{"id":38936,"date":"2026-07-22T08:25:22","date_gmt":"2026-07-22T06:25:22","guid":{"rendered":"https:\/\/www.chinasmartbuy.com\/blog\/nvidia-blackwell-gb300-record-pretraining-moe-1648-tflops\/"},"modified":"2026-07-22T08:25:24","modified_gmt":"2026-07-22T06:25:24","slug":"nvidia-blackwell-gb300-record-pretraining-moe-1648-tflops","status":"publish","type":"post","link":"https:\/\/www.chinasmartbuy.com\/blog\/nvidia-blackwell-gb300-record-pretraining-moe-1648-tflops\/","title":{"rendered":"Nvidia Blackwell GB300 segna un record nel pretraining MoE con 1648 TFLOPs per GPU"},"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  .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-mrvp6wqv-29yhp\" data-rh-article-type=\"news\" data-rh-site-profile=\"china-smart-buy\">\n  <div class=\"fbp5-intro\">\n    \n    <p>Nvidia ha annunciato un nuovo risultato per la piattaforma <strong>Blackwell GB300<\/strong>, che ha stabilito un record nel pretraining di modelli MoE raggiungendo <strong>1648 TFLOPs per GPU<\/strong>. Il test \u00e8 stato eseguito con il modello <strong>DeepSeek-v3 671B<\/strong> su un sistema GB300 NVL72 con 256 GPU.<\/p><p>Il dato \u00e8 interessante perch\u00e9 misura la capacit\u00e0 della nuova generazione Blackwell in uno scenario concreto di addestramento AI su larga scala. A parit\u00e0 di carico di training, GB300 NVL72 ha ottenuto le stesse prestazioni usando meno hardware rispetto ad altre configurazioni, segnalando un salto netto sul fronte dell&#8217;efficienza.<\/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-blackwell-gb300-segna-un-record-nel-pretraining-moe-con-1648-tflo-af6d3e2e-f712-42a8-b024.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-blackwell-gb300-segna-un-record-nel-pretraining-moe-con-1648-tflo-af6d3e2e-f712-42a8-b024.webp\" alt=\"DeepSeek-v3 671B \u6d4b\u8bd5\uff1a\u82f1\u4f1f\u8fbe Blackwell GB300 \u5237\u65b0 MoE \u9884\u8bad\u7ec3\u4e16\u754c\u7eaa\u5f55\uff0c\u6bcf GPU \u7b97\u529b 1648 TFLOPs\" 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-blackwell-gb300-segna-un-record-nel-pretraining-moe-con-1648-tflo-a9a106cf-9489-4e45-ae42.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-blackwell-gb300-segna-un-record-nel-pretraining-moe-con-1648-tflo-a9a106cf-9489-4e45-ae42.webp\" alt=\"DeepSeek-v3 671B \u6d4b\u8bd5\uff1a\u82f1\u4f1f\u8fbe Blackwell GB300 \u5237\u65b0 MoE \u9884\u8bad\u7ec3\u4e16\u754c\u7eaa\u5f55\uff0c\u6bcf GPU \u7b97\u529b 1648 TFLOPs\" 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-blackwell-gb300-segna-un-record-nel-pretraining-moe-con-1648-tflo-c0a05d42-9c9f-4739-bf75.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-blackwell-gb300-segna-un-record-nel-pretraining-moe-con-1648-tflo-c0a05d42-9c9f-4739-bf75.webp\" alt=\"DeepSeek-v3 671B \u6d4b\u8bd5\uff1a\u82f1\u4f1f\u8fbe Blackwell GB300 \u5237\u65b0 MoE \u9884\u8bad\u7ec3\u4e16\u754c\u7eaa\u5f55\uff0c\u6bcf GPU \u7b97\u529b 1648 TFLOPs\" 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-blackwell-gb300-segna-un-record-nel-pretraining-moe-con-1648-tflo-7ff8e34a-fcd3-4b7b-ae41.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-blackwell-gb300-segna-un-record-nel-pretraining-moe-con-1648-tflo-7ff8e34a-fcd3-4b7b-ae41.webp\" alt=\"DeepSeek-v3 671B \u6d4b\u8bd5\uff1a\u82f1\u4f1f\u8fbe Blackwell GB300 \u5237\u65b0 MoE \u9884\u8bad\u7ec3\u4e16\u754c\u7eaa\u5f55\uff0c\u6bcf GPU \u7b97\u529b 1648 TFLOPs\" 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\">Prestazioni<\/div>\n        <h2>Blackwell GB300 alza il livello nel pretraining dei <span>modelli MoE<\/span><\/h2>\n        <p>MoE, ci\u00f2\u00e8 Mixture of Experts o modello a miscela di esperti, \u00e8 un&#8217;architettura che suddivide un grande modello in pi\u00f9 sottoreti specializzate. Durante training e inferenza viene attivata solo una parte di questi esperti, cos\u00ec da aumentare la capacit\u00e0 complessiva del modello contenendo il costo computazionale. \u00c8 una struttura sempre pi\u00f9 usata nei grandi modelli linguistici proprio per migliorare l&#8217;efficienza.