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È un sistema di intelligenza artificiale locale in grado di comprendere una richiesta, ispezionare lo stato supportato del PC, scegliere uno strumento o un plug-in e quindi eseguire un'azione reale come modificare le impostazioni DLSS, controllare un driver, regolare un profilo della ventola o controllare una periferica.\u003C\u002Fp>\n\u003Caside class=\"editorjs-callout editorjs-callout--info my-6 rounded-xl border p-5 border-blue-300 bg-blue-50 dark:border-blue-900 dark:bg-blue-950\u002F20\" role=\"note\">\u003Cstrong class=\"block mb-2 text-gray-900 dark:text-gray-100\">Risposta diretta\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">\u003Cstrong>G-Assist non è semplicemente un chatbot per la tua GPU.\u003C\u002Fstrong> È un piccolo modello linguistico locale collegato a un insieme di strumenti consentiti. Il modello interpreta ciò che desideri, seleziona una funzione supportata, passa gli argomenti a quella funzione e lo strumento lato PC esegue l'azione.\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Caside class=\"editorjs-callout editorjs-callout--note my-6 rounded-xl border p-5 border-gray-300 bg-gray-50 dark:border-gray-700 dark:bg-gray-900\u002F40\" role=\"note\">\u003Cstrong class=\"block mb-2 text-gray-900 dark:text-gray-100\">Il modello mentale più semplice\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">\u003Cstrong>SLM = comprende la richiesta.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Conoscenza = spiega i concetti supportati NVIDIA\u002FPC.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Strumenti = eseguono azioni.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Plug-in = aggiungono nuovi strumenti.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Il tuo PC = l'ambiente che viene ispezionato o modificato.\u003C\u002Fstrong>\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Cnav class=\"editorjs-toc\" data-editorjs-toc=\"true\" aria-label=\"Contenuti\">\u003Cstrong class=\"editorjs-toc__title\">Contenuti\u003C\u002Fstrong>\u003Col class=\"editorjs-toc__list editorjs-toc__list--depth-0\">\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-5\" class=\"editorjs-toc__link\">Primo: cosa fa effettivamente il modello di IA?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-10\" class=\"editorjs-toc__link\">La pipeline di azione di G-Assist\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-12\" class=\"editorjs-toc__link\">Questa è chiamata di strumenti, non controllo magico del PC\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-17\" class=\"editorjs-toc__link\">Cos'è il livello di conoscenza?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-24\" class=\"editorjs-toc__link\">G-Assist utilizza il RAG?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-28\" class=\"editorjs-toc__link\">Perché G-Assist può funzionare offline\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-33\" class=\"editorjs-toc__link\">Il costo dell'IA locale: G-Assist utilizza la tua GPU e la VRAM\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-40\" class=\"editorjs-toc__link\">Modalità Ragionamento vs Modalità Flash\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-44\" class=\"editorjs-toc__link\">Cosa aggiungono effettivamente i plug-in\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-49\" class=\"editorjs-toc__link\">G-Assist Protocol V2 è JSON-RPC 2.0\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-54\" class=\"editorjs-toc__link\">Dove entra in gioco MCP\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-59\" class=\"editorjs-toc__link\">Perché questo conta al di là delle luci RGB\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-63\" class=\"editorjs-toc__link\">Lo stack dell'agente locale\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-65\" class=\"editorjs-toc__link\">Perché i confini degli strumenti sono una caratteristica di sicurezza\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-70\" class=\"editorjs-toc__link\">Il confine tra autorità e strumenti\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-72\" class=\"editorjs-toc__link\">Perché G-Assist può ridurre temporaneamente le prestazioni di gioco\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-77\" class=\"editorjs-toc__link\">Il test delle risorse dell'assistente locale\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-79\" class=\"editorjs-toc__link\">Perché i plug-in meritano lo stesso esame di qualsiasi altro software\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-84\" class=\"editorjs-toc__link\">G-Assist è più vicino a un agente che a un chatbot\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-89\" class=\"editorjs-toc__link\">Ciò che G-Assist ancora non è\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-93\" class=\"editorjs-toc__link\">Cosa è cambiato nelle versioni attuali?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-96\" class=\"editorjs-toc__link\">Cosa potrebbe cambiare questa risposta?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-100\" class=\"editorjs-toc__link\">Limitazioni\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-104\" class=\"editorjs-toc__link\">Conclusione\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-109\" class=\"editorjs-toc__link\">FAQ\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-111\" class=\"editorjs-toc__link\">Glossario\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-113\" class=\"editorjs-toc__link\">Fonti primarie\u003C\u002Fa>\u003C\u002Fli>\u003C\u002Fol>\u003C\u002Fnav>\n\u003Ch2 id=\"section-5\">Primo: cosa fa effettivamente il modello di IA?\u003C\u002Fh2>\n\u003Cp>G-Assist utilizza un piccolo modello linguistico locale, o SLM. Attualmente NVIDIA descrive il sistema come l'uso di un modello instruct basato su Llama con 8 miliardi di parametri.\u003C\u002Fp>\n\u003Cp>Il compito principale del modello non è renderizzare grafica o modificare direttamente i registri hardware. Il suo compito è comprendere il linguaggio dell'utente, decidere quale capacità supportata corrisponde alla richiesta e preparare la chiamata a quella capacità.\u003C\u002Fp>\n\u003Cp>Ad esempio, se dici \"imposta DLSS Super Resolution in modalità Prestazioni\", il modello linguistico non modifica esso stesso il DLSS. Interpreta il comando e lo indirizza alla funzione supportata che può modificare l'impostazione.\u003C\u002Fp>\n\u003Caside class=\"editorjs-callout editorjs-callout--success my-6 rounded-xl border p-5 border-emerald-300 bg-emerald-50 dark:border-emerald-900 dark:bg-emerald-950\u002F20\" role=\"note\">\u003Cstrong class=\"block mb-2 text-gray-900 dark:text-gray-100\">La distinzione importante\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">Il modello di IA \u003Cstrong>decide quale strumento chiamare\u003C\u002Fstrong>. Lo strumento \u003Cstrong>fa il lavoro reale\u003C\u002Fstrong>.\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Ch2 id=\"section-10\">La pipeline di azione di G-Assist\u003C\u002Fh2>\n\u003Csection class=\"editorjs-process my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Cosa succede dopo che dai un comando a G-Assist\u003C\u002Fh3>\u003Cdiv class=\"grid grid-cols-1 md:grid-cols-2 xl:grid-cols-3 gap-4\">\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">1\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">1. Fornisci una richiesta in linguaggio naturale\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Ad esempio: \"Ottimizza questo gioco per le prestazioni.\"\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">2\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">2. L'SLM locale interpreta la richiesta\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Determina l'intento dell'utente e identifica quale funzione supportata o plug-in è rilevante.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">3\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">3. Il sistema sceglie uno strumento\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Potrebbe essere una funzione integrata per le impostazioni grafiche, il controllo del driver, una funzione di monitoraggio o un plug-in della community.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">4\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">4. Vengono estratti gli argomenti\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Il modello converte la richiesta in valori strutturati come nome del gioco, modalità, profilo della ventola o impostazione DLSS.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">5\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">5. Lo strumento viene eseguito\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Lo strumento comunica con l'App NVIDIA, il sistema operativo, il software della periferica o un altro servizio.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">6\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">6. Il risultato viene restituito\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">G-Assist riporta cosa è successo o restituisce dati che il modello può spiegare.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-12\">Questa è chiamata di strumenti, non controllo magico del PC\u003C\u002Fh2>\n\u003Cp>Un modello linguistico non può controllare in modo sicuro un computer arbitrario semplicemente perché comprende l'inglese.\u003C\u002Fp>\n\u003Cp>Ha bisogno di un'interfaccia definita che specifichi quali azioni esistono, quali argomenti accettano e cosa restituisce lo strumento.\u003C\u002Fp>\n\u003Cp>Le attuali capacità integrate di G-Assist includono funzioni come l'ottimizzazione delle impostazioni grafiche, la modifica delle opzioni RTX supportate, il controllo o il download dei driver, la visualizzazione delle informazioni sulle prestazioni, la modifica di alcune funzionalità di alimentazione del laptop, il controllo delle funzioni del monitor supportate e l'uso di plug-in per periferiche supportate.\u003C\u002Fp>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Modello linguistico vs strumento\u003C\u002Fh3>\u003Cdiv class=\"overflow-x-auto\">\u003Ctable class=\"w-full border-collapse\">\u003Cthead>\u003Ctr>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left dark:border-gray-700 dark:bg-gray-900\">\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">Modello linguistico\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">Strumento \u002F plug-in\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Comprendere "attiva DLSS"\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Scegliere la funzione corretta\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Modificare effettivamente l'impostazione\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Spiegare il risultato\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-17\">Cos'è il livello di conoscenza?\u003C\u002Fh2>\n\u003Cp>G-Assist ha anche un livello di conoscenza per rispondere a domande e fornire raccomandazioni.\u003C\u002Fp>\n\u003Cp>NVIDIA afferma che la versione 0.2.1 ha introdotto un sistema di conoscenza migliorato che aiuta G-Assist a fornire raccomandazioni sulle impostazioni più accurate.\u003C\u002Fp>\n\u003Cp>Quel livello di conoscenza è diverso dallo stato attuale del tuo PC.\u003C\u002Fp>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Conoscenza vs stato attuale del PC\u003C\u002Fh3>\u003Cdiv class=\"overflow-x-auto\">\u003Ctable class=\"w-full border-collapse\">\u003Cthead>\u003Ctr>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left dark:border-gray-700 dark:bg-gray-900\">\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">Conoscenza\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">Stato attuale\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">GPU\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Impostazioni di gioco\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Prestazioni\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Caside class=\"editorjs-callout editorjs-callout--warning my-6 rounded-xl border p-5 border-amber-300 bg-amber-50 dark:border-amber-900 dark:bg-amber-950\u002F20\" role=\"note\">\u003Cstrong class=\"block mb-2 text-gray-900 dark:text-gray-100\">Non confondere la conoscenza con lo stato\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">\u003Cstrong>La conoscenza\u003C\u002Fstrong> dice all'assistente cosa significa una funzionalità o cosa di solito è importante.\u003Cbr>\u003Cstrong>Lo stato\u003C\u002Fstrong> gli dice cosa è vero sulla tua macchina in questo momento.\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Caside class=\"editorjs-referral my-6\">\u003Ca href=\"https:\u002F\u002Fstajic.de\u002Fblog\u002Fwhat-is-rag-the-simplest-explanation-of-how-it-works\" target=\"_blank\" rel=\"noopener noreferrer\" class=\"flex flex-col sm:flex-row gap-4 rounded-xl border border-gray-200 dark:border-gray-700 p-4 transition hover:border-primary-500\">\u003Cdiv class=\"min-w-0 flex-1\">\u003Cstrong class=\"block text-lg text-gray-900 dark:text-gray-100\">Cos'è il RAG? La spiegazione più semplice di come funziona\u003C\u002Fstrong>\u003Cp class=\"mt-2 text-sm text-gray-600 dark:text-gray-300\">Una spiegazione in linguaggio semplice del recupero della conoscenza, dello stato, della memoria, del contesto e del modello linguistico.\u003C\u002Fp>\u003Cspan class=\"mt-3 inline-flex text-sm font-medium text-primary-600 dark:text-primary-400\">Leggi la guida semplice al RAG →\u003C\u002Fspan>\u003C\u002Fdiv>\u003C\u002Fa>\u003C\u002Faside>\n\u003Ch2 id=\"section-24\">G-Assist utilizza il RAG?\u003C\u002Fh2>\n\u003Cp>La risposta più sicura è: G-Assist ha chiaramente un sistema di conoscenza, ma la pagina pubblica del prodotto NVIDIA non documenta ogni meccanismo di recupero interno con sufficiente dettaglio per affermare che ogni risposta di conoscenza sia specificamente prodotta dal RAG.\u003C\u002Fp>\n\u003Cp>La distinzione architetturale conta comunque. Un livello di recupero può fornire conoscenze pertinenti, mentre gli strumenti di sistema forniscono lo stato attuale del PC ed eseguono azioni.\u003C\u002Fp>\n\u003Cp>È la stessa separazione utilizzata in molti agenti moderni: la conoscenza è una fonte di contesto, le osservazioni in tempo reale un'altra, e l'esecuzione degli strumenti una terza.\u003C\u002Fp>\n\u003Ch2 id=\"section-28\">Perché G-Assist può funzionare offline\u003C\u002Fh2>\n\u003Cp>NVIDIA esegue il modello linguistico localmente sulla GPU GeForce RTX.\u003C\u002Fp>\n\u003Cp>Ciò significa che l'assistente principale non richiede un modello linguistico ospitato nel cloud per ogni prompt.\u003C\u002Fp>\n\u003Cp>NVIDIA afferma esplicitamente che G-Assist può funzionare offline per le sue capacità locali.\u003C\u002Fp>\n\u003Cp>Un plug-in può comunque utilizzare Internet se quel plug-in chiama un servizio online. L'esecuzione del modello locale e l'accesso ai plug-in online sono questioni separate.\u003C\u002Fp>\n\u003Ch2 id=\"section-33\">Il costo dell'IA locale: G-Assist utilizza la tua GPU e la VRAM\u003C\u002Fh2>\n\u003Cp>L'esecuzione locale offre privacy e indipendenza da un modello cloud, ma il lavoro deve essere eseguito da qualche parte.\u003C\u002Fp>\n\u003Cp>Per G-Assist, quel \"da qualche parte\" è la stessa GPU GeForce RTX che potrebbe già stare renderizzando il tuo gioco.\u003C\u002Fp>\n\u003Cp>NVIDIA avverte che la GPU alloca brevemente risorse di calcolo all'inferenza dell'IA quando G-Assist risponde. Se un gioco impegnativo è in esecuzione contemporaneamente, il gioco può perdere temporaneamente parte delle prestazioni di rendering mentre il modello è attivo.\u003C\u002Fp>\n\u003Cp>I requisiti attuali specificano anche obiettivi di VRAM libera oltre alla memoria già utilizzata dal gioco: circa 6 GB di VRAM libera per la Modalità Ragionamento e 4,5 GB per la Modalità Flash.\u003C\u002Fp>\n\u003Caside class=\"editorjs-callout editorjs-callout--warning my-6 rounded-xl border p-5 border-amber-300 bg-amber-50 dark:border-amber-900 dark:bg-amber-950\u002F20\" role=\"note\">\u003Cstrong class=\"block mb-2 text-gray-900 dark:text-gray-100\">8 GB di VRAM non significa che 8 GB siano disponibili per G-Assist\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">Il gioco, Windows, il driver e altre applicazioni consumano già VRAM. Il requisito di G-Assist riguarda la \u003Cstrong>VRAM libera in aggiunta a quella già utilizzata dal carico di lavoro in esecuzione\u003C\u002Fstrong>.\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Caside class=\"editorjs-referral my-6\">\u003Ca href=\"https:\u002F\u002Ffigure.rocks\u002Fit\u002Fblog\u002Fvram-usage-is-not-vram-requirement-why-a-full-memory-meter-does-not-tell-the-whole-story\" class=\"flex flex-col sm:flex-row gap-4 rounded-xl border border-gray-200 dark:border-gray-700 p-4 transition hover:border-primary-500\">\u003Cdiv class=\"min-w-0 flex-1\">\u003Cstrong class=\"block text-lg text-gray-900 dark:text-gray-100\">L'utilizzo della VRAM non è il requisito di VRAM: perché un misuratore di memoria pieno non racconta tutta la storia\u003C\u002Fstrong>\u003Cp class=\"mt-2 text-sm text-gray-600 dark:text-gray-300\">Perché la VRAM installata, l'utilizzo attuale, i budget di residenza e la reale pressione sulla memoria sono cose diverse.\u003C\u002Fp>\u003Cspan class=\"mt-3 inline-flex text-sm font-medium text-primary-600 dark:text-primary-400\">Leggi la guida sulla VRAM →\u003C\u002Fspan>\u003C\u002Fdiv>\u003C\u002Fa>\u003C\u002Faside>\n\u003Ch2 id=\"section-40\">Modalità Ragionamento vs Modalità Flash\u003C\u002Fh2>\n\u003Cp>Le versioni attuali di G-Assist separano una Modalità Ragionamento più capace da una Modalità Flash più veloce.\u003C\u002Fp>\n\u003Cp>La Modalità Ragionamento è progettata per decisioni di qualità superiore e può coordinare più azioni da un singolo prompt. La Modalità Flash è ottimizzata per risposte più rapide e una domanda di risorse inferiore.\u003C\u002Fp>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Modalità Ragionamento vs Modalità Flash\u003C\u002Fh3>\u003Cdiv class=\"overflow-x-auto\">\u003Ctable class=\"w-full border-collapse\">\u003Cthead>\u003Ctr>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left dark:border-gray-700 dark:bg-gray-900\">\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">Modalità Ragionamento\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">Modalità Flash\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Obiettivo principale\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">VRAM libera consigliata\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Ideale per\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-44\">Cosa aggiungono effettivamente i plug-in\u003C\u002Fh2>\n\u003Cp>Un plug-in non sostituisce il modello linguistico. Fornisce al modello una nuova azione che è autorizzato a chiamare.\u003C\u002Fp>\n\u003Cp>Il plug-in definisce funzioni, descrizioni e parametri. G-Assist legge quelle descrizioni, abbina una richiesta dell'utente alla funzione appropriata e le invia argomenti strutturati.\u003C\u002Fp>\n\u003Cp>Ciò consente all'assistente di crescere oltre le funzioni integrate di NVIDIA.