{"id":48084,"date":"2026-09-12T04:37:00","date_gmt":"2026-09-12T02:37:00","guid":{"rendered":"https:\/\/www.chinasmartbuy.com\/blog\/nvidia-dlss-5-nvfp4-rtx-50-test\/"},"modified":"2026-09-12T04:38:47","modified_gmt":"2026-09-12T02:38:47","slug":"nvidia-dlss-5-nvfp4-rtx-50-test","status":"publish","type":"post","link":"https:\/\/www.chinasmartbuy.com\/blog\/nvidia-dlss-5-nvfp4-rtx-50-test\/","title":{"rendered":"DLSS 5 con NVFP4 su RTX 50: i test mostrano guadagni minimi"},"content":{"rendered":"\n\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<\/style>\n<div class=\"fbp5-wrap rh-json-article\" id=\"rh-article-mtxryw2g-44vst\" data-rh-article-type=\"news\" data-rh-site-profile=\"china-smart-buy\">\n  <div class=\"fbp5-intro\">\n    \n    <p>I primi test della community su una versione modificata di <strong>DLSS 5<\/strong> con calcolo a precisione mista ridimensionano le aspettative: sulle GPU <strong>RTX 50<\/strong> il vantaggio misurato \u00e8 molto contenuto. L\u2019idea era sfruttare meglio le capacit\u00e0 native dei Tensor Core di Blackwell con il formato NVFP4, ma al momento i benefici restano marginali.<\/p><p>Il punto pi\u00f9 importante \u00e8 che il guadagno osservato non riguarda direttamente gli fps complessivi del gioco, bens\u00ec il solo tempo richiesto dalla fase di neural rendering di DLSS 5. \u00c8 una distinzione decisiva, perch\u00e9 evita di leggere quel miglioramento come un aumento lineare delle prestazioni in gioco.<\/p>\n  <\/div><div class=\"rh-inline-gallery rh-inline-gallery-cols-2\" style=\"display:grid;grid-template-columns:repeat(2,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\/09\/dlss-5-con-nvfp4-su-rtx-50-0d3e4957-027c-4d65-ad64-d1fa-1e2yszy1h0.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\/09\/dlss-5-con-nvfp4-su-rtx-50-0d3e4957-027c-4d65-ad64-d1fa-1e2yszy1h0.webp\" alt=\"\u82f1\u4f1f\u8fbe DLSS 5 \u6df7\u5408\u7cbe\u5ea6 Mod \u6d4b\u8bd5\uff1aRTX 50 \u7cfb\u5217\u663e\u5361\u6027\u80fd\u4ec5\u63d0\u5347 1% \u81f3 2%\" 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\/09\/dlss-5-con-nvfp4-su-rtx-50-2ce26f94-7c54-4798-a341-c535-u8x6n412zi.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\/09\/dlss-5-con-nvfp4-su-rtx-50-2ce26f94-7c54-4798-a341-c535-u8x6n412zi.webp\" alt=\"\u82f1\u4f1f\u8fbe DLSS 5 \u6df7\u5408\u7cbe\u5ea6 Mod \u6d4b\u8bd5\uff1aRTX 50 \u7cfb\u5217\u663e\u5361\u6027\u80fd\u4ec5\u63d0\u5347 1% \u81f3 2%\" 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\">Test<\/div>\n        <h2>La modifica a precisione mista riduce i tempi del neural rendering solo in <span>modo limitato<\/span><\/h2>\n        <p>Dopo la circolazione del file DLL legato al neural rendering di DLSS 5, diversi sviluppatori indipendenti hanno iniziato a sperimentare ottimizzazioni non ufficiali. Una delle prove pi\u00f9 interessanti ha introdotto una modalit\u00e0 ibrida tra <strong>FP8<\/strong> e <strong>NVFP4<\/strong> nel modello di inferenza, con l\u2019obiettivo di abbassare il costo computazionale sulle schede video RTX 50 basate su architettura Blackwell.<\/p><p>Nei test a 4K, questa soluzione ha portato a una riduzione del tempo della fase di neural rendering nell\u2019ordine dell\u20191%-2%. Si tratta quindi di un miglioramento reale, ma molto distante da un salto prestazionale percepibile su larga scala.