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Il s'agit d'un système d'IA local capable de comprendre une requête, d'inspecter l'état pris en charge du PC, de choisir un outil ou un plug-in, puis d'effectuer une action réelle comme modifier les paramètres DLSS, vérifier un pilote, ajuster un profil de ventilateur ou contrôler un périphérique.\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\">Réponse directe\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">\u003Cstrong>G-Assist n'est pas simplement un chatbot pour votre GPU.\u003C\u002Fstrong> C'est un petit modèle de langage local connecté à un ensemble d'outils autorisés. Le modèle interprète ce que vous voulez, sélectionne une fonction prise en charge, transmet des arguments à cette fonction, et l'outil côté PC exécute l'action.\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\">Le modèle mental le plus simple\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">\u003Cstrong>SLM = comprend la requête.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Connaissances = explique les concepts NVIDIA\u002FPC pris en charge.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Outils = effectuent des actions.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Plug-ins = ajoutent de nouveaux outils.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Votre PC = l'environnement inspecté ou modifié.\u003C\u002Fstrong>\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Cnav class=\"editorjs-toc\" data-editorjs-toc=\"true\" aria-label=\"Sommaire\">\u003Cstrong class=\"editorjs-toc__title\">Sommaire\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\">D'abord : que fait réellement le modèle d'IA ?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-10\" class=\"editorjs-toc__link\">Le pipeline d'action de G-Assist\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-12\" class=\"editorjs-toc__link\">C'est de l'appel d'outils, pas du contrôle magique du PC\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-17\" class=\"editorjs-toc__link\">Qu'est-ce que la couche de connaissances ?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-24\" class=\"editorjs-toc__link\">G-Assist utilise-t-il le RAG ?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-28\" class=\"editorjs-toc__link\">Pourquoi G-Assist peut fonctionner hors ligne\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-33\" class=\"editorjs-toc__link\">Le coût de l'IA locale : G-Assist utilise votre GPU et votre VRAM\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-40\" class=\"editorjs-toc__link\">Mode Reasoning vs mode Flash\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-44\" class=\"editorjs-toc__link\">Ce que les plug-ins ajoutent réellement\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-49\" class=\"editorjs-toc__link\">Le protocole G-Assist V2 est JSON-RPC 2.0\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-54\" class=\"editorjs-toc__link\">Où MCP entre en jeu\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-59\" class=\"editorjs-toc__link\">Pourquoi cela compte au-delà des lumières RGB\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-63\" class=\"editorjs-toc__link\">La pile d'agents locaux\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-65\" class=\"editorjs-toc__link\">Pourquoi les frontières des outils sont une fonction de sécurité\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-70\" class=\"editorjs-toc__link\">La frontière d'autorité des outils\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-72\" class=\"editorjs-toc__link\">Pourquoi G-Assist peut temporairement réduire les performances de jeu\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-77\" class=\"editorjs-toc__link\">Le test des ressources de l'assistant local\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-79\" class=\"editorjs-toc__link\">Pourquoi les plug-ins méritent le même examen que tout autre logiciel\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-84\" class=\"editorjs-toc__link\">G-Assist est plus proche d'un agent que d'un chatbot\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-89\" class=\"editorjs-toc__link\">Ce que G-Assist n'est toujours pas\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-93\" class=\"editorjs-toc__link\">Qu'est-ce qui a changé dans les versions actuelles ?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-96\" class=\"editorjs-toc__link\">Qu'est-ce qui pourrait changer cette réponse ?