\u003C\u002Fp>\n\u003Csection class=\"editorjs-process my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Come funziona un plug-in di G-Assist\u003C\u002Fh3>\u003Cdiv class=\"grid grid-cols-1 md:grid-cols-2 xl:grid-cols-3 gap-4\">\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">1\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">1. Il plug-in dichiara una funzione\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Ad esempio: set_keyboard_color(color).\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">2\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">2. Il manifest descrive la funzione\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Il manifest indica a G-Assist cosa fa la funzione e quali parametri richiede.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">3\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">3. L'utente chiede in modo naturale\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Ad esempio: “Rendi la mia tastiera verde.”\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">4\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">4. L'SLM seleziona la funzione\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Il modello mappa la richiesta sulla funzione del plug-in ed estrae verde come parametro.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">5\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">5. Il plug-in esegue\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Il plug-in comunica con il software della periferica o il servizio esterno.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-49\">G-Assist Protocol V2 è JSON-RPC 2.0\u003C\u002Fh2>\n\u003Cp>L'attuale repository pubblico di plug-in di NVIDIA utilizza il Protocollo V2.\u003C\u002Fp>\n\u003Cp>Il Protocollo V2 utilizza JSON-RPC 2.0 con messaggi con prefisso di lunghezza tra il motore G-Assist e i plug-in.\u003C\u002Fp>\n\u003Cp>Il motore può inizializzare un plug-in, verificarne lo stato di salute, eseguire una funzione, inviare input dell'utente e spegnerlo. I plug-in possono restituire risultati, trasmettere in streaming il progresso o segnalare errori.\u003C\u002Fp>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">I messaggi importanti del Protocollo V2\u003C\u002Fh3>\u003Cdiv class=\"overflow-x-auto\">\u003Ctable class=\"w-full border-collapse\">\u003Cthead>\u003Ctr>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left dark:border-gray-700 dark:bg-gray-900\">\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">Direzione\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">Scopo\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">initialize\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">ping\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">execute\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">stream\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">complete\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-54\">Dove entra in gioco MCP\u003C\u002Fh2>\n\u003Cp>Il protocollo plug-in proprietario di G-Assist non è MCP. Il suo attuale sistema pubblico di plug-in utilizza JSON-RPC 2.0.\u003C\u002Fp>\n\u003Cp>Tuttavia, un plug-in di G-Assist può connettersi a un server MCP.\u003C\u002Fp>\n\u003Cp>La versione attuale 0.2.2 di NVIDIA include un'integrazione Elgato che può invocare azioni esposte tramite il server MCP di Elgato Stream Deck.\u003C\u002Fp>\n\u003Caside class=\"editorjs-callout editorjs-callout--success my-6 rounded-xl border p-5 border-emerald-300 bg-emerald-50 dark:border-emerald-900 dark:bg-emerald-950\u002F20\" role=\"note\">\u003Cstrong class=\"block mb-2 text-gray-900 dark:text-gray-100\">Distinzione importante tra protocolli\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">\u003Cstrong>G-Assist ↔ il suo plug-in:\u003C\u002Fstrong> NVIDIA Protocol V2 \u002F JSON-RPC 2.0.\u003Cbr>\u003Cstrong>Plug-in ↔ un altro ecosistema di strumenti:\u003C\u002Fstrong> può utilizzare MCP quando tale integrazione lo supporta.\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Ch2 id=\"section-59\">Perché questo conta al di là delle luci RGB\u003C\u002Fh2>\n\u003Cp>L'architettura dei plug-in trasforma G-Assist da un assistente fisso a un router locale di strumenti.\u003C\u002Fp>\n\u003Cp>Lo stesso schema può connettere un SLM a strumenti di monitoraggio, periferiche, API, sistemi di automazione, applicazioni locali o servizi esterni.\u003C\u002Fp>\n\u003Cp>L'unità architetturale importante non è quindi la finestra di chat. È il confine tra l'intento in linguaggio naturale e l'esecuzione strutturata degli strumenti.\u003C\u002Fp>\n\u003Ch2 id=\"section-63\">Lo stack dell'agente locale\u003C\u002Fh2>\n\u003Csection class=\"editorjs-process my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Un modo utile di pensare a G-Assist\u003C\u002Fh3>\u003Cdiv class=\"grid grid-cols-1 md:grid-cols-2 xl:grid-cols-3 gap-4\">\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">1\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">1. Intento dell'utente\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Comando in linguaggio naturale o vocale.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">2\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">2. SLM locale\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Comprende la richiesta e sceglie una capacità.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">3\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">3. Conoscenza \u002F contesto\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Fornisce conoscenze sul prodotto, raccomandazioni o informazioni necessarie per la decisione.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">4\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">4. Stato del sistema in tempo reale\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Fornisce informazioni attuali su hardware, driver, prestazioni o configurazione quando supportato.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">5\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">5. Selezione dello strumento\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Viene scelta una funzione integrata o un plug-in.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">6\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">6. Esecuzione strutturata\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">La funzione riceve argomenti ed esegue l'azione reale.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">7\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">7. Verifica del risultato\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Lo strumento restituisce stato o dati e il modello spiega cosa è successo.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-65\">Perché i confini degli strumenti sono una caratteristica di sicurezza\u003C\u002Fh2>\n\u003Cp>Un assistente AI in grado di eseguire comandi arbitrari del sistema operativo sarebbe molto più potente, ma anche molto più difficile da limitare.\u003C\u002Fp>\n\u003Cp>G-Assist invece espone funzioni definite con parametri noti.\u003C\u002Fp>\n\u003Cp>Ciò significa che il modello può eseguire solo azioni rese disponibili dall'insieme di funzioni integrate o dai plug-in installati.\u003C\u002Fp>\n\u003Cp>Questo non elimina tutti i rischi, specialmente con plug-in di terze parti, ma crea un confine di autorizzazione e capacità più chiaro rispetto all'accesso illimitato alla shell.\u003C\u002Fp>\n\u003Ch2 id=\"section-70\">Il confine tra autorità e strumenti\u003C\u002Fh2>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Cosa l'assistente può capire vs cosa è autorizzato a fare\u003C\u002Fh3>\u003Cdiv class=\"overflow-x-auto\">\u003Ctable class=\"w-full border-collapse\">\u003Cthead>\u003Ctr>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left dark:border-gray-700 dark:bg-gray-900\">\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">Il modello può capire\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">Autorità dello strumento\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Ottimizzazione GPU\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">File\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Internet\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Controllo periferiche\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-72\">Perché G-Assist può ridurre temporaneamente le prestazioni di gioco\u003C\u002Fh2>\n\u003Cp>L'architettura con modello locale ha una conseguenza diretta: l'IA e il gioco possono competere per la stessa GPU.\u003C\u002Fp>\n\u003Cp>NVIDIA avverte esplicitamente che la frequenza di rendering o la velocità di inferenza possono calare brevemente mentre G-Assist elabora una richiesta durante un carico di lavoro intenso sulla GPU.\u003C\u002Fp>\n\u003Cp>Una volta terminata l'inferenza, queste risorse GPU tornano al gioco.\u003C\u002Fp>\n\u003Cp>Questo è diverso da un assistente cloud, dove la maggior parte dell'inferenza del modello avviene su un server remoto e non consuma la GPU da gaming.\u003C\u002Fp>\n\u003Ch2 id=\"section-77\">Il test delle risorse dell'assistente locale\u003C\u002Fh2>\n\u003Csection class=\"editorjs-process my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Come giudicare se un assistente da gaming locale è adatto al tuo PC\u003C\u002Fh3>\u003Cdiv class=\"grid grid-cols-1 md:grid-cols-2 xl:grid-cols-3 gap-4\">\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">1\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">1. Controlla la VRAM installata\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Il requisito minimo attuale di G-Assist è una GPU RTX con almeno 6 GB di VRAM.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">2\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">2. Controlla la VRAM libera durante il gioco effettivo\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">La capacità installata non è la stessa cosa della capacità libera.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">3\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">3. Scegli in modo appropriato la modalità Reasoning o Flash\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Usa la modalità più leggera quando la pressione sulle risorse conta più del ragionamento approfondito.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">4\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">4. Misura i cali di frame rate durante l'inferenza\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Osserva il gioco mentre chiedi a G-Assist di eseguire attività.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">5\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">5. Ispeziona l'autorità degli strumenti\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Sappi esattamente quali funzioni integrate e plug-in possono modificare il tuo sistema.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">6\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">6. Tratta i plug-in di terze parti come software\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Esamina il loro codice sorgente, i permessi, l'accesso alla rete e le credenziali memorizzate.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-79\">Perché i plug-in meritano lo stesso esame di qualsiasi altro software\u003C\u002Fh2>\n\u003Cp>Un plug-in può collegare l'assistente ad API, applicazioni periferiche e servizi online.\u003C\u002Fp>\n\u003Cp>Ciò significa che un plug-in può gestire valori di configurazione, credenziali o richieste esterne a seconda di ciò per cui è stato creato.\u003C\u002Fp>\n\u003Cp>Il repository di NVIDIA fornisce esplicitamente una posizione config.json per le impostazioni dei plug-in e avverte gli sviluppatori di non commettere credenziali.\u003C\u002Fp>\n\u003Cp>La domanda di sicurezza corretta quindi non è solo \"G-Assist è locale?\" ma anche \"A cosa si connette ogni plug-in installato?\"\u003C\u002Fp>\n\u003Ch2 id=\"section-84\">G-Assist è più vicino a un agente che a un chatbot\u003C\u002Fh2>\n\u003Cp>Un chatbot produce principalmente linguaggio.\u003C\u002Fp>\n\u003Cp>Un agente interpreta un obiettivo, osserva le informazioni rilevanti, sceglie un'azione, chiama uno strumento e valuta il risultato.\u003C\u002Fp>\n\u003Cp>G-Assist ora corrisponde molto più da vicino a questa seconda descrizione perché può coordinare più azioni, ispezionare lo stato supportato del PC e invocare strumenti reali.\u003C\u002Fp>\n\u003Caside class=\"editorjs-referral my-6\">\u003Ca href=\"https:\u002F\u002Ffigure.rocks\u002Fit\u002Fblog\u002Fpubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning\" class=\"flex flex-col sm:flex-row gap-4 rounded-xl border border-gray-200 dark:border-gray-700 p-4 transition hover:border-primary-500\">\u003Cdiv class=\"min-w-0 flex-1\">\u003Cstrong class=\"block text-lg text-gray-900 dark:text-gray-100\">PUBG Ally mostra perché i compagni di squadra IA hanno bisogno di due cervelli: riflessi rapidi e ragionamento lento\u003C\u002Fstrong>\u003Cp class=\"mt-2 text-sm text-gray-600 dark:text-gray-300\">Un esempio di architettura di un agente di gioco che mostra la separazione tra ragionamento, stato in tempo reale, strumenti ed esecuzione deterministica.\u003C\u002Fp>\u003Cspan class=\"mt-3 inline-flex text-sm font-medium text-primary-600 dark:text-primary-400\">Leggi la guida all'architettura di PUBG Ally →\u003C\u002Fspan>\u003C\u002Fdiv>\u003C\u002Fa>\u003C\u002Faside>\n\u003Ch2 id=\"section-89\">Ciò che G-Assist ancora non è\u003C\u002Fh2>\n\u003Cp>NVIDIA descrive esplicitamente G-Assist come un assistente locale specializzato, non come un'IA conversazionale generica.\u003C\u002Fp>\n\u003Cp>Il suo valore deriva dalla comprensione di un insieme mirato di attività relative a PC e gaming e dalla disponibilità di strumenti collegati a tali attività.\u003C\u002Fp>\n\u003Cp>Questa focalizzazione è importante perché un modello locale più piccolo può essere utile quando il sistema circostante gli fornisce strumenti potenti e confini chiari.\u003C\u002Fp>\n\u003Ch2 id=\"section-93\">Cosa è cambiato nelle versioni attuali?\u003C\u002Fh2>\n\u003Cp>La cronologia delle versioni pubbliche attuali mostra G-Assist in costante evoluzione verso un agente locale più capace.\u003C\u002Fp>\n\u003Cdiv class=\"overflow-x-auto\">\u003Ctable class=\"w-full border-collapse\">\u003Cthead>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-2 text-left font-semibold\">Versione\u003C\u002Fth>\u003Cth class=\"border border-gray-300 px-4 py-2 text-left font-semibold\">Modifica importante\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Ctd class=\"border border-gray-300 px-4 py-2\">0.1.17\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Modello più leggero, tutte le GPU RTX con 6 GB+ di VRAM, plug-in della community\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd class=\"border border-gray-300 px-4 py-2\">0.1.18\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Ottimizzazione per laptop, controlli BatteryBoost e WhisperMode\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd class=\"border border-gray-300 px-4 py-2\">0.2\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Modalità di ragionamento, modalità Flash, prompt multi-azione, nuovi controlli dei dispositivi\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd class=\"border border-gray-300 px-4 py-2\">0.2.1\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Sistema di conoscenza migliorato, raccomandazioni migliori, controlli delle funzionalità RTX\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd class=\"border border-gray-300 px-4 py-2\">0.2.2\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Integrazione con Elgato Stream Deck tramite un server MCP\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003C\u002Fdiv>\n\u003Ch2 id=\"section-96\">Cosa potrebbe cambiare questa risposta?\u003C\u002Fh2>\n\u003Cp>G-Assist è ancora sperimentale e la sua architettura è in evoluzione.\u003C\u002Fp>\n\u003Cp>Le dimensioni del modello, i requisiti di VRAM, il set di strumenti, il protocollo dei plug-in e il supporto hardware possono tutti cambiare nelle versioni future.\u003C\u002Fp>\n\u003Cp>Una versione futura potrebbe anche spostare parte dell'inferenza su una NPU o introdurre un'integrazione MCP più ampia, ma non bisogna presumerlo finché NVIDIA non lo documenta.\u003C\u002Fp>\n\u003Ch2 id=\"section-100\">Limitazioni\u003C\u002Fh2>\n\u003Cp>Questo articolo descrive la documentazione pubblica del prodotto G-Assist di NVIDIA e l'architettura pubblica dei plug-in a partire da settembre 2026.\u003C\u002Fp>\n\u003Cp>NVIDIA non documenta pubblicamente ogni dettaglio interno della sua pipeline di conoscenza e raccomandazione, quindi questo articolo non afferma che ogni risposta di conoscenza utilizzi RAG o qualsiasi altra specifica implementazione di recupero.\u003C\u002Fp>\n\u003Cp>I plug-in di terze parti possono avere comportamenti e accesso alla rete al di là delle funzioni integrate di NVIDIA, quindi ogni plug-in dovrebbe essere valutato separatamente.\u003C\u002Fp>\n\u003Ch2 id=\"section-104\">Conclusione\u003C\u002Fh2>\n\u003Cp>Il modo più semplice per comprendere Project G-Assist è smettere di pensarlo come un chatbot.\u003C\u002Fp>\n\u003Cp>Il SLM locale interpreta la tua richiesta. La conoscenza lo aiuta a comprendere il problema. Le informazioni di sistema in tempo reale gli dicono cosa è vero sul tuo PC. Una funzione integrata o un plug-in definisce ciò che gli è effettivamente consentito fare. Lo strumento esegue l'azione e restituisce il risultato.\u003C\u002Fp>\n\u003Cp>Questa è un'architettura di agente locale.\u003C\u002Fp>\n\u003Cp>La sua idea più forte non è che un modello da 8 miliardi di parametri possa parlare della tua GPU. È che un modello locale relativamente piccolo può diventare utile quando è collegato a strumenti ben definiti, allo stato corrente e a un confine d'azione controllato.\u003C\u002Fp>\n\u003Ch2 id=\"section-109\">FAQ\u003C\u002Fh2>\n\u003Csection class=\"editorjs-faq my-6 rounded-xl border border-gray-200 p-5 dark:border-gray-700\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">NVIDIA Project G-Assist in parole semplici\u003C\u002Fh3>\u003Cdiv id=\"faq1\" class=\"border-t border-gray-200 py-4 first:border-t-0 dark:border-gray-700\">\u003Ch4 class=\"font-semibold text-gray-900 dark:text-gray-100\">G-Assist è un chatbot cloud?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">No. Il suo modello linguistico principale viene eseguito localmente sulla GPU GeForce RTX e può funzionare offline per le funzioni locali supportate.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv id=\"faq2\" class=\"border-t border-gray-200 py-4 first:border-t-0 dark:border-gray-700\">\u003Ch4 class=\"font-semibold text-gray-900 dark:text-gray-100\">Quale modello utilizza G-Assist?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Attualmente NVIDIA lo descrive come un modello instruct locale basato su Llama con 8 miliardi di parametri.