<\/p>\n        \n        \n        \n        \n        \n      <\/section>\n    \n\n      <section class=\"fbp5-section\">\n        <div class=\"fbp5-section-label\">Tecnica<\/div>\n        <h2>Perch\u00e9 NVFP4 non sta ancora cambiando davvero il comportamento di <span>DLSS 5<\/span><\/h2>\n        <p>Dal punto di vista tecnico, il tentativo ha senso: Blackwell supporta nativamente <strong>NVFP4<\/strong>, un formato a 4 bit pensato per l\u2019inferenza neurale che pu\u00f2 ridurre l\u2019uso di memoria rispetto a FP8 e sfruttare in modo pi\u00f9 diretto l\u2019accelerazione hardware dei Tensor Core di quinta generazione.<\/p><p>Il progetto OptiScaler-DLSSNR-PreSR-Multipass ha introdotto questo percorso nella versione 0.7. 1, ma con un limite chiaro: le forme di modello non supportate tornano automaticamente a FP8. Questo significa che la modalit\u00e0 ibrida non copre l\u2019intera pipeline di calcolo.<\/p>\n        \n        \n        \n        \n        \n      <\/section>\n    \n\n      <section class=\"fbp5-section\">\n        <div class=\"fbp5-section-label\">Risultati<\/div>\n        <h2>Il test su Baldur\u2019s Gate 3 conferma un vantaggio minimo e apre a <span>ottimizzazioni future<\/span><\/h2>\n        <p>In una prova da 120 secondi su Baldur\u2019s Gate 3, la configurazione a precisione mista ha registrato <strong>55,16 fps<\/strong> contro i <strong>54,57 fps<\/strong> della modalit\u00e0 FP8, pari a un incremento di circa l\u20191,08%. \u00c8 un dato coerente con il quadro generale emerso finora: l\u2019approccio funziona, ma non produce ancora quel salto che molti si aspettavano dal supporto hardware a NVFP4.<\/p><p>Il contesto resta comunque interessante perch\u00e9 DLSS 5 \u00e8 al momento il modello DLSS con il carico pi\u00f9 elevato, quindi ogni taglio al costo del neural rendering ha un valore concreto. Nvidia aveva gi\u00e0 indicato che la velocit\u00e0 di esecuzione di DLSS 5 \u00e8 cresciuta sensibilmente rispetto alle prime dimostrazioni pubbliche e che il lavoro di ottimizzazione continuer\u00e0.<\/p>\n        \n        \n        \n        \n        \n      <\/section>\n    \n<\/div><div class=\"rh-attribution-pills\" style=\"display:flex;gap:10px;flex-wrap:wrap;justify-content:flex-start;margin:16px 0 0\"><a href=\"https:\/\/www.ithome.com\/1\/001\/524.htm\" target=\"_blank\" rel=\"noopener\" title=\"Via: VIA\" aria-label=\"Via: VIA\" style=\"display:inline-flex;align-items:center;gap:8px;padding:10px 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>\n","protected":false},"excerpt":{"rendered":"<p>I test della community su DLSS 5 con precisione mista FP8 e NVFP4 mostrano vantaggi molto contenuti sulle RTX 50.<\/p>\n","protected":false},"author":9,"featured_media":48083,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_exactmetrics_skip_tracking":false,"_yoast_wpseo_focuskw_text_input":"DLSS 5 RTX 50 NVFP4","footnotes":""},"categories":[480],"tags":[212,44],"class_list":["post-48084","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","tag-poco","tag-smartphone"],"blocksy_meta":{"styles_descriptor":{"styles":{"desktop":"","tablet":"","mobile":""},"google_fonts":[],"version":8}},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>DLSS 5 con NVFP4 su RTX 50: i test mostrano guadagni minimi<\/title>\n<meta name=\"description\" content=\"Le prove della community su DLSS 5 con precisione mista FP8 e NVFP4 mostrano miglioramenti molto contenuti 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