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-100\" class=\"editorjs-toc__link\">Limites\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-104\" class=\"editorjs-toc__link\">Conclusion\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\">Glossaire\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-113\" class=\"editorjs-toc__link\">Sources principales\u003C\u002Fa>\u003C\u002Fli>\u003C\u002Fol>\u003C\u002Fnav>\n\u003Ch2 id=\"section-5\">D'abord : que fait réellement le modèle d'IA ?\u003C\u002Fh2>\n\u003Cp>G-Assist utilise un petit modèle de langage local, ou SLM. NVIDIA décrit actuellement le système comme utilisant un modèle instruct basé sur Llama de 8 milliards de paramètres.\u003C\u002Fp>\n\u003Cp>Le rôle principal du modèle n'est pas de rendre des graphiques ou de modifier directement les registres matériels. Son rôle est de comprendre le langage de l'utilisateur, de décider quelle capacité prise en charge correspond à la requête, et de préparer l'appel à cette capacité.\u003C\u002Fp>\n\u003Cp>Par exemple, si vous dites « définir DLSS Super Resolution en mode Performance », le modèle de langage ne modifie pas lui-même DLSS. Il interprète la commande et la dirige vers la fonction prise en charge qui peut modifier le paramètre.\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 distinction importante\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">Le modèle d'IA \u003Cstrong>décide quel outil appeler\u003C\u002Fstrong>. L'outil \u003Cstrong>fait le vrai travail\u003C\u002Fstrong>.\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Ch2 id=\"section-10\">Le pipeline d'action de G-Assist\u003C\u002Fh2>\n\u003Csection class=\"editorjs-process my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Ce qui se passe après avoir donné une commande à 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. Vous donnez une requête en langage naturel\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Par exemple : « Optimise ce jeu pour la performance. »\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. Le SLM local interprète la requête\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Il détermine l'intention de l'utilisateur et identifie quelle fonction ou plug-in pris en charge est pertinent.\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. Le système choisit un outil\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Cela peut être une fonction intégrée de paramètres graphiques, une vérification de pilote, une fonction de surveillance ou un plug-in communautaire.\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. Les arguments sont extraits\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Le modèle convertit la requête en valeurs structurées telles que le nom du jeu, le mode, le profil de ventilateur ou le paramètre 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. L'outil s'exécute\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">L'outil communique avec l'application NVIDIA, le système d'exploitation, le logiciel du périphérique ou un autre service.\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. Le résultat est renvoyé\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">G-Assist rapporte ce qui s'est passé, ou renvoie des données que le modèle peut expliquer.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-12\">C'est de l'appel d'outils, pas du contrôle magique du PC\u003C\u002Fh2>\n\u003Cp>Un modèle de langage ne peut pas contrôler en toute sécurité un ordinateur arbitraire simplement parce qu'il comprend l'anglais.\u003C\u002Fp>\n\u003Cp>Il a besoin d'une interface définie qui indique quelles actions existent, quels arguments elles acceptent et ce que l'outil renvoie.\u003C\u002Fp>\n\u003Cp>Les capacités intégrées actuelles de G-Assist incluent des fonctions telles que l'optimisation des paramètres graphiques, la modification des options RTX prises en charge, la vérification ou le téléchargement de pilotes, l'affichage d'informations de performance, la modification de certaines fonctionnalités d'alimentation des ordinateurs portables, le contrôle des fonctions d'écran prises en charge et l'utilisation de plug-ins de périphériques pris en charge.\u003C\u002Fp>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Modèle de langage vs outil\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\">Modèle de langage\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\">Outil \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\">Comprendre « activer 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\">Choisir la bonne fonction\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\">Modifier réellement le paramètre\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\">Expliquer le résultat\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\">Qu'est-ce que la couche de connaissances ?