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv id=\"faq3\" class=\"border-t border-gray-200 py-4 first:border-t-0 dark:border-gray-700\">\u003Ch4 class=\"font-semibold text-gray-900 dark:text-gray-100\">Il modello AI modifica direttamente le impostazioni della mia GPU?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">No. Il modello seleziona una funzione integrata o un plug-in supportato, e quello strumento esegue la modifica effettiva.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv id=\"faq4\" class=\"border-t border-gray-200 py-4 first:border-t-0 dark:border-gray-700\">\u003Ch4 class=\"font-semibold text-gray-900 dark:text-gray-100\">G-Assist utilizza VRAM durante il gaming?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Sì. NVIDIA consiglia VRAM libera aggiuntiva per l'assistente e avverte che l'inferenza può ridurre brevemente le prestazioni di rendering del gioco.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv id=\"faq5\" class=\"border-t border-gray-200 py-4 first:border-t-0 dark:border-gray-700\">\u003Ch4 class=\"font-semibold text-gray-900 dark:text-gray-100\">I plug-in di G-Assist sono plug-in MCP?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Non direttamente. L'attuale protocollo plug-in di G-Assist utilizza JSON-RPC 2.0, sebbene un plug-in possa connettersi a un server MCP.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv id=\"faq6\" class=\"border-t border-gray-200 py-4 first:border-t-0 dark:border-gray-700\">\u003Ch4 class=\"font-semibold text-gray-900 dark:text-gray-100\">G-Assist può funzionare offline?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Il suo assistente locale può farlo, ma i singoli plug-in potrebbero comunque richiedere l'accesso a Internet se chiamano servizi online.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv id=\"faq7\" class=\"border-t border-gray-200 py-4 first:border-t-0 dark:border-gray-700\">\u003Ch4 class=\"font-semibold text-gray-900 dark:text-gray-100\">G-Assist è un assistente AI generico?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">NVIDIA lo descrive come un assistente specializzato per PC e gaming piuttosto che un modello conversazionale generico e ampio.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-111\">Glossario\u003C\u002Fh2>\n\u003Csection class=\"editorjs-glossary my-6 rounded-xl border border-gray-200 dark:border-gray-700 p-5\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Termini chiave di G-Assist\u003C\u002Fh3>\u003Cdl>\u003Cdiv id=\"slm\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">SLM\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Small Language Model, un modello linguistico compatto progettato per essere eseguito localmente con requisiti hardware inferiori rispetto ai grandi modelli cloud.\u003C\u002Fdd>\u003C\u002Fdiv>\u003Cdiv id=\"tool-calling\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">Tool calling\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Il processo in cui un modello linguistico sceglie una funzione definita e fornisce argomenti strutturati affinché un altro componente possa eseguire un'azione.\u003C\u002Fdd>\u003C\u002Fdiv>\u003Cdiv id=\"plugin\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">Plug-in\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Un'estensione che espone funzioni o integrazioni aggiuntive a G-Assist.\u003C\u002Fdd>\u003C\u002Fdiv>\u003Cdiv id=\"json-rpc\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">JSON-RPC 2.0\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Il protocollo di messaggistica strutturato utilizzato dall'attuale sistema di plug-in G-Assist Protocol V2.\u003C\u002Fdd>\u003C\u002Fdiv>\u003Cdiv id=\"mcp\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">MCP\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Model Context Protocol, un protocollo separato di interoperabilità di strumenti e contesto che alcune integrazioni esterne possono esporre.\u003C\u002Fdd>\u003C\u002Fdiv>\u003Cdiv id=\"tool-authority-boundary\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">Tool-Authority Boundary\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Un modello Figure Rocks che separa ciò che un modello AI può comprendere da ciò che i suoi strumenti collegati gli consentono effettivamente di fare.\u003C\u002Fdd>\u003C\u002Fdiv>\u003Cdiv id=\"local-agent-stack\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">Local Agent Stack\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Un modello Figure Rocks che combina intento dell'utente, SLM locale, conoscenza, stato in tempo reale, selezione degli strumenti, esecuzione e verifica dei risultati.\u003C\u002Fdd>\u003C\u002Fdiv>\u003Cdiv id=\"local-assistant-resource-test\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">Local Assistant Resource Test\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Un flusso di lavoro Figure Rocks per valutare VRAM, costo di inferenza, autorizzazioni degli strumenti e rischio dei plug-in prima di utilizzare un assistente di gaming locale.\u003C\u002Fdd>\u003C\u002Fdiv>\u003C\u002Fdl>\u003C\u002Fsection>\n\u003Ch2 id=\"section-113\">Fonti primarie\u003C\u002Fh2>\n\u003Ca href=\"https:\u002F\u002Fwww.nvidia.com\u002Fen-us\u002Fsoftware\u002Fnvidia-app\u002Fg-assist\u002F\" target=\"_blank\" rel=\"noopener noreferrer\" class=\"editorjs-link-tool block border border-gray-200 dark:border-gray-700 rounded-lg p-4 transition text-gray-900 dark:text-gray-100 hover:border-primary-500 hover:bg-primary-50 dark:hover:bg-gray-900 hover:text-gray-900 dark:hover:text-gray-100\">\u003Cstrong class=\"block font-semibold\">NVIDIA — Project G-Assist\u003C\u002Fstrong>\u003Cp class=\"text-sm text-gray-600 dark:text-gray-400\">Pagina ufficiale attuale del prodotto che copre il modello locale, le funzioni supportate, le modalità Reasoning e Flash, i requisiti VRAM, i controlli RTX, i plug-in e l'integrazione Elgato basata su MCP versione 0.2.2.\u003C\u002Fp>\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FG-Assist\" target=\"_blank\" rel=\"noopener noreferrer\" class=\"editorjs-link-tool block border border-gray-200 dark:border-gray-700 rounded-lg p-4 transition text-gray-900 dark:text-gray-100 hover:border-primary-500 hover:bg-primary-50 dark:hover:bg-gray-900 hover:text-gray-900 dark:hover:text-gray-100\">\u003Cstrong class=\"block font-semibold\">NVIDIA — G-Assist GitHub\u003C\u002Fstrong>\u003Cp class=\"text-sm text-gray-600 dark:text-gray-400\">Repository pubblico ufficiale dei plug-in che documenta l'architettura dei moduli di G-Assist, il rilevamento dei plug-in e il Protocol V2.\u003C\u002Fp>\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FG-Assist\u002Fblob\u002Fmain\u002FPLUGIN_MIGRATION_GUIDE_V2.md\" target=\"_blank\" rel=\"noopener noreferrer\" class=\"editorjs-link-tool block border border-gray-200 dark:border-gray-700 rounded-lg p-4 transition text-gray-900 dark:text-gray-100 hover:border-primary-500 hover:bg-primary-50 dark:hover:bg-gray-900 hover:text-gray-900 dark:hover:text-gray-100\">\u003Cstrong class=\"block font-semibold\">NVIDIA — Guida alla migrazione a G-Assist Protocol V2\u003C\u002Fstrong>\u003Cp class=\"text-sm text-gray-600 dark:text-gray-400\">Documentazione ufficiale del protocollo che copre JSON-RPC 2.0, inizializzazione, controlli di integrità, esecuzione, streaming, completamento e comportamento dell'SDK dei plug-in.\u003C\u002Fp>\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fblogs.nvidia.com\u002Fblog\u002Frtx-ai-garage-gamescom-g-assist-rtx-remix\u002F\" target=\"_blank\" rel=\"noopener noreferrer\" class=\"editorjs-link-tool block border border-gray-200 dark:border-gray-700 rounded-lg p-4 transition text-gray-900 dark:text-gray-100 hover:border-primary-500 hover:bg-primary-50 dark:hover:bg-gray-900 hover:text-gray-900 dark:hover:text-gray-100\">\u003Cstrong class=\"block font-semibold\">NVIDIA Blog — Modello G-Assist leggero\u003C\u002Fstrong>\u003Cp class=\"text-sm text-gray-600 dark:text-gray-400\">Contesto ufficiale sul modello G-Assist a memoria ridotta, supporto per GPU RTX da 6 GB e hub dei plug-in della community.\u003C\u002Fp>\u003C\u002Fa>",{"time":538,"blocks":539,"version":1438},1790407989900,[540,546,554,561,568,574,579,584,589,596,601,627,632,637,642,647,678,683,688,693,698,723,730,739,744,749,754,759,764,769,774,779,784,789,794,799,804,809,815,823,828,833,838,862,867,872,877,882,903,908,913,918,923,951,956,961,966,971,977,982,987,992,997,1002,1029,1034,1039,1044,1049,1054,1059,1086,1091,1096,1101,1106,1111,1116,1140,1145,1150,1155,1160,1165,1170,1175,1180,1185,1193,1198,1203,1208,1213,1218,1223,1247,1252,1257,1262,1267,1272,1277,1282,1287,1292,1297,1302,1307,1312,1317,1352,1357,1396,1401,1411,1420,1429],{"id":541,"data":542,"type":544,"tunes":545},"3cee674645",{"text":543},"NVIDIA Project G-Assist sembra un chatbot, ma questa descrizione trascura la parte importante. È un sistema di intelligenza artificiale locale in grado di comprendere una richiesta, ispezionare lo stato supportato del PC, scegliere uno strumento o un plug-in e quindi eseguire un'azione reale come modificare le impostazioni DLSS, controllare un driver, regolare un profilo della ventola o controllare una periferica.","paragraph",{},{"id":547,"data":548,"type":552,"tunes":553},"24a1733ca8",{"body":549,"title":550,"variant":551},"\u003Cstrong>G-Assist non è semplicemente un chatbot per la tua GPU.\u003C\u002Fstrong> È un piccolo modello linguistico locale collegato a un insieme di strumenti consentiti. Il modello interpreta ciò che desideri, seleziona una funzione supportata, passa gli argomenti a quella funzione e lo strumento lato PC esegue l'azione.","Risposta diretta","info","callout",{},{"id":555,"data":556,"type":552,"tunes":560},"1fcbe512dc",{"body":557,"title":558,"variant":559},"\u003Cstrong>SLM = comprende la richiesta.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Conoscenza = spiega i concetti supportati NVIDIA\u002FPC.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Strumenti = eseguono azioni.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Plug-in = aggiungono nuovi strumenti.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Il tuo PC = l'ambiente che viene ispezionato o modificato.\u003C\u002Fstrong>","Il modello mentale più semplice","note",{},{"id":562,"data":563,"type":566,"tunes":567},"2a609230a5",{"title":564,"maxLevel":565,"minLevel":47},"Contenuti",3,"tableOfContents",{},{"id":569,"data":570,"type":572,"tunes":573},"a52f97cb62",{"text":571,"level":47},"Primo: cosa fa effettivamente il modello di IA?","header",{},{"id":575,"data":576,"type":544,"tunes":578},"1871a0d8e6",{"text":577},"G-Assist utilizza un piccolo modello linguistico locale, o SLM. Attualmente NVIDIA descrive il sistema come l'uso di un modello instruct basato su Llama con 8 miliardi di parametri.",{},{"id":580,"data":581,"type":544,"tunes":583},"cfbc6473c4",{"text":582},"Il compito principale del modello non è renderizzare grafica o modificare direttamente i registri hardware. Il suo compito è comprendere il linguaggio dell'utente, decidere quale capacità supportata corrisponde alla richiesta e preparare la chiamata a quella capacità.",{},{"id":585,"data":586,"type":544,"tunes":588},"53cadaaeb6",{"text":587},"Ad esempio, se dici \"imposta DLSS Super Resolution in modalità Prestazioni\", il modello linguistico non modifica esso stesso il DLSS. Interpreta il comando e lo indirizza alla funzione supportata che può modificare l'impostazione.",{},{"id":590,"data":591,"type":552,"tunes":595},"5d8e508019",{"body":592,"title":593,"variant":594},"Il modello di IA \u003Cstrong>decide quale strumento chiamare\u003C\u002Fstrong>. Lo strumento \u003Cstrong>fa il lavoro reale\u003C\u002Fstrong>.","La distinzione importante","success",{},{"id":597,"data":598,"type":572,"tunes":600},"9ce7e91c28",{"text":599,"level":47},"La pipeline di azione di G-Assist",{},{"id":602,"data":603,"type":625,"tunes":626},"992b5d6667",{"steps":604,"title":623,"orientation":624},[605,608,611,614,617,620],{"label":606,"description":607},"1. Fornisci una richiesta in linguaggio naturale","Ad esempio: \"Ottimizza questo gioco per le prestazioni.\"",{"label":609,"description":610},"2. L'SLM locale interpreta la richiesta","Determina l'intento dell'utente e identifica quale funzione supportata o plug-in è rilevante.",{"label":612,"description":613},"3. Il sistema sceglie uno strumento","Potrebbe essere una funzione integrata per le impostazioni grafiche, il controllo del driver, una funzione di monitoraggio o un plug-in della community.",{"label":615,"description":616},"4. Vengono estratti gli argomenti","Il modello converte la richiesta in valori strutturati come nome del gioco, modalità, profilo della ventola o impostazione DLSS.",{"label":618,"description":619},"5. Lo strumento viene eseguito","Lo strumento comunica con l'App NVIDIA, il sistema operativo, il software della periferica o un altro servizio.",{"label":621,"description":622},"6. Il risultato viene restituito","G-Assist riporta cosa è successo o restituisce dati che il modello può spiegare.","Cosa succede dopo che dai un comando a G-Assist","auto","processFlow",{},{"id":628,"data":629,"type":572,"tunes":631},"aba1e38958",{"text":630,"level":47},"Questa è chiamata di strumenti, non controllo magico del PC",{},{"id":633,"data":634,"type":544,"tunes":636},"0a7cb6107d",{"text":635},"Un modello linguistico non può controllare in modo sicuro un computer arbitrario semplicemente perché comprende l'inglese.",{},{"id":638,"data":639,"type":544,"tunes":641},"31191a478c",{"text":640},"Ha bisogno di un'interfaccia definita che specifichi quali azioni esistono, quali argomenti accettano e cosa restituisce lo strumento.",{},{"id":643,"data":644,"type":544,"tunes":646},"af3d1a846f",{"text":645},"Le attuali capacità integrate di G-Assist includono funzioni come l'ottimizzazione delle impostazioni grafiche, la modifica delle opzioni RTX supportate, il controllo o il download dei driver, la visualizzazione delle informazioni sulle prestazioni, la modifica di alcune funzionalità di alimentazione del laptop, il controllo delle funzioni del monitor supportate e l'uso di plug-in per periferiche supportate.",{},{"id":648,"data":649,"type":676,"tunes":677},"d6fd0eb144",{"rows":650,"title":667,"layout":668,"columns":669},[651,655,659,663],{"id":652,"label":653,"values":654},"understand","Comprendere \"attiva DLSS\"",[13,13],{"id":656,"label":657,"values":658},"decide","Scegliere la funzione corretta",[13,13],{"id":660,"label":661,"values":662},"change","Modificare effettivamente l'impostazione",[13,13],{"id":664,"label":665,"values":666},"explain","Spiegare il risultato",[13,13],"Modello linguistico vs strumento","table",[670,673],{"id":671,"label":672},"model","Modello linguistico",{"id":674,"label":675},"tool","Strumento \u002F plug-in","comparison",{},{"id":679,"data":680,"type":572,"tunes":682},"1537be641c",{"text":681,"level":47},"Cos'è il livello di conoscenza?",{},{"id":684,"data":685,"type":544,"tunes":687},"1db6e2e4b5",{"text":686},"G-Assist ha anche un livello di conoscenza per rispondere a domande e fornire raccomandazioni.",{},{"id":689,"data":690,"type":544,"tunes":692},"616d72b881",{"text":691},"NVIDIA afferma che la versione 0.2.1 ha introdotto un sistema di conoscenza migliorato che aiuta G-Assist a fornire raccomandazioni sulle impostazioni più accurate.",{},{"id":694,"data":695,"type":544,"tunes":697},"eb987c41e5",{"text":696},"Quel livello di conoscenza è diverso dallo stato attuale del tuo PC.",{},{"id":699,"data":700,"type":676,"tunes":722},"bf6a4f5502",{"rows":701,"title":714,"layout":668,"columns":715},[702,706,710],{"id":703,"label":704,"values":705},"gpu","GPU",[13,13],{"id":707,"label":708,"values":709},"game","Impostazioni di gioco",[13,13],{"id":711,"label":712,"values":713},"system","Prestazioni",[13,13],"Conoscenza vs stato attuale del PC",[716,719],{"id":717,"label":718},"knowledge","Conoscenza",{"id":720,"label":721},"state","Stato attuale",{},{"id":724,"data":725,"type":552,"tunes":729},"2bac13ef99",{"body":726,"title":727,"variant":728},"\u003Cstrong>La conoscenza\u003C\u002Fstrong> dice all'assistente cosa significa una funzionalità o cosa di solito è importante.\u003Cbr>\u003Cstrong>Lo stato\u003C\u002Fstrong> gli dice cosa è vero sulla tua macchina in questo momento.","Non confondere la conoscenza con lo stato","warning",{},{"id":731,"data":732,"type":737,"tunes":738},"73708d5e0d",{"url":733,"title":734,"excerpt":735,"ctaLabel":736},"https:\u002F\u002Fstajic.de\u002Fblog\u002Fwhat-is-rag-the-simplest-explanation-of-how-it-works","Cos'è il RAG? La spiegazione più semplice di come funziona","Una spiegazione in linguaggio semplice del recupero della conoscenza, dello stato, della memoria, del contesto e del modello linguistico.","Leggi la guida semplice al RAG","referralArticle",{},{"id":740,"data":741,"type":572,"tunes":743},"acbb9b7940",{"text":742,"level":47},"G-Assist utilizza il RAG?",{},{"id":745,"data":746,"type":544,"tunes":748},"ce0371e492",{"text":747},"La risposta più sicura è: G-Assist ha chiaramente un sistema di conoscenza, ma la pagina pubblica del prodotto NVIDIA non documenta ogni meccanismo di recupero interno con sufficiente dettaglio per affermare che ogni risposta di conoscenza sia specificamente prodotta dal RAG.",{},{"id":750,"data":751,"type":544,"tunes":753},"c2226e5ec5",{"text":752},"La distinzione architetturale conta comunque. Un livello di recupero può fornire conoscenze pertinenti, mentre gli strumenti di sistema forniscono lo stato attuale del PC ed eseguono azioni.",{},{"id":755,"data":756,"type":544,"tunes":758},"e5137fc2c8",{"text":757},"È la stessa separazione utilizzata in molti agenti moderni: la conoscenza è una fonte di contesto, le osservazioni in tempo reale un'altra, e l'esecuzione degli strumenti una terza.",{},{"id":760,"data":761,"type":572,"tunes":763},"059b89dedb",{"text":762,"level":47},"Perché G-Assist può funzionare offline",{},{"id":765,"data":766,"type":544,"tunes":768},"19447df6a4",{"text":767},"NVIDIA esegue il modello linguistico localmente sulla GPU GeForce RTX.",{},{"id":770,"data":771,"type":544,"tunes":773},"55aee6ada7",{"text":772},"Ciò significa che l'assistente principale non richiede un modello linguistico ospitato nel cloud per ogni prompt.",{},{"id":775,"data":776,"type":544,"tunes":778},"f265d1fd96",{"text":777},"NVIDIA afferma esplicitamente che G-Assist può funzionare offline per le sue capacità locali.",{},{"id":780,"data":781,"type":544,"tunes":783},"1dc8613200",{"text":782},"Un plug-in può comunque utilizzare Internet se quel plug-in chiama un servizio online. L'esecuzione del modello locale e l'accesso ai plug-in online sono questioni separate.",{},{"id":785,"data":786,"type":572,"tunes":788},"ee01c97a66",{"text":787,"level":47},"Il costo dell'IA locale: G-Assist utilizza la tua GPU e la VRAM",{},{"id":790,"data":791,"type":544,"tunes":793},"1784ad3fcf",{"text":792},"L'esecuzione locale offre privacy e indipendenza da un modello cloud, ma il lavoro deve essere eseguito da qualche parte.",{},{"id":795,"data":796,"type":544,"tunes":798},"1275ab759f",{"text":797},"Per G-Assist, quel \"da qualche parte\" è la stessa GPU GeForce RTX che potrebbe già stare renderizzando il tuo gioco.",{},{"id":800,"data":801,"type":544,"tunes":803},"cec86f847a",{"text":802},"NVIDIA avverte che la GPU alloca brevemente risorse di calcolo all'inferenza dell'IA quando G-Assist risponde. Se un gioco impegnativo è in esecuzione contemporaneamente, il gioco può perdere temporaneamente parte delle prestazioni di rendering mentre il modello è attivo.",{},{"id":805,"data":806,"type":544,"tunes":808},"e6ea700df6",{"text":807},"I requisiti attuali specificano anche obiettivi di VRAM libera oltre alla memoria già utilizzata dal gioco: circa 6 GB di VRAM libera per la Modalità Ragionamento e 4,5 GB per la Modalità Flash.",{},{"id":810,"data":811,"type":552,"tunes":814},"2126f74de5",{"body":812,"title":813,"variant":728},"Il gioco, Windows, il driver e altre applicazioni consumano già VRAM. Il requisito di G-Assist riguarda la \u003Cstrong>VRAM libera in aggiunta a quella già utilizzata dal carico di lavoro in esecuzione\u003C\u002Fstrong>.","8 GB di VRAM non significa che 8 GB siano disponibili per G-Assist",{},{"id":816,"data":817,"type":737,"tunes":822},"13c0dcb3f3",{"url":818,"title":819,"excerpt":820,"ctaLabel":821},"https:\u002F\u002Ffigure.rocks\u002Fit\u002Fblog\u002Fvram-usage-is-not-vram-requirement-why-a-full-memory-meter-does-not-tell-the-whole-story","L'utilizzo della VRAM non è il requisito di VRAM: perché un misuratore di memoria pieno non racconta tutta la storia","Perché la VRAM installata, l'utilizzo attuale, i budget di residenza e la reale pressione sulla memoria sono cose diverse.","Leggi la guida sulla VRAM",{},{"id":824,"data":825,"type":572,"tunes":827},"d684b2c1c8",{"text":826,"level":47},"Modalità Ragionamento vs Modalità Flash",{},{"id":829,"data":830,"type":544,"tunes":832},"3c1f2379db",{"text":831},"Le versioni attuali di G-Assist separano una Modalità Ragionamento più capace da una Modalità Flash più veloce.",{},{"id":834,"data":835,"type":544,"tunes":837},"86f50ebd33",{"text":836},"La Modalità Ragionamento è progettata per decisioni di qualità superiore e può coordinare più azioni da un singolo prompt. La Modalità Flash è ottimizzata per risposte più rapide e una domanda di risorse inferiore.",{},{"id":839,"data":840,"type":676,"tunes":861},"e7be4789db",{"rows":841,"title":826,"layout":668,"columns":854},[842,846,850],{"id":843,"label":844,"values":845},"goal","Obiettivo principale",[13,13],{"id":847,"label":848,"values":849},"vram","VRAM libera consigliata",[13,13],{"id":851,"label":852,"values":853},"use","Ideale per",[13,13],[855,858],{"id":856,"label":857},"reasoning","Modalità Ragionamento",{"id":859,"label":860},"flash","Modalità Flash",{},{"id":863,"data":864,"type":572,"tunes":866},"cef1bcf553",{"text":865,"level":47},"Cosa aggiungono effettivamente i plug-in",{},{"id":868,"data":869,"type":544,"tunes":871},"d380d5e28b",{"text":870},"Un plug-in non sostituisce il modello linguistico. Fornisce al modello una nuova azione che è autorizzato a chiamare.",{},{"id":873,"data":874,"type":544,"tunes":876},"434979ebda",{"text":875},"Il plug-in definisce funzioni, descrizioni e parametri. G-Assist legge quelle descrizioni, abbina una richiesta dell'utente alla funzione appropriata e le invia argomenti strutturati.",{},{"id":878,"data":879,"type":544,"tunes":881},"21ebe69c79",{"text":880},"Ciò consente all'assistente di crescere oltre le funzioni integrate di NVIDIA.",{},{"id":883,"data":884,"type":625,"tunes":902},"d0ba7ef284",{"steps":885,"title":901,"orientation":624},[886,889,892,895,898],{"label":887,"description":888},"1. Il plug-in dichiara una funzione","Ad esempio: set_keyboard_color(color).",{"label":890,"description":891},"2. Il manifest descrive la funzione","Il manifest indica a G-Assist cosa fa la funzione e quali parametri richiede.",{"label":893,"description":894},"3. L'utente chiede in modo naturale","Ad esempio: “Rendi la mia tastiera verde.”",{"label":896,"description":897},"4. L'SLM seleziona la funzione","Il modello mappa la richiesta sulla funzione del plug-in ed estrae verde come parametro.",{"label":899,"description":900},"5. Il plug-in esegue","Il plug-in comunica con il software della periferica o il servizio esterno.","Come funziona un plug-in di G-Assist",{},{"id":904,"data":905,"type":572,"tunes":907},"1dc857ce2f",{"text":906,"level":47},"G-Assist Protocol V2 è JSON-RPC 2.0",{},{"id":909,"data":910,"type":544,"tunes":912},"02bdb0566d",{"text":911},"L'attuale repository pubblico di plug-in di NVIDIA utilizza il Protocollo V2.",{},{"id":914,"data":915,"type":544,"tunes":917},"f82da294cf",{"text":916},"Il Protocollo V2 utilizza JSON-RPC 2.0 con messaggi con prefisso di lunghezza tra il motore G-Assist e i plug-in.",{},{"id":919,"data":920,"type":544,"tunes":922},"530c3cf9b9",{"text":921},"Il motore può inizializzare un plug-in, verificarne lo stato di salute, eseguire una funzione, inviare input dell'utente e spegnerlo. I plug-in possono restituire risultati, trasmettere in streaming il progresso o segnalare errori.",{},{"id":924,"data":925,"type":676,"tunes":950},"2ce3fa5d75",{"rows":926,"title":942,"layout":668,"columns":943},[927,930,933,936,939],{"id":928,"label":928,"values":929},"initialize",[13,13],{"id":931,"label":931,"values":932},"ping",[13,13],{"id":934,"label":934,"values":935},"execute",[13,13],{"id":937,"label":937,"values":938},"stream",[13,13],{"id":940,"label":940,"values":941},"complete",[13,13],"I messaggi importanti del Protocollo V2",[944,947],{"id":945,"label":946},"direction","Direzione",{"id":948,"label":949},"purpose","Scopo",{},{"id":952,"data":953,"type":572,"tunes":955},"304fbd9944",{"text":954,"level":47},"Dove entra in gioco MCP",{},{"id":957,"data":958,"type":544,"tunes":960},"fae73881e4",{"text":959},"Il protocollo plug-in proprietario di G-Assist non è MCP. Il suo attuale sistema pubblico di plug-in utilizza JSON-RPC 2.0.",{},{"id":962,"data":963,"type":544,"tunes":965},"551d11710a",{"text":964},"Tuttavia, un plug-in di G-Assist può connettersi a un server MCP.",{},{"id":967,"data":968,"type":544,"tunes":970},"0537fb222a",{"text":969},"La versione attuale 0.2.2 di NVIDIA include un'integrazione Elgato che può invocare azioni esposte tramite il server MCP di Elgato Stream Deck.",{},{"id":972,"data":973,"type":552,"tunes":976},"760a86ad19",{"body":974,"title":975,"variant":594},"\u003Cstrong>G-Assist ↔ il suo plug-in:\u003C\u002Fstrong> NVIDIA Protocol V2 \u002F JSON-RPC 2.0.\u003Cbr>\u003Cstrong>Plug-in ↔ un altro ecosistema di strumenti:\u003C\u002Fstrong> può utilizzare MCP quando tale integrazione lo supporta.","Distinzione importante tra protocolli",{},{"id":978,"data":979,"type":572,"tunes":981},"bd182f72b0",{"text":980,"level":47},"Perché questo conta al di là delle luci RGB",{},{"id":983,"data":984,"type":544,"tunes":986},"d072506ce2",{"text":985},"L'architettura dei plug-in trasforma G-Assist da un assistente fisso a un router locale di strumenti.",{},{"id":988,"data":989,"type":544,"tunes":991},"2876e067dc",{"text":990},"Lo stesso schema può connettere un SLM a strumenti di monitoraggio, periferiche, API, sistemi di automazione, applicazioni locali o servizi esterni.",{},{"id":993,"data":994,"type":544,"tunes":996},"37689640e9",{"text":995},"L'unità architetturale importante non è quindi la finestra di chat. È il confine tra l'intento in linguaggio naturale e l'esecuzione strutturata degli strumenti.",{},{"id":998,"data":999,"type":572,"tunes":1001},"550fbb42d4",{"text":1000,"level":47},"Lo stack dell'agente locale",{},{"id":1003,"data":1004,"type":625,"tunes":1028},"8518dbf820",{"steps":1005,"title":1027,"orientation":624},[1006,1009,1012,1015,1018,1021,1024],{"label":1007,"description":1008},"1. Intento dell'utente","Comando in linguaggio naturale o vocale.",{"label":1010,"description":1011},"2. SLM locale","Comprende la richiesta e sceglie una capacità.",{"label":1013,"description":1014},"3. Conoscenza \u002F contesto","Fornisce conoscenze sul prodotto, raccomandazioni o informazioni necessarie per la decisione.",{"label":1016,"description":1017},"4. Stato del sistema in tempo reale","Fornisce informazioni attuali su hardware, driver, prestazioni o configurazione quando supportato.",{"label":1019,"description":1020},"5. Selezione dello strumento","Viene scelta una funzione integrata o un plug-in.",{"label":1022,"description":1023},"6. Esecuzione strutturata","La funzione riceve argomenti ed esegue l'azione reale.",{"label":1025,"description":1026},"7. Verifica del risultato","Lo strumento restituisce stato o dati e il modello spiega cosa è successo.","Un modo utile di pensare a G-Assist",{},{"id":1030,"data":1031,"type":572,"tunes":1033},"6c976db763",{"text":1032,"level":47},"Perché i confini degli strumenti sono una caratteristica di sicurezza",{},{"id":1035,"data":1036,"type":544,"tunes":1038},"ba65a3b467",{"text":1037},"Un assistente AI in grado di eseguire comandi arbitrari del sistema operativo sarebbe molto più potente, ma anche molto più difficile da limitare.",{},{"id":1040,"data":1041,"type":544,"tunes":1043},"a932df9663",{"text":1042},"G-Assist invece espone funzioni definite con parametri noti.",{},{"id":1045,"data":1046,"type":544,"tunes":1048},"7d1d45c83d",{"text":1047},"Ciò significa che il modello può eseguire solo azioni rese disponibili dall'insieme di funzioni integrate o dai plug-in installati.",{},{"id":1050,"data":1051,"type":544,"tunes":1053},"10460fda21",{"text":1052},"Questo non elimina tutti i rischi, specialmente con plug-in di terze parti, ma crea un confine di autorizzazione e capacità più chiaro rispetto all'accesso illimitato alla shell.",{},{"id":1055,"data":1056,"type":572,"tunes":1058},"25049448ea",{"text":1057,"level":47},"Il confine tra autorità e strumenti",{},{"id":1060,"data":1061,"type":676,"tunes":1085},"d3ff568795",{"rows":1062,"title":1078,"layout":668,"columns":1079},[1063,1066,1070,1074],{"id":703,"label":1064,"values":1065},"Ottimizzazione GPU",[13,13],{"id":1067,"label":1068,"values":1069},"files","File",[13,13],{"id":1071,"label":1072,"values":1073},"web","Internet",[13,13],{"id":1075,"label":1076,"values":1077},"device","Controllo periferiche",[13,13],"Cosa l'assistente può capire vs cosa è autorizzato a fare",[1080,1082],{"id":652,"label":1081},"Il modello può capire",{"id":1083,"label":1084},"authority","Autorità dello strumento",{},{"id":1087,"data":1088,"type":572,"tunes":1090},"8fd8e35c51",{"text":1089,"level":47},"Perché G-Assist può ridurre temporaneamente le prestazioni di gioco",{},{"id":1092,"data":1093,"type":544,"tunes":1095},"f75234546f",{"text":1094},"L'architettura con modello locale ha una conseguenza diretta: l'IA e il gioco possono competere per la stessa GPU.",{},{"id":1097,"data":1098,"type":544,"tunes":1100},"28bc054afa",{"text":1099},"NVIDIA avverte esplicitamente che la frequenza di rendering o la velocità di inferenza possono calare brevemente mentre G-Assist elabora una richiesta durante un carico di lavoro intenso sulla GPU.",{},{"id":1102,"data":1103,"type":544,"tunes":1105},"0823573513",{"text":1104},"Una volta terminata l'inferenza, queste risorse GPU tornano al gioco.",{},{"id":1107,"data":1108,"type":544,"tunes":1110},"905eed843d",{"text":1109},"Questo è diverso da un assistente cloud, dove la maggior parte dell'inferenza del modello avviene su un server remoto e non consuma la GPU da gaming.",{},{"id":1112,"data":1113,"type":572,"tunes":1115},"839c0e3988",{"text":1114,"level":47},"Il test delle risorse dell'assistente locale",{},{"id":1117,"data":1118,"type":625,"tunes":1139},"affa0ee1b3",{"steps":1119,"title":1138,"orientation":624},[1120,1123,1126,1129,1132,1135],{"label":1121,"description":1122},"1. Controlla la VRAM installata","Il requisito minimo attuale di G-Assist è una GPU RTX con almeno 6 GB di VRAM.",{"label":1124,"description":1125},"2. Controlla la VRAM libera durante il gioco effettivo","La capacità installata non è la stessa cosa della capacità libera.",{"label":1127,"description":1128},"3. Scegli in modo appropriato la modalità Reasoning o Flash","Usa la modalità più leggera quando la pressione sulle risorse conta più del ragionamento approfondito.",{"label":1130,"description":1131},"4. Misura i cali di frame rate durante l'inferenza","Osserva il gioco mentre chiedi a G-Assist di eseguire attività.",{"label":1133,"description":1134},"5. Ispeziona l'autorità degli strumenti","Sappi esattamente quali funzioni integrate e plug-in possono modificare il tuo sistema.",{"label":1136,"description":1137},"6. Tratta i plug-in di terze parti come software","Esamina il loro codice sorgente, i permessi, l'accesso alla rete e le credenziali memorizzate.","Come giudicare se un assistente da gaming locale è adatto al tuo PC",{},{"id":1141,"data":1142,"type":572,"tunes":1144},"ca52c48d2e",{"text":1143,"level":47},"Perché i plug-in meritano lo stesso esame di qualsiasi altro software",{},{"id":1146,"data":1147,"type":544,"tunes":1149},"8e6a760529",{"text":1148},"Un plug-in può collegare l'assistente ad API, applicazioni periferiche e servizi online.",{},{"id":1151,"data":1152,"type":544,"tunes":1154},"be793240e1",{"text":1153},"Ciò significa che un plug-in può gestire valori di configurazione, credenziali o richieste esterne a seconda di ciò per cui è stato creato.",{},{"id":1156,"data":1157,"type":544,"tunes":1159},"3c6c4c9aaf",{"text":1158},"Il repository di NVIDIA fornisce esplicitamente una posizione config.json per le impostazioni dei plug-in e avverte gli sviluppatori di non commettere credenziali.",{},{"id":1161,"data":1162,"type":544,"tunes":1164},"03413f935a",{"text":1163},"La domanda di sicurezza corretta quindi non è solo \"G-Assist è locale?\" ma anche \"A cosa si connette ogni plug-in installato?\"",{},{"id":1166,"data":1167,"type":572,"tunes":1169},"f473162e86",{"text":1168,"level":47},"G-Assist è più vicino a un agente che a un chatbot",{},{"id":1171,"data":1172,"type":544,"tunes":1174},"59dd3df9c2",{"text":1173},"Un chatbot produce principalmente linguaggio.",{},{"id":1176,"data":1177,"type":544,"tunes":1179},"188cb4bb40",{"text":1178},"Un agente interpreta un obiettivo, osserva le informazioni rilevanti, sceglie un'azione, chiama uno strumento e valuta il risultato.",{},{"id":1181,"data":1182,"type":544,"tunes":1184},"117d1032f1",{"text":1183},"G-Assist ora corrisponde molto più da vicino a questa seconda descrizione perché può coordinare più azioni, ispezionare lo stato supportato del PC e invocare strumenti reali.",{},{"id":1186,"data":1187,"type":737,"tunes":1192},"ef132fc518",{"url":1188,"title":1189,"excerpt":1190,"ctaLabel":1191},"https:\u002F\u002Ffigure.rocks\u002Fit\u002Fblog\u002Fpubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning","PUBG Ally mostra perché i compagni di squadra IA hanno bisogno di due cervelli: riflessi rapidi e ragionamento lento","Un esempio di architettura di un agente di gioco che mostra la separazione tra ragionamento, stato in tempo reale, strumenti ed esecuzione deterministica.","Leggi la guida all'architettura di PUBG Ally",{},{"id":1194,"data":1195,"type":572,"tunes":1197},"9f8fa308a5",{"text":1196,"level":47},"Ciò che G-Assist ancora non è",{},{"id":1199,"data":1200,"type":544,"tunes":1202},"f5f24e8aa3",{"text":1201},"NVIDIA descrive esplicitamente G-Assist come un assistente locale specializzato, non come un'IA conversazionale generica.",{},{"id":1204,"data":1205,"type":544,"tunes":1207},"e4d187593f",{"text":1206},"Il suo valore deriva dalla comprensione di un insieme mirato di attività relative a PC e gaming e dalla disponibilità di strumenti collegati a tali attività.",{},{"id":1209,"data":1210,"type":544,"tunes":1212},"0c1b7f8948",{"text":1211},"Questa focalizzazione è importante perché un modello locale più piccolo può essere utile quando il sistema circostante gli fornisce strumenti potenti e confini chiari.",{},{"id":1214,"data":1215,"type":572,"tunes":1217},"79a5920e77",{"text":1216,"level":47},"Cosa è cambiato nelle versioni attuali?",{},{"id":1219,"data":1220,"type":544,"tunes":1222},"e78d96ef6c",{"text":1221},"La cronologia delle versioni pubbliche attuali mostra G-Assist in costante evoluzione verso un agente locale più capace.",{},{"id":1224,"data":1225,"type":668,"tunes":1246},"87dd1d3d3c",{"content":1226,"stretched":1245,"withHeadings":15},[1227,1230,1233,1236,1239,1242],[1228,1229],"Versione","Modifica importante",[1231,1232],"0.1.17","Modello più leggero, tutte le GPU RTX con 6 GB+ di VRAM, plug-in della community",[1234,1235],"0.1.18","Ottimizzazione per laptop, controlli BatteryBoost e WhisperMode",[1237,1238],"0.2","Modalità di ragionamento, modalità Flash, prompt multi-azione, nuovi controlli dei dispositivi",[1240,1241],"0.2.1","Sistema di conoscenza migliorato, raccomandazioni migliori, controlli delle funzionalità RTX",[1243,1244],"0.2.2","Integrazione con Elgato Stream Deck tramite un server MCP",false,{},{"id":1248,"data":1249,"type":572,"tunes":1251},"09bde21a8d",{"text":1250,"level":47},"Cosa potrebbe cambiare questa risposta?",{},{"id":1253,"data":1254,"type":544,"tunes":1256},"b0e7ca01a4",{"text":1255},"G-Assist è ancora sperimentale e la sua architettura è in evoluzione.",{},{"id":1258,"data":1259,"type":544,"tunes":1261},"537568c224",{"text":1260},"Le dimensioni del modello, i requisiti di VRAM, il set di strumenti, il protocollo dei plug-in e il supporto hardware possono tutti cambiare nelle versioni future.",{},{"id":1263,"data":1264,"type":544,"tunes":1266},"fe24516c11",{"text":1265},"Una versione futura potrebbe anche spostare parte dell'inferenza su una NPU o introdurre un'integrazione MCP più ampia, ma non bisogna presumerlo finché NVIDIA non lo documenta.",{},{"id":1268,"data":1269,"type":572,"tunes":1271},"0e31e2d54d",{"text":1270,"level":47},"Limitazioni",{},{"id":1273,"data":1274,"type":544,"tunes":1276},"a7881e11e1",{"text":1275},"Questo articolo descrive la documentazione pubblica del prodotto G-Assist di NVIDIA e l'architettura pubblica dei plug-in a partire da settembre 2026.",{},{"id":1278,"data":1279,"type":544,"tunes":1281},"71ebc16fda",{"text":1280},"NVIDIA non documenta pubblicamente ogni dettaglio interno della sua pipeline di conoscenza e raccomandazione, quindi questo articolo non afferma che ogni risposta di conoscenza utilizzi RAG o qualsiasi altra specifica implementazione di recupero.",{},{"id":1283,"data":1284,"type":544,"tunes":1286},"add780d6ba",{"text":1285},"I plug-in di terze parti possono avere comportamenti e accesso alla rete al di là delle funzioni integrate di NVIDIA, quindi ogni plug-in dovrebbe essere valutato separatamente.",{},{"id":1288,"data":1289,"type":572,"tunes":1291},"f7a38af5be",{"text":1290,"level":47},"Conclusione",{},{"id":1293,"data":1294,"type":544,"tunes":1296},"f1308f3e80",{"text":1295},"Il modo più semplice per comprendere Project G-Assist è smettere di pensarlo come un chatbot.",{},{"id":1298,"data":1299,"type":544,"tunes":1301},"b102a861bb",{"text":1300},"Il SLM locale interpreta la tua richiesta. La conoscenza lo aiuta a comprendere il problema. Le informazioni di sistema in tempo reale gli dicono cosa è vero sul tuo PC. Una