<\/p><p>Nel test condotto da Nvidia, il sistema <strong>GB300 NVL72<\/strong> ha pre-addestrato il modello <strong>DeepSeek-v3 671B<\/strong> con 256 GPU, arrivando a una throughput per singola GPU di 1648 TFLOPs. In pratica, Blackwell GB300 non punta solo alla potenza grezza, ma a tradurre questa potenza in prestazioni reali su workload AI complessi e molto pesanti.<\/p>\n        <ul class=\"fbp5-bullet-list\"><li>Record di <strong>1648 TFLOPs per GPU<\/strong> nel pretraining MoE.<\/li><li>Test eseguito sul modello <strong>DeepSeek-v3 671B<\/strong>.<\/li><li>Configurazione impiegata: sistema <strong>GB300 NVL72<\/strong> con 256 GPU.<\/li><li>A parit\u00e0 di attivit\u00e0 di training, il sistema ha raggiunto lo stesso risultato con meno hardware.<\/li><\/ul>\n        <div class=\"rh-quickfacts-grid\">\n      <div class=\"rh-quickfacts-card\">\n        <div class=\"rh-quickfacts-label\">Architettura testata<\/div>\n        <div class=\"rh-quickfacts-value\">Blackwell GB300<\/div>\n      <\/div>\n    \n      <div class=\"rh-quickfacts-card\">\n        <div class=\"rh-quickfacts-label\">Tipologia di workload<\/div>\n        <div class=\"rh-quickfacts-value\">Pretraining di modello MoE<\/div>\n      <\/div>\n    <\/div>\n        <div class=\"fbp5-highlight\">Il passaggio a 1648 TFLOPs per GPU colloca GB300 tra le piattaforme pi\u00f9 aggressive per il training AI su larga scala.<\/div>\n        <div class=\"fbp5-info\">Il pretraining \u00e8 la fase in cui un modello apprende pattern generali da grandi quantit\u00e0 di dati non etichettati tramite apprendimento auto-supervisionato.<\/div>\n        \n      <div class=\"fbp5-scheda\">\n        <div class=\"fbp5-scheda-header\">Dati chiave del test<\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">Piattaforma<\/div>\n            <div class=\"fbp5-scheda-val\">Nvidia GB300 NVL72<\/div>\n          <\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">Numero di GPU<\/div>\n            <div class=\"fbp5-scheda-val\">256<\/div>\n          <\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">Modello utilizzato<\/div>\n            <div class=\"fbp5-scheda-val\">DeepSeek-v3 671B<\/div>\n          <\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">Prestazioni per GPU<\/div>\n            <div class=\"fbp5-scheda-val\">1648 TFLOPs<\/div>\n          <\/div>\n        \n      <\/div>\n    \n      <\/section>\n    \n\n      <section class=\"fbp5-section\">\n        <div class=\"fbp5-section-label\">Confronto<\/div>\n        <h2>Il salto rispetto a GB200 e ai test precedenti \u00e8 <span>molto netto<\/span><\/h2>\n        <p>Nvidia indica che negli ultimi sei mesi ha simulato oltre 250.000 configurazioni differenti per affinare Blackwell, individuando <strong>38 ottimizzazioni rilevanti<\/strong> e accumulando <strong>1,4 milioni di ore di test GPU<\/strong>. Questo lavoro di ottimizzazione aiuta a spiegare perch\u00e9 il guadagno non dipenda solo dall&#8217;hardware, ma anche dalla messa a punto dell&#8217;intera piattaforma.<\/p><p>Rispetto a un test di pretraining precedente fermo a <strong>1088 TFLOPs<\/strong>, il sistema GB300 NVL72 mostra un miglioramento del <strong>50%<\/strong>. Il confronto con la generazione precedente \u00e8 ancora pi\u00f9 evidente: contro i <strong>606 TFLOPs per GPU<\/strong> registrati da GB200, GB300 arriva a circa <strong>tre volte<\/strong> le prestazioni.<\/p>\n        <ul class=\"fbp5-bullet-list\"><li>Oltre <strong>250.000 configurazioni<\/strong> simulate per l&#8217;ottimizzazione.<\/li><li>Individuate <strong>38 ottimizzazioni<\/strong> considerate di rilievo.