 miliardi di transistor e AI fino a 10 volte pi\u00f9 efficiente di Blackwell\" \/>\n<meta property=\"og:description\" content=\"NVIDIA pubblica i dettagli di Rubin 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