funzione integrata o un plug-in definisce ciò che gli è effettivamente consentito fare. Lo strumento esegue l'azione e restituisce il risultato.",{},{"id":1303,"data":1304,"type":544,"tunes":1306},"da805fabf0",{"text":1305},"Questa è un'architettura di agente locale.",{},{"id":1308,"data":1309,"type":544,"tunes":1311},"675aecee06",{"text":1310},"La sua idea più forte non è che un modello da 8 miliardi di parametri possa parlare della tua GPU. È che un modello locale relativamente piccolo può diventare utile quando è collegato a strumenti ben definiti, allo stato corrente e a un confine d'azione controllato.",{},{"id":1313,"data":1314,"type":572,"tunes":1316},"0354b8daaf",{"text":1315,"level":47},"FAQ",{},{"id":1318,"data":1319,"type":1350,"tunes":1351},"e75bc04532",{"items":1320,"title":1349},[1321,1325,1329,1333,1337,1341,1345],{"id":1322,"answer":1323,"question":1324},"faq1","No. Il suo modello linguistico principale viene eseguito localmente sulla GPU GeForce RTX e può funzionare offline per le funzioni locali supportate.","G-Assist è un chatbot cloud?",{"id":1326,"answer":1327,"question":1328},"faq2","Attualmente NVIDIA lo descrive come un modello instruct locale basato su Llama con 8 miliardi di parametri.","Quale modello utilizza G-Assist?",{"id":1330,"answer":1331,"question":1332},"faq3","No. Il modello seleziona una funzione integrata o un plug-in supportato, e quello strumento esegue la modifica effettiva.","Il modello AI modifica direttamente le impostazioni della mia GPU?",{"id":1334,"answer":1335,"question":1336},"faq4","Sì. NVIDIA consiglia VRAM libera aggiuntiva per l'assistente e avverte che l'inferenza può ridurre brevemente le prestazioni di rendering del gioco.","G-Assist utilizza VRAM durante il gaming?",{"id":1338,"answer":1339,"question":1340},"faq5","Non direttamente. L'attuale protocollo plug-in di G-Assist utilizza JSON-RPC 2.0, sebbene un plug-in possa connettersi a un server MCP.","I plug-in di G-Assist sono plug-in MCP?",{"id":1342,"answer":1343,"question":1344},"faq6","Il suo assistente locale può farlo, ma i singoli plug-in potrebbero comunque richiedere l'accesso a Internet se chiamano servizi online.","G-Assist può funzionare offline?",{"id":1346,"answer":1347,"question":1348},"faq7","NVIDIA lo descrive come un assistente specializzato per PC e gaming piuttosto che un modello conversazionale generico e ampio.","G-Assist è un assistente AI generico?","NVIDIA Project G-Assist in parole semplici","faq",{},{"id":1353,"data":1354,"type":572,"tunes":1356},"8733f298cd",{"text":1355,"level":47},"Glossario",{},{"id":1358,"data":1359,"type":1394,"tunes":1395},"407257a6d1",{"title":1360,"entries":1361},"Termini chiave di G-Assist",[1362,1366,1370,1374,1378,1382,1386,1390],{"term":1363,"anchor":1364,"definition":1365},"SLM","slm","Small Language Model, un modello linguistico compatto progettato per essere eseguito localmente con requisiti hardware inferiori rispetto ai grandi modelli cloud.",{"term":1367,"anchor":1368,"definition":1369},"Tool calling","tool-calling","Il processo in cui un modello linguistico sceglie una funzione definita e fornisce argomenti strutturati affinché un altro componente possa eseguire un'azione.",{"term":1371,"anchor":1372,"definition":1373},"Plug-in","plugin","Un'estensione che espone funzioni o integrazioni aggiuntive a G-Assist.",{"term":1375,"anchor":1376,"definition":1377},"JSON-RPC 2.0","json-rpc","Il protocollo di messaggistica strutturato utilizzato dall'attuale sistema di plug-in G-Assist Protocol V2.",{"term":1379,"anchor":1380,"definition":1381},"MCP","mcp","Model Context Protocol, un protocollo separato di interoperabilità di strumenti e contesto che alcune integrazioni esterne possono esporre.",{"term":1383,"anchor":1384,"definition":1385},"Tool-Authority Boundary","tool-authority-boundary","Un modello Figure Rocks che separa ciò che un modello AI può comprendere da ciò che i suoi strumenti collegati gli consentono effettivamente di fare.",{"term":1387,"anchor":1388,"definition":1389},"Local Agent Stack","local-agent-stack","Un modello Figure Rocks che combina intento dell'utente, SLM locale, conoscenza, stato in tempo reale, selezione degli strumenti, esecuzione e verifica dei risultati.",{"term":1391,"anchor":1392,"definition":1393},"Local Assistant Resource Test","local-assistant-resource-test","Un flusso di lavoro Figure Rocks per valutare VRAM, costo di inferenza, autorizzazioni degli strumenti e rischio dei plug-in prima di utilizzare un assistente di gaming locale.","glossary",{},{"id":1397,"data":1398,"type":572,"tunes":1400},"3ab856f2b4",{"text":1399,"level":47},"Fonti primarie",{},{"id":1402,"data":1403,"type":1409,"tunes":1410},"367d2e3548",{"link":1404,"meta":1405},"https:\u002F\u002Fwww.nvidia.com\u002Fen-us\u002Fsoftware\u002Fnvidia-app\u002Fg-assist\u002F",{"image":1406,"title":1407,"description":1408},{"url":13},"NVIDIA — Project G-Assist","Pagina ufficiale attuale del prodotto che copre il modello locale, le funzioni supportate, le modalità Reasoning e Flash, i requisiti VRAM, i controlli RTX, i plug-in e l'integrazione Elgato basata su MCP versione 0.2.2.","linkTool",{},{"id":1412,"data":1413,"type":1409,"tunes":1419},"5641b514c0",{"link":1414,"meta":1415},"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FG-Assist",{"image":1416,"title":1417,"description":1418},{"url":13},"NVIDIA — G-Assist GitHub","Repository pubblico ufficiale dei plug-in che documenta l'architettura dei moduli di G-Assist, il rilevamento dei plug-in e il Protocol V2.",{},{"id":1421,"data":1422,"type":1409,"tunes":1428},"22a5b77a1b",{"link":1423,"meta":1424},"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FG-Assist\u002Fblob\u002Fmain\u002FPLUGIN_MIGRATION_GUIDE_V2.md",{"image":1425,"title":1426,"description":1427},{"url":13},"NVIDIA — Guida alla migrazione a G-Assist Protocol V2","Documentazione ufficiale del protocollo che copre JSON-RPC 2.0, inizializzazione, controlli di integrità, esecuzione, streaming, completamento e comportamento dell'SDK dei plug-in.",{},{"id":1430,"data":1431,"type":1409,"tunes":1437},"cc3301d997",{"link":1432,"meta":1433},"https:\u002F\u002Fblogs.nvidia.com\u002Fblog\u002Frtx-ai-garage-gamescom-g-assist-rtx-remix\u002F",{"image":1434,"title":1435,"description":1436},{"url":13},"NVIDIA Blog — Modello G-Assist leggero","Contesto ufficiale sul modello G-Assist a memoria ridotta, supporto per GPU RTX da 6 GB e hub dei plug-in della community.",{},"2.31","NVIDIA Project G-Assist sembra un chatbot, ma la sua vera architettura è più simile a un agente AI locale. Un piccolo modello linguistico interpreta la tua richiesta, lo stato del sistema fornisce le informazioni attuali del PC, gli strumenti eseguono azioni reali e i plug-in estendono ciò che l'assistente è autorizzato a controllare.","\u002Fuploads\u002F2026\u002F09\u002Fnvidia-g-assist-is-not-just-a-chatbot-how-its-local-slm-tools-plug-ins-and-mcp-actually-work-1790407739731-smbdnv.webp","nvidia-g-assist-is-not-just-a-chatbot-how-its-local-slm-tools-plug-ins-and-mcp-actually-work-1790407739731-smbdnv","PUBLISHED","2026-09-26T03:27:00.000Z","2026-09-26T07:27:18.273Z","2026-09-26T07:34:28.920Z",{"en":1447,"de":1448,"sr":1449,"es":1450,"fr":1451,"it":1452,"ru":1453,"zh":1454},"\u002Fblog\u002Fnvidia-g-assist-is-not-just-a-chatbot-how-its-local-slm-tools-plug-ins-and-mcp-actually-work","\u002Fde\u002Fblog\u002Fnvidia-g-assist-is-not-just-a-chatbot-how-its-local-slm-tools-plug-ins-and-mcp-actually-work","\u002Fsr\u002Fblog\u002Fnvidia-g-assist-is-not-just-a-chatbot-how-its-local-slm-tools-plug-ins-and-mcp-actually-work","\u002Fes\u002Fblog\u002Fnvidia-g-assist-is-not-just-a-chatbot-how-its-local-slm-tools-plug-ins-and-mcp-actually-work","\u002Ffr\u002Fblog\u002Fnvidia-g-assist-is-not-just-a-chatbot-how-its-local-slm-tools-plug-ins-and-mcp-actually-work","\u002Fit\u002Fblog\u002Fnvidia-g-assist-is-not-just-a-chatbot-how-its-local-slm-tools-plug-ins-and-mcp-actually-work","\u002Fru\u002Fblog\u002Fnvidia-g-assist-is-not-just-a-chatbot-how-its-local-slm-tools-plug-ins-and-mcp-actually-work","\u002Fzh\u002Fblog\u002Fnvidia-g-assist-is-not-just-a-chatbot-how-its-local-slm-tools-plug-ins-and-mcp-actually-work",[1456,1460,1464,1467,1471],{"id":1457,"name":1458,"slug":1459},171,"GPU e driver","gpus-and-drivers",{"id":1461,"name":1462,"slug":1463},67,"Windows e driver","windows-and-drivers",{"id":1465,"name":708,"slug":1466},68,"in-game-settings",{"id":1468,"name":1469,"slug":1470},69,"Impostazioni display","display-settings",{"id":1472,"name":1473,"slug":1474},197,"Prima le impostazioni migliori","best-settings-first",{"id":283,"login":1476,"email":1477,"displayName":1478},"aleksandar","aleksandar@stajic.de","Aleksandar Stajic",[1480,2186],{"lang":8,"title":1481,"content":1482,"contentJson":1483,"excerpt":2185},"NVIDIA G-Assist Is Not Just a Chatbot: How Its Local SLM, Tools, Plug-ins and MCP Actually Work","{\"time\":1790407740910,\"blocks\":[{\"id\":\"3cee674645\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA Project G-Assist looks like a chatbot, but that description misses the important part. It is a local AI system that can understand a request, inspect supported PC state, choose a tool or plug-in, and then perform a real action such as changing DLSS settings, checking a driver, adjusting a fan profile or controlling a peripheral.\"},\"tunes\":{}},{\"id\":\"24a1733ca8\",\"type\":\"callout\",\"data\":{\"variant\":\"info\",\"title\":\"Direct answer\",\"body\":\"\u003Cstrong>G-Assist is not simply a chatbot for your GPU.\u003C\u002Fstrong> It is a local small language model connected to a set of allowed tools. The model interprets what you want, selects a supported function, passes arguments to that function, and the PC-side tool performs the action.\"},\"tunes\":{}},{\"id\":\"1fcbe512dc\",\"type\":\"callout\",\"data\":{\"variant\":\"note\",\"title\":\"The easiest mental model\",\"body\":\"\u003Cstrong>SLM = understands the request.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Knowledge = explains supported NVIDIA\u002FPC concepts.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Tools = perform actions.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Plug-ins = add new tools.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Your PC = the environment being inspected or changed.\u003C\u002Fstrong>\"},\"tunes\":{}},{\"id\":\"2a609230a5\",\"type\":\"tableOfContents\",\"data\":{\"title\":\"Contents\",\"minLevel\":2,\"maxLevel\":3},\"tunes\":{}},{\"id\":\"a52f97cb62\",\"type\":\"header\",\"data\":{\"text\":\"First: what is the AI model actually doing?\",\"level\":2},\"tunes\":{}},{\"id\":\"1871a0d8e6\",\"type\":\"paragraph\",\"data\":{\"text\":\"G-Assist uses a local small language model, or SLM. NVIDIA currently describes the system as using a Llama-based 8-billion-parameter instruct model.\"},\"tunes\":{}},{\"id\":\"cfbc6473c4\",\"type\":\"paragraph\",\"data\":{\"text\":\"The model's main job is not to render graphics or directly change hardware registers. Its job is to understand the user's language, decide which supported capability matches the request, and prepare the call to that capability.\"},\"tunes\":{}},{\"id\":\"53cadaaeb6\",\"type\":\"paragraph\",\"data\":{\"text\":\"For example, if you say “set DLSS Super Resolution to Performance Mode,” the language model does not itself modify DLSS. It interprets the command and routes it to the supported function that can change the setting.\"},\"tunes\":{}},{\"id\":\"5d8e508019\",\"type\":\"callout\",\"data\":{\"variant\":\"success\",\"title\":\"The important distinction\",\"body\":\"The AI model \u003Cstrong>decides what tool to call\u003C\u002Fstrong>. The tool \u003Cstrong>does the real work\u003C\u002Fstrong>.\"},\"tunes\":{}},{\"id\":\"9ce7e91c28\",\"type\":\"header\",\"data\":{\"text\":\"The G-Assist action pipeline\",\"level\":2},\"tunes\":{}},{\"id\":\"992b5d6667\",\"type\":\"processFlow\",\"data\":{\"title\":\"What happens after you give G-Assist a command\",\"orientation\":\"auto\",\"steps\":[{\"label\":\"1. You give a natural-language request\",\"description\":\"For example: “Optimize this game for performance.”\"},{\"label\":\"2. The local SLM interprets the request\",\"description\":\"It determines the user's intent and identifies which supported function or plug-in is relevant.\"},{\"label\":\"3. The system chooses a tool\",\"description\":\"That could be a built-in graphics-setting function, driver check, monitoring function or community plug-in.\"},{\"label\":\"4. Arguments are extracted\",\"description\":\"The model converts the request into structured values such as game name, mode, fan profile or DLSS setting.\"},{\"label\":\"5. The tool executes\",\"description\":\"The tool talks to the NVIDIA App, operating system, peripheral software or another service.\"},{\"label\":\"6. The result is returned\",\"description\":\"G-Assist reports what happened, or returns data that the model can explain.\"}]},\"tunes\":{}},{\"id\":\"aba1e38958\",\"type\":\"header\",\"data\":{\"text\":\"This is tool calling, not magic PC control\",\"level\":2},\"tunes\":{}},{\"id\":\"0a7cb6107d\",\"type\":\"paragraph\",\"data\":{\"text\":\"A language model cannot safely control an arbitrary computer simply because it understands English.\"},\"tunes\":{}},{\"id\":\"31191a478c\",\"type\":\"paragraph\",\"data\":{\"text\":\"It needs a defined interface that says which actions exist, which arguments they accept and what the tool returns.\"},\"tunes\":{}},{\"id\":\"af3d1a846f\",\"type\":\"paragraph\",\"data\":{\"text\":\"G-Assist's current built-in capabilities include functions such as optimizing graphics settings, changing supported RTX options, checking or downloading drivers, showing performance information, changing some laptop power features, controlling supported monitor functions and using supported peripheral plug-ins.\"},\"tunes\":{}},{\"id\":\"d6fd0eb144\",\"type\":\"comparison\",\"data\":{\"title\":\"Language model vs tool\",\"layout\":\"table\",\"columns\":[{\"id\":\"model\",\"label\":\"Language model\"},{\"id\":\"tool\",\"label\":\"Tool \u002F plug-in\"}],\"rows\":[{\"id\":\"understand\",\"label\":\"Understand “turn on DLSS”\",\"values\":[\"\",\"\"]},{\"id\":\"decide\",\"label\":\"Choose the correct function\",\"values\":[\"\",\"\"]},{\"id\":\"change\",\"label\":\"Actually change the setting\",\"values\":[\"\",\"\"]},{\"id\":\"explain\",\"label\":\"Explain the result\",\"values\":[\"\",\"\"]}]},\"tunes\":{}},{\"id\":\"1537be641c\",\"type\":\"header\",\"data\":{\"text\":\"What is the knowledge layer?\",\"level\":2},\"tunes\":{}},{\"id\":\"1db6e2e4b5\",\"type\":\"paragraph\",\"data\":{\"text\":\"G-Assist also has a knowledge layer for answering questions and making recommendations.\"},\"tunes\":{}},{\"id\":\"616d72b881\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA says version 0.2.1 introduced an improved knowledge system that helps G-Assist make more accurate settings recommendations.\"},\"tunes\":{}},{\"id\":\"eb987c41e5\",\"type\":\"paragraph\",\"data\":{\"text\":\"That knowledge layer is different from the live state of your PC.\"},\"tunes\":{}},{\"id\":\"bf6a4f5502\",\"type\":\"comparison\",\"data\":{\"title\":\"Knowledge vs live PC state\",\"layout\":\"table\",\"columns\":[{\"id\":\"knowledge\",\"label\":\"Knowledge\"},{\"id\":\"state\",\"label\":\"Live state\"}],\"rows\":[{\"id\":\"gpu\",\"label\":\"GPU\",\"values\":[\"\",\"\"]},{\"id\":\"game\",\"label\":\"Game settings\",\"values\":[\"\",\"\"]},{\"id\":\"system\",\"label\":\"Performance\",\"values\":[\"\",\"\"]}]},\"tunes\":{}},{\"id\":\"2bac13ef99\",\"type\":\"callout\",\"data\":{\"variant\":\"warning\",\"title\":\"Do not mix knowledge with state\",\"body\":\"\u003Cstrong>Knowledge\u003C\u002Fstrong> tells the assistant what a feature means or what usually matters.\u003Cbr>\u003Cstrong>State\u003C\u002Fstrong> tells it what is true on your machine right now.\"},\"tunes\":{}},{\"id\":\"73708d5e0d\",\"type\":\"referralArticle\",\"data\":{\"url\":\"https:\u002F\u002Fstajic.de\u002Fblog\u002Fwhat-is-rag-the-simplest-explanation-of-how-it-works\",\"title\":\"What Is RAG? The Simplest Explanation of How It Works\",\"excerpt\":\"A plain-English explanation of knowledge retrieval, state, memory, context and the language model.\",\"ctaLabel\":\"Read the simple RAG guide\"},\"tunes\":{}},{\"id\":\"acbb9b7940\",\"type\":\"header\",\"data\":{\"text\":\"Does G-Assist use RAG?\",\"level\":2},\"tunes\":{}},{\"id\":\"ce0371e492\",\"type\":\"paragraph\",\"data\":{\"text\":\"The safest answer is: G-Assist clearly has a knowledge system, but NVIDIA's public product page does not document every internal retrieval mechanism in enough detail to say that every knowledge answer is specifically produced by RAG.\"},\"tunes\":{}},{\"id\":\"c2226e5ec5\",\"type\":\"paragraph\",\"data\":{\"text\":\"The architectural distinction still matters. A retrieval layer can provide relevant knowledge, while system tools provide current PC state and perform actions.\"},\"tunes\":{}},{\"id\":\"e5137fc2c8\",\"type\":\"paragraph\",\"data\":{\"text\":\"That is the same separation used in many modern agents: knowledge is one source of context, live observations are another, and tool execution is a third.\"},\"tunes\":{}},{\"id\":\"059b89dedb\",\"type\":\"header\",\"data\":{\"text\":\"Why G-Assist can work offline\",\"level\":2},\"tunes\":{}},{\"id\":\"19447df6a4\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA runs the language model locally on the GeForce RTX GPU.\"},\"tunes\":{}},{\"id\":\"55aee6ada7\",\"type\":\"paragraph\",\"data\":{\"text\":\"That means the core assistant does not require a cloud-hosted language model for every prompt.\"},\"tunes\":{}},{\"id\":\"f265d1fd96\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA explicitly says G-Assist can run offline for its local capabilities.\"},\"tunes\":{}},{\"id\":\"1dc8613200\",\"type\":\"paragraph\",\"data\":{\"text\":\"A plug-in can still use the internet if that plug-in calls an online service. Local model execution and online plug-in access are separate questions.\"},\"tunes\":{}},{\"id\":\"ee01c97a66\",\"type\":\"header\",\"data\":{\"text\":\"The local-AI cost: G-Assist uses your GPU and VRAM\",\"level\":2},\"tunes\":{}},{\"id\":\"1784ad3fcf\",\"type\":\"paragraph\",\"data\":{\"text\":\"Running locally gives privacy and independence from a cloud model, but the work has to execute somewhere.\"},\"tunes\":{}},{\"id\":\"1275ab759f\",\"type\":\"paragraph\",\"data\":{\"text\":\"For G-Assist, that somewhere is the same GeForce RTX GPU that may already be rendering your game.\"},\"tunes\":{}},{\"id\":\"cec86f847a\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA warns that the GPU briefly allocates compute resources to AI inference when G-Assist responds. If a demanding game is running at the same time, the game can temporarily lose some rendering performance while the model is active.\"},\"tunes\":{}},{\"id\":\"e6ea700df6\",\"type\":\"paragraph\",\"data\":{\"text\":\"The current requirements also specify free-VRAM targets beyond the memory already used by the game: approximately 6 GB of free VRAM for Reasoning Mode and 4.5 GB for Flash Mode.