<\/li><li>Completate <strong>1,4 milioni di ore<\/strong> di test GPU.<\/li><li>Incremento del <strong>50%<\/strong> rispetto al test a 1088 TFLOPs.<\/li><li>Balzo di circa <strong>3 volte<\/strong> rispetto ai 606 TFLOPs per GPU di GB200.<\/li><\/ul>\n        <div class=\"rh-quickfacts-grid\">\n      <div class=\"rh-quickfacts-card\">\n        <div class=\"rh-quickfacts-label\">Generazione precedente<\/div>\n        <div class=\"rh-quickfacts-value\">GB200 a 606 TFLOPs per GPU<\/div>\n      <\/div>\n    \n      <div class=\"rh-quickfacts-card\">\n        <div class=\"rh-quickfacts-label\">Periodo di lavoro sulle ottimizzazioni<\/div>\n        <div class=\"rh-quickfacts-value\">Oltre 6 mesi<\/div>\n      <\/div>\n    <\/div>\n        <div class=\"fbp5-highlight\">Il punto centrale non \u00e8 solo il picco numerico, ma il fatto che GB300 riesca a mantenere prestazioni elevate nel pretraining di un modello da 671 miliardi di parametri.<\/div>\n        <div class=\"fbp5-info\">Per chi segue l&#8217;hardware AI, questo risultato rafforza il posizionamento di Blackwell come piattaforma di riferimento per training ad alta densit\u00e0 e workload MoE.<\/div>\n        \n      <div class=\"fbp5-scheda\">\n        <div class=\"fbp5-scheda-header\">Confronto prestazionale<\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">GB300 NVL72 attuale<\/div>\n            <div class=\"fbp5-scheda-val\">1648 TFLOPs per GPU<\/div>\n          <\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">Test precedente<\/div>\n            <div class=\"fbp5-scheda-val\">1088 TFLOPs per GPU<\/div>\n          <\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">Variazione sul test precedente<\/div>\n            <div class=\"fbp5-scheda-val\">+50%<\/div>\n          <\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">GB200<\/div>\n            <div class=\"fbp5-scheda-val\">606 TFLOPs per GPU<\/div>\n          <\/div>\n        \n          <div class=\"fbp5-scheda-row\">\n            <div class=\"fbp5-scheda-key\">Vantaggio su GB200<\/div>\n            <div class=\"fbp5-scheda-val\">Circa 3x<\/div>\n          <\/div>\n        \n      <\/div>\n    \n      <\/section>\n    \n<section class=\"fbp5-section\" data-rh-related-section=\"1\">\n      <div class=\"fbp5-section-label\">Articoli correlati<\/div>\n      <h2>Altre notizie <span>da leggere<\/span><\/h2>\n 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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>Blackwell GB300 firma un nuovo record nel pretraining MoE con DeepSeek-v3 671B, raggiungendo 1648 TFLOPs per GPU e migliorando nettamente rispetto a GB200.<\/p>\n","protected":false},"author":15,"featured_media":38935,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_exactmetrics_skip_tracking":false,"_yoast_wpseo_focuskw_text_input":"Nvidia Blackwell GB300 1648 TFLOPs per GPU","footnotes":""},"categories":[480],"tags":[933],"class_list":["post-38936","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","tag-ai"],"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 Blackwell GB300 segna un record nel pretraining MoE con 1648 TFLOPs per GPU<\/title>\n<meta name=\"description\" content=\"Nvidia annuncia un nuovo record per Blackwell GB300: 1648 TFLOPs per GPU nel pretraining MoE del modello DeepSeek-v3 671B, con un netto salto su GB200.\" \/>\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-blackwell-gb300-record-pretraining-moe-1648-tflops\/\" \/>\n<meta property=\"og:locale\" content=\"it_IT\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Nvidia Blackwell GB300 segna un record nel pretraining MoE con 1648 TFLOPs per GPU\" \/>\n<meta property=\"og:description\" content=\"Nvidia annuncia un nuovo record per Blackwell GB300: 1648 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