\"},\"tunes\":{}},{\"id\":\"2126f74de5\",\"type\":\"callout\",\"data\":{\"variant\":\"warning\",\"title\":\"8 GB VRAM does not mean 8 GB is available to G-Assist\",\"body\":\"The game, Windows, the driver and other applications already consume VRAM. G-Assist's own requirement is about \u003Cstrong>free VRAM in addition to what the running workload already uses\u003C\u002Fstrong>.\"},\"tunes\":{}},{\"id\":\"13c0dcb3f3\",\"type\":\"referralArticle\",\"data\":{\"url\":\"https:\u002F\u002Ffigure.rocks\u002Fblog\u002Fvram-usage-is-not-vram-requirement-why-a-full-memory-meter-does-not-tell-the-whole-story\",\"title\":\"VRAM Usage Is Not VRAM Requirement: Why a Full Memory Meter Does Not Tell the Whole Story\",\"excerpt\":\"Why installed VRAM, current usage, residency budgets and real memory pressure are different things.\",\"ctaLabel\":\"Read the VRAM guide\"},\"tunes\":{}},{\"id\":\"d684b2c1c8\",\"type\":\"header\",\"data\":{\"text\":\"Reasoning Mode vs Flash Mode\",\"level\":2},\"tunes\":{}},{\"id\":\"3c1f2379db\",\"type\":\"paragraph\",\"data\":{\"text\":\"Current G-Assist versions separate a more capable Reasoning Mode from a faster Flash Mode.\"},\"tunes\":{}},{\"id\":\"86f50ebd33\",\"type\":\"paragraph\",\"data\":{\"text\":\"Reasoning Mode is designed for higher-quality decisions and can coordinate multiple actions from one prompt. Flash Mode is optimized for faster responses and lower resource demand.\"},\"tunes\":{}},{\"id\":\"e7be4789db\",\"type\":\"comparison\",\"data\":{\"title\":\"Reasoning Mode vs Flash Mode\",\"layout\":\"table\",\"columns\":[{\"id\":\"reasoning\",\"label\":\"Reasoning Mode\"},{\"id\":\"flash\",\"label\":\"Flash Mode\"}],\"rows\":[{\"id\":\"goal\",\"label\":\"Primary goal\",\"values\":[\"\",\"\"]},{\"id\":\"vram\",\"label\":\"Recommended free VRAM\",\"values\":[\"\",\"\"]},{\"id\":\"use\",\"label\":\"Best fit\",\"values\":[\"\",\"\"]}]},\"tunes\":{}},{\"id\":\"cef1bcf553\",\"type\":\"header\",\"data\":{\"text\":\"What plug-ins actually add\",\"level\":2},\"tunes\":{}},{\"id\":\"d380d5e28b\",\"type\":\"paragraph\",\"data\":{\"text\":\"A plug-in does not replace the language model. It gives the model a new action it is allowed to call.\"},\"tunes\":{}},{\"id\":\"434979ebda\",\"type\":\"paragraph\",\"data\":{\"text\":\"The plug-in defines functions, descriptions and parameters. G-Assist reads those descriptions, matches a user request to the appropriate function and sends structured arguments to it.\"},\"tunes\":{}},{\"id\":\"21ebe69c79\",\"type\":\"paragraph\",\"data\":{\"text\":\"That lets the assistant grow beyond NVIDIA's built-in functions.\"},\"tunes\":{}},{\"id\":\"d0ba7ef284\",\"type\":\"processFlow\",\"data\":{\"title\":\"How a G-Assist plug-in works\",\"orientation\":\"auto\",\"steps\":[{\"label\":\"1. Plug-in declares a function\",\"description\":\"For example: set_keyboard_color(color).\"},{\"label\":\"2. Manifest describes the function\",\"description\":\"The manifest tells G-Assist what the function does and what parameters it needs.\"},{\"label\":\"3. User asks naturally\",\"description\":\"For example: “Make my keyboard green.”\"},{\"label\":\"4. SLM selects the function\",\"description\":\"The model maps the request to the plug-in function and extracts green as the parameter.\"},{\"label\":\"5. Plug-in executes\",\"description\":\"The plug-in talks to the peripheral software or external service.\"}]},\"tunes\":{}},{\"id\":\"1dc857ce2f\",\"type\":\"header\",\"data\":{\"text\":\"G-Assist Protocol V2 is JSON-RPC 2.0\",\"level\":2},\"tunes\":{}},{\"id\":\"02bdb0566d\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA's current public plug-in repository uses Protocol V2.\"},\"tunes\":{}},{\"id\":\"f82da294cf\",\"type\":\"paragraph\",\"data\":{\"text\":\"Protocol V2 uses JSON-RPC 2.0 with length-prefixed messages between the G-Assist engine and plug-ins.\"},\"tunes\":{}},{\"id\":\"530c3cf9b9\",\"type\":\"paragraph\",\"data\":{\"text\":\"The engine can initialize a plug-in, check its health, execute a function, send user input and shut it down. Plug-ins can return results, stream progress or report errors.\"},\"tunes\":{}},{\"id\":\"2ce3fa5d75\",\"type\":\"comparison\",\"data\":{\"title\":\"The important Protocol V2 messages\",\"layout\":\"table\",\"columns\":[{\"id\":\"direction\",\"label\":\"Direction\"},{\"id\":\"purpose\",\"label\":\"Purpose\"}],\"rows\":[{\"id\":\"initialize\",\"label\":\"initialize\",\"values\":[\"\",\"\"]},{\"id\":\"ping\",\"label\":\"ping\",\"values\":[\"\",\"\"]},{\"id\":\"execute\",\"label\":\"execute\",\"values\":[\"\",\"\"]},{\"id\":\"stream\",\"label\":\"stream\",\"values\":[\"\",\"\"]},{\"id\":\"complete\",\"label\":\"complete\",\"values\":[\"\",\"\"]}]},\"tunes\":{}},{\"id\":\"304fbd9944\",\"type\":\"header\",\"data\":{\"text\":\"Where MCP enters the picture\",\"level\":2},\"tunes\":{}},{\"id\":\"fae73881e4\",\"type\":\"paragraph\",\"data\":{\"text\":\"G-Assist's own plug-in protocol is not MCP. Its current public plug-in system uses JSON-RPC 2.0.\"},\"tunes\":{}},{\"id\":\"551d11710a\",\"type\":\"paragraph\",\"data\":{\"text\":\"However, a G-Assist plug-in can connect to an MCP server.\"},\"tunes\":{}},{\"id\":\"0537fb222a\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA's current version 0.2.2 includes an Elgato integration that can invoke actions exposed through the Elgato Stream Deck MCP server.\"},\"tunes\":{}},{\"id\":\"760a86ad19\",\"type\":\"callout\",\"data\":{\"variant\":\"success\",\"title\":\"Important protocol distinction\",\"body\":\"\u003Cstrong>G-Assist ↔ its plug-in:\u003C\u002Fstrong> NVIDIA Protocol V2 \u002F JSON-RPC 2.0.\u003Cbr>\u003Cstrong>Plug-in ↔ another tool ecosystem:\u003C\u002Fstrong> can use MCP when that integration supports it.\"},\"tunes\":{}},{\"id\":\"bd182f72b0\",\"type\":\"header\",\"data\":{\"text\":\"Why this matters beyond RGB lights\",\"level\":2},\"tunes\":{}},{\"id\":\"d072506ce2\",\"type\":\"paragraph\",\"data\":{\"text\":\"The plug-in architecture turns G-Assist from a fixed assistant into a local tool router.\"},\"tunes\":{}},{\"id\":\"2876e067dc\",\"type\":\"paragraph\",\"data\":{\"text\":\"The same pattern can connect an SLM to monitoring tools, peripherals, APIs, automation systems, local applications or external services.\"},\"tunes\":{}},{\"id\":\"37689640e9\",\"type\":\"paragraph\",\"data\":{\"text\":\"The important architectural unit is therefore not the chat window. It is the boundary between natural-language intent and structured tool execution.\"},\"tunes\":{}},{\"id\":\"550fbb42d4\",\"type\":\"header\",\"data\":{\"text\":\"The Local Agent Stack\",\"level\":2},\"tunes\":{}},{\"id\":\"8518dbf820\",\"type\":\"processFlow\",\"data\":{\"title\":\"A useful way to think about G-Assist\",\"orientation\":\"auto\",\"steps\":[{\"label\":\"1. User intent\",\"description\":\"Natural language or voice command.\"},{\"label\":\"2. Local SLM\",\"description\":\"Understands the request and chooses a capability.\"},{\"label\":\"3. Knowledge \u002F context\",\"description\":\"Provides product knowledge, recommendations or information needed for the decision.\"},{\"label\":\"4. Live system state\",\"description\":\"Provides current hardware, driver, performance or configuration information when supported.\"},{\"label\":\"5. Tool selection\",\"description\":\"Built-in function or plug-in is chosen.\"},{\"label\":\"6. Structured execution\",\"description\":\"The function receives arguments and performs the real action.\"},{\"label\":\"7. Result verification\",\"description\":\"The tool returns status or data and the model explains what happened.\"}]},\"tunes\":{}},{\"id\":\"6c976db763\",\"type\":\"header\",\"data\":{\"text\":\"Why tool boundaries are a safety feature\",\"level\":2},\"tunes\":{}},{\"id\":\"ba65a3b467\",\"type\":\"paragraph\",\"data\":{\"text\":\"An AI assistant that could execute arbitrary operating-system commands would be far more powerful, but also much harder to constrain.\"},\"tunes\":{}},{\"id\":\"a932df9663\",\"type\":\"paragraph\",\"data\":{\"text\":\"G-Assist instead exposes defined functions with known parameters.\"},\"tunes\":{}},{\"id\":\"7d1d45c83d\",\"type\":\"paragraph\",\"data\":{\"text\":\"That means the model can only perform actions that the built-in function set or installed plug-ins make available.\"},\"tunes\":{}},{\"id\":\"10460fda21\",\"type\":\"paragraph\",\"data\":{\"text\":\"This does not remove all risk, especially with third-party plug-ins, but it creates a clearer permission and capability boundary than unrestricted shell access.\"},\"tunes\":{}},{\"id\":\"25049448ea\",\"type\":\"header\",\"data\":{\"text\":\"The Tool-Authority Boundary\",\"level\":2},\"tunes\":{}},{\"id\":\"d3ff568795\",\"type\":\"comparison\",\"data\":{\"title\":\"What the assistant can understand vs what it is allowed to do\",\"layout\":\"table\",\"columns\":[{\"id\":\"understand\",\"label\":\"Model may understand\"},{\"id\":\"authority\",\"label\":\"Tool authority\"}],\"rows\":[{\"id\":\"gpu\",\"label\":\"GPU tuning\",\"values\":[\"\",\"\"]},{\"id\":\"files\",\"label\":\"Files\",\"values\":[\"\",\"\"]},{\"id\":\"web\",\"label\":\"Internet\",\"values\":[\"\",\"\"]},{\"id\":\"device\",\"label\":\"Peripheral control\",\"values\":[\"\",\"\"]}]},\"tunes\":{}},{\"id\":\"8fd8e35c51\",\"type\":\"header\",\"data\":{\"text\":\"Why G-Assist can temporarily reduce game performance\",\"level\":2},\"tunes\":{}},{\"id\":\"f75234546f\",\"type\":\"paragraph\",\"data\":{\"text\":\"The local-model architecture has a straightforward consequence: the AI and the game can compete for the same GPU.\"},\"tunes\":{}},{\"id\":\"28bc054afa\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA explicitly warns that render rate or inference speed can briefly dip while G-Assist is processing a request during a GPU-heavy workload.\"},\"tunes\":{}},{\"id\":\"0823573513\",\"type\":\"paragraph\",\"data\":{\"text\":\"Once inference finishes, those GPU resources return to the game.\"},\"tunes\":{}},{\"id\":\"905eed843d\",\"type\":\"paragraph\",\"data\":{\"text\":\"This is different from a cloud assistant, where most model inference happens on a remote server and does not consume the gaming GPU.\"},\"tunes\":{}},{\"id\":\"839c0e3988\",\"type\":\"header\",\"data\":{\"text\":\"The Local Assistant Resource Test\",\"level\":2},\"tunes\":{}},{\"id\":\"affa0ee1b3\",\"type\":\"processFlow\",\"data\":{\"title\":\"How to judge whether a local gaming assistant fits your PC\",\"orientation\":\"auto\",\"steps\":[{\"label\":\"1. Check installed VRAM\",\"description\":\"The current G-Assist baseline is an RTX GPU with at least 6 GB VRAM.\"},{\"label\":\"2. Check free VRAM during the actual game\",\"description\":\"Installed capacity is not the same as free capacity.\"},{\"label\":\"3. Choose Reasoning or Flash Mode appropriately\",\"description\":\"Use the lighter mode when resource pressure matters more than deep reasoning.\"},{\"label\":\"4. Measure inference-time frame-rate dips\",\"description\":\"Watch the game while asking G-Assist to perform tasks.\"},{\"label\":\"5. Inspect tool authority\",\"description\":\"Know exactly which built-in functions and plug-ins can change your system.\"},{\"label\":\"6. Treat third-party plug-ins as software\",\"description\":\"Review their source, permissions, network access and stored credentials.\"}]},\"tunes\":{}},{\"id\":\"ca52c48d2e\",\"type\":\"header\",\"data\":{\"text\":\"Why plug-ins deserve the same scrutiny as any other software\",\"level\":2},\"tunes\":{}},{\"id\":\"8e6a760529\",\"type\":\"paragraph\",\"data\":{\"text\":\"A plug-in can connect the assistant to APIs, peripheral applications and online services.\"},\"tunes\":{}},{\"id\":\"be793240e1\",\"type\":\"paragraph\",\"data\":{\"text\":\"That means a plug-in may handle configuration values, credentials or external requests depending on what it was built to do.\"},\"tunes\":{}},{\"id\":\"3c6c4c9aaf\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA's repository explicitly provides a config.json location for plug-in settings and warns developers not to commit credentials.\"},\"tunes\":{}},{\"id\":\"03413f935a\",\"type\":\"paragraph\",\"data\":{\"text\":\"The correct security question is therefore not only “Is G-Assist local?” but also “What does each installed plug-in connect to?”\"},\"tunes\":{}},{\"id\":\"f473162e86\",\"type\":\"header\",\"data\":{\"text\":\"G-Assist is closer to an agent than a chatbot\",\"level\":2},\"tunes\":{}},{\"id\":\"59dd3df9c2\",\"type\":\"paragraph\",\"data\":{\"text\":\"A chatbot mainly produces language.\"},\"tunes\":{}},{\"id\":\"188cb4bb40\",\"type\":\"paragraph\",\"data\":{\"text\":\"An agent interprets a goal, observes relevant information, chooses an action, calls a tool and evaluates the result.\"},\"tunes\":{}},{\"id\":\"117d1032f1\",\"type\":\"paragraph\",\"data\":{\"text\":\"G-Assist now fits that second description much more closely because it can coordinate multiple actions, inspect supported PC state and invoke real tools.\"},\"tunes\":{}},{\"id\":\"ef132fc518\",\"type\":\"referralArticle\",\"data\":{\"url\":\"https:\u002F\u002Ffigure.rocks\u002Fblog\u002Fpubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning\",\"title\":\"PUBG Ally Shows Why AI Teammates Need Two Brains: Fast Reflexes and Slow Reasoning\",\"excerpt\":\"A game-agent architecture example showing the separation between reasoning, live state, tools and deterministic execution.\",\"ctaLabel\":\"Read the PUBG Ally architecture guide\"},\"tunes\":{}},{\"id\":\"9f8fa308a5\",\"type\":\"header\",\"data\":{\"text\":\"What G-Assist still is not\",\"level\":2},\"tunes\":{}},{\"id\":\"f5f24e8aa3\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA explicitly describes G-Assist as a specialized local assistant, not a general-purpose conversational AI.\"},\"tunes\":{}},{\"id\":\"e4d187593f\",\"type\":\"paragraph\",\"data\":{\"text\":\"Its value comes from understanding a focused set of PC and gaming tasks and having tools connected to those tasks.\"},\"tunes\":{}},{\"id\":\"0c1b7f8948\",\"type\":\"paragraph\",\"data\":{\"text\":\"That focus is important because a smaller local model can be useful when the surrounding system gives it strong tools and clear boundaries.\"},\"tunes\":{}},{\"id\":\"79a5920e77\",\"type\":\"header\",\"data\":{\"text\":\"What changed in the current versions?\",\"level\":2},\"tunes\":{}},{\"id\":\"e78d96ef6c\",\"type\":\"paragraph\",\"data\":{\"text\":\"The current public release history shows G-Assist moving steadily toward a more capable local agent.\"},\"tunes\":{}},{\"id\":\"87dd1d3d3c\",\"type\":\"table\",\"data\":{\"withHeadings\":true,\"stretched\":false,\"content\":[[\"Version\",\"Important change\"],[\"0.1.17\",\"Lighter model, all RTX GPUs with 6 GB+ VRAM, community plug-ins\"],[\"0.1.18\",\"Laptop optimization, BatteryBoost and WhisperMode controls\"],[\"0.2\",\"Reasoning Mode, Flash Mode, multi-action prompts, new device controls\"],[\"0.2.1\",\"Improved knowledge system, better recommendations, RTX feature controls\"],[\"0.2.2\",\"Elgato Stream Deck integration through an MCP server\"]]},\"tunes\":{}},{\"id\":\"09bde21a8d\",\"type\":\"header\",\"data\":{\"text\":\"What would change this answer?\",\"level\":2},\"tunes\":{}},{\"id\":\"b0e7ca01a4\",\"type\":\"paragraph\",\"data\":{\"text\":\"G-Assist is still experimental and its architecture is evolving.\"},\"tunes\":{}},{\"id\":\"537568c224\",\"type\":\"paragraph\",\"data\":{\"text\":\"The model size, VRAM requirements, tool set, plug-in protocol and hardware support can all change in future releases.\"},\"tunes\":{}},{\"id\":\"fe24516c11\",\"type\":\"paragraph\",\"data\":{\"text\":\"A future version could also move some inference to an NPU or introduce broader MCP integration, but that should not be assumed until NVIDIA documents it.\"},\"tunes\":{}},{\"id\":\"0e31e2d54d\",\"type\":\"header\",\"data\":{\"text\":\"Limitations\",\"level\":2},\"tunes\":{}},{\"id\":\"a7881e11e1\",\"type\":\"paragraph\",\"data\":{\"text\":\"This article describes NVIDIA's public G-Assist product documentation and public plug-in architecture as of September 2026.\"},\"tunes\":{}},{\"id\":\"71ebc16fda\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA does not publicly document every internal detail of its knowledge and recommendation pipeline, so this article does not claim that every knowledge answer uses RAG or any other specific retrieval implementation.\"},\"tunes\":{}},{\"id\":\"add780d6ba\",\"type\":\"paragraph\",\"data\":{\"text\":\"Third-party plug-ins can have behavior and network access beyond NVIDIA's built-in functions, so each plug-in should be evaluated separately.\"},\"tunes\":{}},{\"id\":\"f7a38af5be\",\"type\":\"header\",\"data\":{\"text\":\"Conclusion\",\"level\":2},\"tunes\":{}},{\"id\":\"f1308f3e80\",\"type\":\"paragraph\",\"data\":{\"text\":\"The easiest way to understand Project G-Assist is to stop thinking of it as a chatbot.\"},\"tunes\":{}},{\"id\":\"b102a861bb\",\"type\":\"paragraph\",\"data\":{\"text\":\"The local SLM interprets your request. Knowledge helps it understand the problem. Live system information tells it what is true on your PC. A built-in function or plug-in defines what it is actually allowed to do. The tool performs the action and returns the result.\"},\"tunes\":{}},{\"id\":\"da805fabf0\",\"type\":\"paragraph\",\"data\":{\"text\":\"That is a local agent architecture.\"},\"tunes\":{}},{\"id\":\"675aecee06\",\"type\":\"paragraph\",\"data\":{\"text\":\"Its strongest idea is not that an 8-billion-parameter model can talk about your GPU. It is that a relatively small local model can become useful when it is connected to well-defined tools, current state and a controlled action boundary.\"},\"tunes\":{}},{\"id\":\"0354b8daaf\",\"type\":\"header\",\"data\":{\"text\":\"FAQ\",\"level\":2},\"tunes\":{}},{\"id\":\"e75bc04532\",\"type\":\"faq\",\"data\":{\"title\":\"NVIDIA Project G-Assist in plain English\",\"items\":[{\"id\":\"faq1\",\"question\":\"Is G-Assist a cloud chatbot?\",\"answer\":\"No. Its core language model runs locally on the GeForce RTX GPU and can work offline for supported local functions.\"},{\"id\":\"faq2\",\"question\":\"What model does G-Assist use?\",\"answer\":\"NVIDIA currently describes it as a local Llama-based instruct model with 8 billion parameters.\"},{\"id\":\"faq3\",\"question\":\"Does the AI model directly change my GPU settings?\",\"answer\":\"No. The model selects a supported built-in function or plug-in, and that tool performs the actual change.\"},{\"id\":\"faq4\",\"question\":\"Does G-Assist use VRAM while gaming?\",\"answer\":\"Yes. NVIDIA recommends additional free VRAM for the assistant and warns that inference can briefly reduce game render performance.\"},{\"id\":\"faq5\",\"question\":\"Are G-Assist plug-ins MCP plug-ins?\",\"answer\":\"Not directly. G-Assist's own current plug-in protocol uses JSON-RPC 2.0, although a plug-in can connect to an MCP server.\"},{\"id\":\"faq6\",\"question\":\"Can G-Assist work offline?\",\"answer\":\"Its local assistant can, but individual plug-ins may still require internet access if they call online services.\"},{\"id\":\"faq7\",\"question\":\"Is G-Assist a general AI assistant?\",\"answer\":\"NVIDIA describes it as a specialized PC and gaming assistant rather than a broad general-purpose conversational model.\"}]},\"tunes\":{}},{\"id\":\"8733f298cd\",\"type\":\"header\",\"data\":{\"text\":\"Glossary\",\"level\":2},\"tunes\":{}},{\"id\":\"407257a6d1\",\"type\":\"glossary\",\"data\":{\"title\":\"Key G-Assist terms\",\"entries\":[{\"term\":\"SLM\",\"definition\":\"Small Language Model, a compact language model designed to run locally with lower hardware requirements than large cloud models.\",\"anchor\":\"slm\"},{\"term\":\"Tool calling\",\"definition\":\"The process where a language model chooses a defined function and supplies structured arguments so another component can perform an action.\",\"anchor\":\"tool-calling\"},{\"term\":\"Plug-in\",\"definition\":\"An extension that exposes additional functions or integrations to G-Assist.\",\"anchor\":\"plugin\"},{\"term\":\"JSON-RPC 2.0\",\"definition\":\"The structured message protocol used by the current G-Assist Protocol V2 plug-in system.\",\"anchor\":\"json-rpc\"},{\"term\":\"MCP\",\"definition\":\"Model Context Protocol, a separate tool and context interoperability protocol that some external integrations can expose.\",\"anchor\":\"mcp\"},{\"term\":\"Tool-Authority Boundary\",\"definition\":\"A Figure Rocks model separating what an AI model can understand from what its connected tools actually allow it to do.\",\"anchor\":\"tool-authority-boundary\"},{\"term\":\"Local Agent Stack\",\"definition\":\"A Figure Rocks model combining user intent, local SLM, knowledge, live state, tool selection, execution and result verification.\",\"anchor\":\"local-agent-stack\"},{\"term\":\"Local Assistant Resource Test\",\"definition\":\"A Figure Rocks workflow for evaluating VRAM, inference cost, tool permissions and plug-in risk before using a local gaming assistant.\",\"anchor\":\"local-assistant-resource-test\"}]},\"tunes\":{}},{\"id\":\"3ab856f2b4\",\"type\":\"header\",\"data\":{\"text\":\"Primary sources\",\"level\":2},\"tunes\":{}},{\"id\":\"367d2e3548\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fwww.nvidia.com\u002Fen-us\u002Fsoftware\u002Fnvidia-app\u002Fg-assist\u002F\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"NVIDIA — Project G-Assist\",\"description\":\"Official current product page covering the local model, supported functions, Reasoning and Flash modes, VRAM requirements, RTX controls, plug-ins and version 0.2.2 MCP-based Elgato integration.\"}},\"tunes\":{}},{\"id\":\"5641b514c0\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FG-Assist\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"NVIDIA — G-Assist GitHub\",\"description\":\"Official public plug-in repository documenting G-Assist's module architecture, plug-in discovery and Protocol V2.\"}},\"tunes\":{}},{\"id\":\"22a5b77a1b\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FG-Assist\u002Fblob\u002Fmain\u002FPLUGIN_MIGRATION_GUIDE_V2.md\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"NVIDIA — G-Assist Protocol V2 Migration Guide\",\"description\":\"Official protocol documentation covering JSON-RPC 2.0, initialization, health checks, execution, streaming, completion and plug-in SDK behavior.\"}},\"tunes\":{}},{\"id\":\"cc3301d997\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fblogs.nvidia.com\u002Fblog\u002Frtx-ai-garage-gamescom-g-assist-rtx-remix\u002F\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"NVIDIA Blog — Lightweight G-Assist Model\",\"description\":\"Official background on the lower-memory G-Assist model, support for 6 GB RTX GPUs and the community plug-in hub.\"}},\"tunes\":{}}],\"version\":\"2.31.6\"}",{"time":1484,"blocks":1485,"version":2184},1790407740910,[1486,1490,1495,1500,1504,1508,1512,1516,1520,1525,1529,1552,1556,1560,1564,1568,1590,1594,1598,1602,1606,1624,1629,1635,1639,1643,1647,1651,1655,1659,1663,1667,1671,1675,1679,1683,1687,1691,1696,1703,1707,1711,1715,1733,1737,1741,1745,1749,1769,1773,1777,1781,1785,1805,1809,1813,1817,1821,1826,1830,1834,1838,1842,1846,1872,1876,1880,1884,1888,1892,1896,1917,1921,1925,1929,1933,1937,1941,1964,1968,1972,1976,1980,1984,1988,1992,1996,2000,2007,2011,2015,2019,2023,2027,2031,2048,2052,2056,2060,2064,2068,2072,2076,2080,2084,2088,2092,2096,2100,2103,2129,2133,2154,2158,2164,2170,2177],{"id":541,"data":1487,"type":544,"tunes":1489},{"text":1488},"NVIDIA Project G-Assist looks like a chatbot, but that description misses the important part. It is a local AI system that can understand a request, inspect supported PC state, choose a tool or plug-in, and then perform a real action such as changing DLSS settings, checking a driver, adjusting a fan profile or controlling a peripheral.",{},{"id":547,"data":1491,"type":552,"tunes":1494},{"body":1492,"title":1493,"variant":551},"\u003Cstrong>G-Assist is not simply a chatbot for your GPU.\u003C\u002Fstrong> It is a local small language model connected to a set of allowed tools. The model interprets what you want, selects a supported function, passes arguments to that function, and the PC-side tool performs the action.","Direct answer",{},{"id":555,"data":1496,"type":552,"tunes":1499},{"body":1497,"title":1498,"variant":559},"\u003Cstrong>SLM = understands the request.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Knowledge = explains supported NVIDIA\u002FPC concepts.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Tools = perform actions.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Plug-ins = add new tools.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Your PC = the environment being inspected or changed.\u003C\u002Fstrong>","The easiest mental model",{},{"id":562,"data":1501,"type":566,"tunes":1503},{"title":1502,"maxLevel":565,"minLevel":47},"Contents",{},{"id":569,"data":1505,"type":572,"tunes":1507},{"text":1506,"level":47},"First: what is the AI model actually doing?",{},{"id":575,"data":1509,"type":544,"tunes":1511},{"text":1510},"G-Assist uses a local small language model, or SLM. NVIDIA currently describes the system as using a Llama-based 8-billion-parameter instruct model.",{},{"id":580,"data":1513,"type":544,"tunes":1515},{"text":1514},"The model's main job is not to render graphics or directly change hardware registers. Its job is to understand the user's language, decide which supported capability matches the request, and prepare the call to that capability.",{},{"id":585,"data":1517,"type":544,"tunes":1519},{"text":1518},"For example, if you say “set DLSS Super Resolution to Performance Mode,” the language model does not itself modify DLSS. It interprets the command and routes it to the supported function that can change the setting.",{},{"id":590,"data":1521,"type":552,"tunes":1524},{"body":1522,"title":1523,"variant":594},"The AI model \u003Cstrong>decides what tool to call\u003C\u002Fstrong>. The tool \u003Cstrong>does the real work\u003C\u002Fstrong>.","The important distinction",{},{"id":597,"data":1526,"type":572,"tunes":1528},{"text":1527,"level":47},"The G-Assist action pipeline",{},{"id":602,"data":1530,"type":625,"tunes":1551},{"steps":1531,"title":1550,"orientation":624},[1532,1535,1538,1541,1544,1547],{"label":1533,"description":1534},"1. You give a natural-language request","For example: “Optimize this game for performance.”",{"label":1536,"description":1537},"2. The local SLM interprets the request","It determines the user's intent and identifies which supported function or plug-in is relevant.",{"label":1539,"description":1540},"3. The system chooses a tool","That could be a built-in graphics-setting function, driver check, monitoring function or community plug-in.",{"label":1542,"description":1543},"4. Arguments are extracted","The model converts the request into structured values such as game name, mode, fan profile or DLSS setting.",{"label":1545,"description":1546},"5. The tool executes","The tool talks to the NVIDIA App, operating system, peripheral software or another service.",{"label":1548,"description":1549},"6. The result is returned","G-Assist reports what happened, or returns data that the model can explain.","What happens after you give G-Assist a command",{},{"id":628,"data":1553,"type":572,"tunes":1555},{"text":1554,"level":47},"This is tool calling, not magic PC control",{},{"id":633,"data":1557,"type":544,"tunes":1559},{"text":1558},"A language model cannot safely control an arbitrary computer simply because it understands English.",{},{"id":638,"data":1561,"type":544,"tunes":1563},{"text":1562},"It needs a defined interface that says which actions exist, which arguments they accept and what the tool returns.",{},{"id":643,"data":1565,"type":544,"tunes":1567},{"text":1566},"G-Assist's current built-in capabilities include functions such as optimizing graphics settings, changing supported RTX options, checking or downloading drivers, showing performance information, changing some laptop power features, controlling supported monitor functions and using supported peripheral plug-ins.",{},{"id":648,"data":1569,"type":676,"tunes":1589},{"rows":1570,"title":1583,"layout":668,"columns":1584},[1571,1574,1577,1580],{"id":652,"label":1572,"values":1573},"Understand “turn on DLSS”",[13,13],{"id":656,"label":1575,"values":1576},"Choose the correct function",[13,13],{"id":660,"label":1578,"values":1579},"Actually change the setting",[13,13],{"id":664,"label":1581,"values":1582},"Explain the result",[13,13],"Language model vs tool",[1585,1587],{"id":671,"label":1586},"Language model",{"id":674,"label":1588},"Tool \u002F plug-in",{},{"id":679,"data":1591,"type":572,"tunes":1593},{"text":1592,"level":47},"What is the knowledge layer?",{},{"id":684,"data":1595,"type":544,"tunes":1597},{"text":1596},"G-Assist also has a knowledge layer for answering questions and making recommendations.",{},{"id":689,"data":1599,"type":544,"tunes":1601},{"text":1600},"NVIDIA says version 0.2.1 introduced an improved knowledge system that helps G-Assist make more accurate settings recommendations.",{},{"id":694,"data":1603,"type":544,"tunes":1605},{"text":1604},"That knowledge layer is different from the live state of your PC.",{},{"id":699,"data":1607,"type":676,"tunes":1623},{"rows":1608,"title":1617,"layout":668,"columns":1618},[1609,1611,1614],{"id":703,"label":704,"values":1610},[13,13],{"id":707,"label":1612,"values":1613},"Game settings",[13,13],{"id":711,"label":1615,"values":1616},"Performance",[13,13],"Knowledge vs live PC state",[1619,1621],{"id":717,"label":1620},"Knowledge",{"id":720,"label":1622},"Live state",{},{"id":724,"data":1625,"type":552,"tunes":1628},{"body":1626,"title":1627,"variant":728},"\u003Cstrong>Knowledge\u003C\u002Fstrong> tells the assistant what a feature means or what usually matters.\u003Cbr>\u003Cstrong>State\u003C\u002Fstrong> tells it what is true on your machine right now.","Do not mix knowledge with state",{},{"id":731,"data":1630,"type":737,"tunes":1634},{"url":733,"title":1631,"excerpt":1632,"ctaLabel":1633},"What Is RAG? The Simplest Explanation of How It Works","A plain-English explanation of knowledge retrieval, state, memory, context and the language model.","Read the simple RAG guide",{},{"id":740,"data":1636,"type":572,"tunes":1638},{"text":1637,"level":47},"Does G-Assist use RAG?",{},{"id":745,"data":1640,"type":544,"tunes":1642},{"text":1641},"The safest answer is: G-Assist clearly has a knowledge system, but NVIDIA's public product page does not document every internal retrieval mechanism in enough detail to say that every knowledge answer is specifically produced by RAG.",{},{"id":750,"data":1644,"type":544,"tunes":1646},{"text":1645},"The architectural distinction still matters. A retrieval layer can provide relevant knowledge, while system tools provide current PC state and perform actions.",{},{"id":755,"data":1648,"type":544,"tunes":1650},{"text":1649},"That is the same separation used in many modern agents: knowledge is one source of context, live observations are another, and tool execution is a third.",{},{"id":760,"data":1652,"type":572,"tunes":1654},{"text":1653,"level":47},"Why G-Assist can work offline",{},{"id":765,"data":1656,"type":544,"tunes":1658},{"text":1657},"NVIDIA runs the language model locally on the GeForce RTX GPU.",{},{"id":770,"data":1660,"type":544,"tunes":1662},{"text":1661},"That means the core assistant does not require a cloud-hosted language model for every prompt.",{},{"id":775,"data":1664,"type":544,"tunes":1666},{"text":1665},"NVIDIA explicitly says G-Assist can run offline for its local capabilities.",{},{"id":780,"data":1668,"type":544,"tunes":1670},{"text":1669},"A plug-in can still use the internet if that plug-in calls an online service. Local model execution and online plug-in access are separate questions.",{},{"id":785,"data":1672,"type":572,"tunes":1674},{"text":1673,"level":47},"The local-AI cost: G-Assist uses your GPU and VRAM",{},{"id":790,"data":1676,"type":544,"tunes":1678},{"text":1677},"Running locally gives privacy and independence from a cloud model, but the work has to execute somewhere.",{},{"id":795,"data":1680,"type":544,"tunes":1682},{"text":1681},"For G-Assist, that somewhere is the same GeForce RTX GPU that may already be rendering your game.",{},{"id":800,"data":1684,"type":544,"tunes":1686},{"text":1685},"NVIDIA warns that the GPU briefly allocates compute resources to AI inference when G-Assist responds. If a demanding game is running at the same time, the game can temporarily lose some rendering performance while the model is active.",{},{"id":805,"data":1688,"type":544,"tunes":1690},{"text":1689},"The current requirements also specify free-VRAM targets beyond the memory already used by the game: approximately 6 GB of free VRAM for Reasoning Mode and 4.5 GB for Flash Mode.",{},{"id":810,"data":1692,"type":552,"tunes":1695},{"body":1693,"title":1694,"variant":728},"The game, Windows, the driver and other applications already consume VRAM. G-Assist's own requirement is about \u003Cstrong>free VRAM in addition to what the running workload already uses\u003C\u002Fstrong>.","8 GB VRAM does not mean 8 GB is available to G-Assist",{},{"id":816,"data":1697,"type":737,"tunes":1702},{"url":1698,"title":1699,"excerpt":1700,"ctaLabel":1701},"https:\u002F\u002Ffigure.rocks\u002Fblog\u002Fvram-usage-is-not-vram-requirement-why-a-full-memory-meter-does-not-tell-the-whole-story","VRAM Usage Is Not VRAM Requirement: Why a Full Memory Meter Does Not Tell the Whole Story","Why installed VRAM, current usage, residency budgets and real memory pressure are different things.","Read the VRAM guide",{},{"id":824,"data":1704,"type":572,"tunes":1706},{"text":1705,"level":47},"Reasoning Mode vs Flash Mode",{},{"id":829,"data":1708,"type":544,"tunes":1710},{"text":1709},"Current G-Assist versions separate a more capable Reasoning Mode from a faster Flash Mode.",{},{"id":834,"data":1712,"type":544,"tunes":1714},{"text":1713},"Reasoning Mode is designed for higher-quality decisions and can coordinate multiple actions from one prompt. Flash Mode is optimized for faster responses and lower resource demand.",{},{"id":839,"data":1716,"type":676,"tunes":1732},{"rows":1717,"title":1705,"layout":668,"columns":1727},[1718,1721,1724],{"id":843,"label":1719,"values":1720},"Primary goal",[13,13],{"id":847,"label":1722,"values":1723},"Recommended free VRAM",[13,13],{"id":851,"label":1725,"values":1726},"Best fit",[13,13],[1728,1730],{"id":856,"label":1729},"Reasoning Mode",{"id":859,"label":1731},"Flash Mode",{},{"id":863,"data":1734,"type":572,"tunes":1736},{"text":1735,"level":47},"What plug-ins actually add",{},{"id":868,"data":1738,"type":544,"tunes":1740},{"text":1739},"A plug-in does not replace the language model. It gives the model a new action it is allowed to call.",{},{"id":873,"data":1742,"type":544,"tunes":1744},{"text":1743},"The plug-in defines functions, descriptions and parameters. G-Assist reads those descriptions, matches a user request to the appropriate function and sends structured arguments to it.",{},{"id":878,"data":1746,"type":544,"tunes":1748},{"text":1747},"That lets the assistant grow beyond NVIDIA's built-in functions.",{},{"id":883,"data":1750,"type":625,"tunes":1768},{"steps":1751,"title":1767,"orientation":624},[1752,1755,1758,1761,1764],{"label":1753,"description":1754},"1. Plug-in declares a function","For example: set_keyboard_color(color).",{"label":1756,"description":1757},"2. Manifest describes the function","The manifest tells G-Assist what the function does and what parameters it needs.",{"label":1759,"description":1760},"3. User asks naturally","For example: “Make my keyboard green.”",{"label":1762,"description":1763},"4. SLM selects the function","The model maps the request to the plug-in function and extracts green as the parameter.",{"label":1765,"description":1766},"5. Plug-in executes","The plug-in talks to the peripheral software or external service.","How a G-Assist plug-in works",{},{"id":904,"data":1770,"type":572,"tunes":1772},{"text":1771,"level":47},"G-Assist Protocol V2 is JSON-RPC 2.0",{},{"id":909,"data":1774,"type":544,"tunes":1776},{"text":1775},"NVIDIA's current public plug-in repository uses Protocol V2.",{},{"id":914,"data":1778,"type":544,"tunes":1780},{"text":1779},"Protocol V2 uses JSON-RPC 2.0 with length-prefixed messages between the G-Assist engine and plug-ins.",{},{"id":919,"data":1782,"type":544,"tunes":1784},{"text":1783},"The engine can initialize a plug-in, check its health, execute a function, send user input and shut it down. Plug-ins can return results, stream progress or report errors.",{},{"id":924,"data":1786,"type":676,"tunes":1804},{"rows":1787,"title":1798,"layout":668,"columns":1799},[1788,1790,1792,1794,1796],{"id":928,"label":928,"values":1789},[13,13],{"id":931,"label":931,"values":1791},[13,13],{"id":934,"label":934,"values":1793},[13,13],{"id":937,"label":937,"values":1795},[13,13],{"id":940,"label":940,"values":1797},[13,13],"The important Protocol V2 messages",[1800,1802],{"id":945,"label":1801},"Direction",{"id":948,"label":1803},"Purpose",{},{"id":952,"data":1806,"type":572,"tunes":1808},{"text":1807,"level":47},"Where MCP enters the picture",{},{"id":957,"data":1810,"type":544,"tunes":1812},{"text":1811},"G-Assist's own plug-in protocol is not MCP. Its current public plug-in system uses JSON-RPC 2.0.",{},{"id":962,"data":1814,"type":544,"tunes":1816},{"text":1815},"However, a G-Assist plug-in can connect to an MCP server.",{},{"id":967,"data":1818,"type":544,"tunes":1820},{"text":1819},"NVIDIA's current version 0.2.2 includes an Elgato integration that can invoke actions exposed through the Elgato Stream Deck MCP server.",{},{"id":972,"data":1822,"type":552,"tunes":1825},{"body":1823,"title":1824,"variant":594},"\u003Cstrong>G-Assist ↔ its plug-in:\u003C\u002Fstrong> NVIDIA Protocol V2 \u002F JSON-RPC 2.0.\u003Cbr>\u003Cstrong>Plug-in ↔ another tool ecosystem:\u003C\u002Fstrong> can use MCP when that integration supports it.","Important protocol distinction",{},{"id":978,"data":1827,"type":572,"tunes":1829},{"text":1828,"level":47},"Why this matters beyond RGB lights",{},{"id":983,"data":1831,"type":544,"tunes":1833},{"text":1832},"The plug-in architecture turns G-Assist from a fixed assistant into a local tool router.",{},{"id":988,"data":1835,"type":544,"tunes":1837},{"text":1836},"The same pattern can connect an SLM to monitoring tools, peripherals, APIs, automation systems, local applications or external services.",{},{"id":993,"data":1839,"type":544,"tunes":1841},{"text":1840},"The important architectural unit is therefore not the chat window. It is the boundary between natural-language intent and structured tool execution.",{},{"id":998,"data":1843,"type":572,"tunes":1845},{"text":1844,"level":47},"The Local Agent Stack",{},{"id":1003,"data":1847,"type":625,"tunes":1871},{"steps":1848,"title":1870,"orientation":624},[1849,1852,1855,1858,1861,1864,1867],{"label":1850,"description":1851},"1. User intent","Natural language or voice command.",{"label":1853,"description":1854},"2. Local SLM","Understands the request and chooses a capability.",{"label":1856,"description":1857},"3. Knowledge \u002F context","Provides product knowledge, recommendations or information needed for the decision.",{"label":1859,"description":1860},"4. Live system state","Provides current hardware, driver, performance or configuration information when supported.",{"label":1862,"description":1863},"5. Tool selection","Built-in function or plug-in is chosen.",{"label":1865,"description":1866},"6. Structured execution","The function receives arguments and performs the real action.",{"label":1868,"description":1869},"7. Result verification","The tool returns status or data and the model explains what happened.","A useful way to think about G-Assist",{},{"id":1030,"data":1873,"type":572,"tunes":1875},{"text":1874,"level":47},"Why tool boundaries are a safety feature",{},{"id":1035,"data":1877,"type":544,"tunes":1879},{"text":1878},"An AI assistant that could execute arbitrary operating-system commands would be far more powerful, but also much harder to constrain.",{},{"id":1040,"data":1881,"type":544,"tunes":1883},{"text":1882},"G-Assist instead exposes defined functions with known parameters.",{},{"id":1045,"data":1885,"type":544,"tunes":1887},{"text":1886},"That means the model can only perform actions that the built-in function set or installed plug-ins make available.",{},{"id":1050,"data":1889,"type":544,"tunes":1891},{"text":1890},"This does not remove all risk, especially with third-party plug-ins, but it creates a clearer permission and capability boundary than unrestricted shell access.",{},{"id":1055,"data":1893,"type":572,"tunes":1895},{"text":1894,"level":47},"The Tool-Authority Boundary",{},{"id":1060,"data":1897,"type":676,"tunes":1916},{"rows":1898,"title":1910,"layout":668,"columns":1911},[1899,1902,1905,1907],{"id":703,"label":1900,"values":1901},"GPU tuning",[13,13],{"id":1067,"label":1903,"values":1904},"Files",[13,13],{"id":1071,"label":1072,"values":1906},[13,13],{"id":1075,"label":1908,"values":1909},"Peripheral control",[13,13],"What the assistant can understand vs what it is allowed to do",[1912,1914],{"id":652,"label":1913},"Model may understand",{"id":1083,"label":1915},"Tool authority",{},{"id":1087,"data":1918,"type":572,"tunes":1920},{"text":1919,"level":47},"Why G-Assist can temporarily reduce game performance",{},{"id":1092,"data":1922,"type":544,"tunes":1924},{"text":1923},"The local-model architecture has a straightforward consequence: the AI and the game can compete for the same GPU.",{},{"id":1097,"data":1926,"type":544,"tunes":1928},{"text":1927},"NVIDIA explicitly warns that render rate or inference speed can briefly dip while G-Assist is processing a request during a GPU-heavy workload.",{},{"id":1102,"data":1930,"type":544,"tunes":1932},{"text":1931},"Once inference finishes, those GPU resources return to the game.",{},{"id":1107,"data":1934,"type":544,"tunes":1936},{"text":1935},"This is different from a cloud assistant, where most model inference happens on a remote server and does not consume the gaming GPU.",{},{"id":1112,"data":1938,"type":572,"tunes":1940},{"text":1939,"level":47},"The Local Assistant Resource Test",{},{"id":1117,"data":1942,"type":625,"tunes":1963},{"steps":1943,"title":1962,"orientation":624},[1944,1947,1950,1953,1956,1959],{"label":1945,"description":1946},"1. Check installed VRAM","The current G-Assist baseline is an RTX GPU with at least 6 GB VRAM.",{"label":1948,"description":1949},"2. Check free VRAM during the actual game","Installed capacity is not the same as free capacity.",{"label":1951,"description":1952},"3. Choose Reasoning or Flash Mode appropriately","Use the lighter mode when resource pressure matters more than deep reasoning.",{"label":1954,"description":1955},"4. Measure inference-time frame-rate dips","Watch the game while asking G-Assist to perform tasks.",{"label":1957,"description":1958},"5. Inspect tool authority","Know exactly which built-in functions and plug-ins can change your system.",{"label":1960,"description":1961},"6. Treat third-party plug-ins as software","Review their source, permissions, network access and stored credentials.","How to judge whether a local gaming assistant fits your PC",{},{"id":1141,"data":1965,"type":572,"tunes":1967},{"text":1966,"level":47},"Why plug-ins deserve the same scrutiny as any other software",{},{"id":1146,"data":1969,"type":544,"tunes":1971},{"text":1970},"A plug-in can connect the assistant to APIs, peripheral applications and online services.",{},{"id":1151,"data":1973,"type":544,"tunes":1975},{"text":1974},"That means a plug-in may handle configuration values, credentials or external requests depending on what it was built to do.",{},{"id":1156,"data":1977,"type":544,"tunes":1979},{"text":1978},"NVIDIA's repository explicitly provides a config.json location for plug-in settings and warns developers not to commit credentials.",{},{"id":1161,"data":1981,"type":544,"tunes":1983},{"text":1982},"The correct security question is therefore not only “Is G-Assist local?” but also “What does each installed plug-in connect to?”",{},{"id":1166,"data":1985,"type":572,"tunes":1987},{"text":1986,"level":47},"G-Assist is closer to an agent than a chatbot",{},{"id":1171,"data":1989,"type":544,"tunes":1991},{"text":1990},"A chatbot mainly produces language.",{},{"id":1176,"data":1993,"type":544,"tunes":1995},{"text":1994},"An agent interprets a goal, observes relevant information, chooses an action, calls a tool and evaluates the result.",{},{"id":1181,"data":1997,"type":544,"tunes":1999},{"text":1998},"G-Assist now fits that second description much more closely because it can coordinate multiple actions, inspect supported PC state and invoke real tools.",{},{"id":1186,"data":2001,"type":737,"tunes":2006},{"url":2002,"title":2003,"excerpt":2004,"ctaLabel":2005},"https:\u002F\u002Ffigure.rocks\u002Fblog\u002Fpubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning","PUBG Ally Shows Why AI Teammates Need Two Brains: Fast Reflexes and Slow Reasoning","A game-agent architecture example showing the separation between reasoning, live state, tools and deterministic execution.","Read the PUBG Ally architecture guide",{},{"id":1194,"data":2008,"type":572,"tunes":2010},{"text":2009,"level":47},"What G-Assist still is not",{},{"id":1199,"data":2012,"type":544,"tunes":2014},{"text":2013},"NVIDIA explicitly describes G-Assist as a specialized local assistant, not a general-purpose conversational AI.",{},{"id":1204,"data":2016,"type":544,"tunes":2018},{"text":2017},"Its value comes from understanding a focused set of PC and gaming tasks and having tools connected to those tasks.",{},{"id":1209,"data":2020,"type":544,"tunes":2022},{"text":2021},"That focus is important because a smaller local model can be useful when the surrounding system gives it strong tools and clear boundaries.",{},{"id":1214,"data":2024,"type":572,"tunes":2026},{"text":2025,"level":47},"What changed in the current versions?",{},{"id":1219,"data":2028,"type":544,"tunes":2030},{"text":2029},"The current public release history shows G-Assist moving steadily toward a more capable local agent.",{},{"id":1224,"data":2032,"type":668,"tunes":2047},{"content":2033,"stretched":1245,"withHeadings":15},[2034,2037,2039,2041,2043,2045],[2035,2036],"Version","Important change",[1231,2038],"Lighter model, all RTX GPUs with 6 GB+ VRAM, community plug-ins",[1234,2040],"Laptop optimization, BatteryBoost and WhisperMode controls",[1237,2042],"Reasoning Mode, Flash Mode, multi-action prompts, new device controls",[1240,2044],"Improved knowledge system, better recommendations, RTX feature controls",[1243,2046],"Elgato Stream Deck integration through an MCP server",{},{"id":1248,"data":2049,"type":572,"tunes":2051},{"text":2050,"level":47},"What would change this answer?",{},{"id":1253,"data":2053,"type":544,"tunes":2055},{"text":2054},"G-Assist is still experimental and its architecture is evolving.",{},{"id":1258,"data":2057,"type":544,"tunes":2059},{"text":2058},"The model size, VRAM requirements, tool set, plug-in protocol and hardware support can all change in future releases.",{},{"id":1263,"data":2061,"type":544,"tunes":2063},{"text":2062},"A future version could also move some inference to an NPU or introduce broader MCP integration, but that should not be assumed until NVIDIA documents it.",{},{"id":1268,"data":2065,"type":572,"tunes":2067},{"text":2066,"level":47},"Limitations",{},{"id":1273,"data":2069,"type":544,"tunes":2071},{"text":2070},"This article describes NVIDIA's public G-Assist product documentation and public plug-in architecture as of September 2026.",{},{"id":1278,"data":2073,"type":544,"tunes":2075},{"text":2074},"NVIDIA does not publicly document every internal detail of its knowledge and recommendation pipeline, so this article does not claim that every knowledge answer uses RAG or any other specific retrieval implementation.",{},{"id":1283,"data":2077,"type":544,"tunes":2079},{"text":2078},"Third-party plug-ins can have behavior and network access beyond NVIDIA's built-in functions, so each plug-in should be evaluated separately.",{},{"id":1288,"data":2081,"type":572,"tunes":2083},{"text":2082,"level":47},"Conclusion",{},{"id":1293,"data":2085,"type":544,"tunes":2087},{"text":2086},"The easiest way to understand Project G-Assist is to stop thinking of it as a chatbot.",{},{"id":1298,"data":2089,"type":544,"tunes":2091},{"text":2090},"The local SLM interprets your request. Knowledge helps it understand the problem. Live system information tells it what is true on your PC. A built-in function or plug-in defines what it is actually allowed to do. The tool performs the action and returns the result.",{},{"id":1303,"data":2093,"type":544,"tunes":2095},{"text":2094},"That is a local agent architecture.",{},{"id":1308,"data":2097,"type":544,"tunes":2099},{"text":2098},"Its strongest idea is not that an 8-billion-parameter model can talk about your GPU. It is that a relatively small local model can become useful when it is connected to well-defined tools, current state and a controlled action boundary.",{},{"id":1313,"data":2101,"type":572,"tunes":2102},{"text":1315,"level":47},{},{"id":1318,"data":2104,"type":1350,"tunes":2128},{"items":2105,"title":2127},[2106,2109,2112,2115,2118,2121,2124],{"id":1322,"answer":2107,"question":2108},"No. Its core language model runs locally on the GeForce RTX GPU and can work offline for supported local functions.","Is G-Assist a cloud chatbot?",{"id":1326,"answer":2110,"question":2111},"NVIDIA currently describes it as a local Llama-based instruct model with 8 billion parameters.","What model does G-Assist use?",{"id":1330,"answer":2113,"question":2114},"No. The model selects a supported built-in function or plug-in, and that tool performs the actual change.","Does the AI model directly change my GPU settings?",{"id":1334,"answer":2116,"question":2117},"Yes. NVIDIA recommends additional free VRAM for the assistant and warns that inference can briefly reduce game render performance.","Does G-Assist use VRAM while gaming?",{"id":1338,"answer":2119,"question":2120},"Not directly. G-Assist's own current plug-in protocol uses JSON-RPC 2.0, although a plug-in can connect to an MCP server.","Are G-Assist plug-ins MCP plug-ins?",{"id":1342,"answer":2122,"question":2123},"Its local assistant can, but individual plug-ins may still require internet access if they call online services.","Can G-Assist work offline?",{"id":1346,"answer":2125,"question":2126},"NVIDIA describes it as a specialized PC and gaming assistant rather than a broad general-purpose conversational model.","Is G-Assist a general AI assistant?","NVIDIA Project G-Assist in plain English",{},{"id":1353,"data":2130,"type":572,"tunes":2132},{"text":2131,"level":47},"Glossary",{},{"id":1358,"data":2134,"type":1394,"tunes":2153},{"title":2135,"entries":2136},"Key G-Assist terms",[2137,2139,2141,2143,2145,2147,2149,2151],{"term":1363,"anchor":1364,"definition":2138},"Small Language Model, a compact language model designed to run locally with lower hardware requirements than large cloud models.",{"term":1367,"anchor":1368,"definition":2140},"The process where a language model chooses a defined function and supplies structured arguments so another component can perform an action.",{"term":1371,"anchor":1372,"definition":2142},"An extension that exposes additional functions or integrations to G-Assist.",{"term":1375,"anchor":1376,"definition":2144},"The structured message protocol used by the current G-Assist Protocol V2 plug-in system.",{"term":1379,"anchor":1380,"definition":2146},"Model Context Protocol, a separate tool and context interoperability protocol that some external integrations can expose.",{"term":1383,"anchor":1384,"definition":2148},"A Figure Rocks model separating what an AI model can understand from what its connected tools actually allow it to do.",{"term":1387,"anchor":1388,"definition":2150},"A Figure Rocks model combining user intent, local SLM, knowledge, live state, tool selection, execution and result verification.",{"term":1391,"anchor":1392,"definition":2152},"A Figure Rocks workflow for evaluating VRAM, inference cost, tool permissions and plug-in risk before using a local gaming assistant.",{},{"id":1397,"data":2155,"type":572,"tunes":2157},{"text":2156,"level":47},"Primary sources",{},{"id":1402,"data":2159,"type":1409,"tunes":2163},{"link":1404,"meta":2160},{"image":2161,"title":1407,"description":2162},{"url":13},"Official current product page covering the local model, supported functions, Reasoning and Flash modes, VRAM requirements, RTX controls, plug-ins and version 0.2.2 MCP-based Elgato integration.",{},{"id":1412,"data":2165,"type":1409,"tunes":2169},{"link":1414,"meta":2166},{"image":2167,"title":1417,"description":2168},{"url":13},"Official public plug-in repository documenting G-Assist's module architecture, plug-in discovery and Protocol V2.",{},{"id":1421,"data":2171,"type":1409,"tunes":2176},{"link":1423,"meta":2172},{"image":2173,"title":2174,"description":2175},{"url":13},"NVIDIA — G-Assist Protocol V2 Migration Guide","Official protocol documentation covering JSON-RPC 2.0, initialization, health checks, execution, streaming, completion and plug-in SDK behavior.",{},{"id":1430,"data":2178,"type":1409,"tunes":2183},{"link":1432,"meta":2179},{"image":2180,"title":2181,"description":2182},{"url":13},"NVIDIA Blog — Lightweight G-Assist Model","Official background on the lower-memory G-Assist model, support for 6 GB RTX GPUs and the community plug-in hub.",{},"2.31.6","NVIDIA Project G-Assist looks like a chatbot, but its real architecture is closer to a local AI agent. A small language model interprets your request, system state provides current PC information, tools perform real actions, and plug-ins extend what the assistant is allowed to 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Usa questo glossario per scegliere la modalità giusta per la chiarezza e il feeling di gioco.","2026-02-20T14:00:00.000Z",{"id":2698,"slug":2699,"title":2700,"excerpt":2701,"featuredImage":14,"publishedAt":2702},"246","router-checklist-for-gaming-the-settings-that-actually-matter","Checklist del router per il gaming: le impostazioni che contano davvero","La maggior parte delle ottimizzazioni per il router non serve. Queste impostazioni sì: gestione delle code sotto carico, comportamento Wi-Fi stabile ed evitare funzionalità che aggiungono latenza o instabilità.","2026-02-21T01:30:00.000Z",{"id":2704,"slug":2705,"title":2706,"excerpt":2707,"featuredImage":14,"publishedAt":2708},"159","ethernet-vs-wi-fi-for-gaming-the-real-reasons-ethernet-wins","Ethernet vs Wi-Fi per il gaming: i veri motivi per cui l'Ethernet vince","Ethernet non riguarda la velocità. Si tratta di stabilità: meno picchi, meno interferenze e tempi prevedibili. Usa questo per decidere quando il Wi-Fi è ‘abbastanza buono’.","2026-02-20T13:00:00.000Z",{"id":2710,"slug":2711,"title":2712,"excerpt":2713,"featuredImage":14,"publishedAt":2714},"207","120hz-feels-worse-the-diagnosis-checklist-wrong-mode-vrr-range-caps","120Hz sembrano peggiori? Checklist di diagnosi (Modalità errata, intervallo VRR, limitazioni)","Un refresh rate più elevato può evidenziare l'instabilità. Usa questa checklist per diagnosticare perché i 120Hz sembrano peggiori: modalità errata, percorso di aggiornamento errato, problemi di intervallo VRR o cap mancanti.","2026-02-20T20:30:00.000Z",{"id":2716,"slug":2717,"title":2718,"excerpt":2719,"featuredImage":14,"publishedAt":2720},"96","game-mode-on-tvs-and-monitors-the-one-setting-that-changes-everything","Modalità Gioco su TV e monitor: l'unica impostazione che cambia tutto","Se un gioco sembra pesante, controlla prima la modalità gioco. Scopri cosa disattiva la modalità gioco, perché riduce il ritardo e come verificare che stia effettivamente funzionando.","2026-02-19T11:00:00.000Z",{"id":2722,"slug":2723,"title":2724,"excerpt":2725,"featuredImage":14,"publishedAt":2726},"174","windows-game-mode-myths-what-it-does-and-what-actually-matters","Miti sulla Modalità Gioco di Windows: cosa fa (e cosa conta davvero)","La Modalità gioco di Windows non è un interruttore magico per la latenza. I vantaggi maggiori derivano ancora da un frame pacing stabile e dal controllo del carico in background. Usala, ma non venerarla.","2026-02-20T15:00:00.000Z",{"id":2728,"slug":2729,"title":2730,"excerpt":2731,"featuredImage":14,"publishedAt":2732},"209","windows-audio-mixer-traps-why-pc-audio-feels-inconsistent-in-games","Le insidie del mixer audio di Windows: perché l'audio del PC sembra incostante nei giochi","L'audio del PC sembra casuale quando il routing cambia silenziosamente. Scopri le trappole del mixer (commutazione del dispositivo predefinito, miglioramenti, routing delle app) e come bloccare un unico percorso stabile.","2026-02-20T23:40:00.000Z","fallback",[],[]]