\u003C\u002Fh2>\n\u003Cp>G-Assist dispose également d'une couche de connaissances pour répondre aux questions et faire des recommandations.\u003C\u002Fp>\n\u003Cp>NVIDIA indique que la version 0.2.1 a introduit un système de connaissances amélioré qui aide G-Assist à formuler des recommandations de réglages plus précises.\u003C\u002Fp>\n\u003Cp>Cette couche de connaissances est différente de l'état en direct de votre PC.\u003C\u002Fp>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Connaissances vs état en direct du 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\">Connaissances\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\">État en direct\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\">Réglages du jeu\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\">Performance\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\">Ne mélangez pas les connaissances et l'état\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">\u003Cstrong>Les connaissances\u003C\u002Fstrong> indiquent à l'assistant ce que signifie une fonctionnalité ou ce qui compte généralement.\u003Cbr>\u003Cstrong>L'état\u003C\u002Fstrong> lui indique ce qui est vrai sur votre machine en ce moment.\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\">Qu'est-ce que le RAG ? L'explication la plus simple de son fonctionnement\u003C\u002Fstrong>\u003Cp class=\"mt-2 text-sm text-gray-600 dark:text-gray-300\">Une explication en langage clair de la récupération de connaissances, de l'état, de la mémoire, du contexte et du modèle de langage.\u003C\u002Fp>\u003Cspan class=\"mt-3 inline-flex text-sm font-medium text-primary-600 dark:text-primary-400\">Lire le guide simple sur le RAG →\u003C\u002Fspan>\u003C\u002Fdiv>\u003C\u002Fa>\u003C\u002Faside>\n\u003Ch2 id=\"section-24\">G-Assist utilise-t-il le RAG ?\u003C\u002Fh2>\n\u003Cp>La réponse la plus prudente est la suivante : G-Assist possède clairement un système de connaissances, mais la page produit publique de NVIDIA ne documente pas suffisamment en détail chaque mécanisme de récupération interne pour affirmer que chaque réponse de connaissances est spécifiquement produite par le RAG.\u003C\u002Fp>\n\u003Cp>La distinction architecturale reste importante. Une couche de récupération peut fournir des connaissances pertinentes, tandis que les outils système fournissent l'état actuel du PC et exécutent des actions.\u003C\u002Fp>\n\u003Cp>C'est la même séparation utilisée dans de nombreux agents modernes : les connaissances sont une source de contexte, les observations en direct en sont une autre, et l'exécution d'outils en est une troisième.\u003C\u002Fp>\n\u003Ch2 id=\"section-28\">Pourquoi G-Assist peut fonctionner hors ligne\u003C\u002Fh2>\n\u003Cp>NVIDIA exécute le modèle de langage localement sur le GPU GeForce RTX.\u003C\u002Fp>\n\u003Cp>Cela signifie que l'assistant principal ne nécessite pas de modèle de langage hébergé dans le cloud pour chaque requête.\u003C\u002Fp>\n\u003Cp>NVIDIA déclare explicitement que G-Assist peut fonctionner hors ligne pour ses capacités locales.\u003C\u002Fp>\n\u003Cp>Un plug-in peut toujours utiliser Internet si ce plug-in appelle un service en ligne. L'exécution locale du modèle et l'accès en ligne des plug-ins sont deux questions distinctes.\u003C\u002Fp>\n\u003Ch2 id=\"section-33\">Le coût de l'IA locale : G-Assist utilise votre GPU et votre VRAM\u003C\u002Fh2>\n\u003Cp>L'exécution locale offre la confidentialité et l'indépendance vis-à-vis d'un modèle cloud, mais le travail doit s'exécuter quelque part.\u003C\u002Fp>\n\u003Cp>Pour G-Assist, ce quelque part est le même GPU GeForce RTX qui est peut-être déjà en train de rendre votre jeu.\u003C\u002Fp>\n\u003Cp>NVIDIA avertit que le GPU alloue brièvement des ressources de calcul à l'inférence IA lorsque G-Assist répond. Si un jeu exigeant tourne en même temps, le jeu peut temporairement perdre une partie de ses performances de rendu pendant que le modèle est actif.\u003C\u002Fp>\n\u003Cp>Les exigences actuelles spécifient également des cibles de VRAM libre au-delà de la mémoire déjà utilisée par le jeu : environ 6 Go de VRAM libre pour le mode Reasoning et 4,5 Go pour le mode 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 Go de VRAM ne signifie pas que 8 Go sont disponibles pour G-Assist\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">Le jeu, Windows, le pilote et d'autres applications consomment déjà de la VRAM. L'exigence propre de G-Assist concerne la \u003Cstrong>VRAM libre en plus de ce que la charge de travail en cours utilise déjà\u003C\u002Fstrong>.\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Caside class=\"editorjs-referral my-6\">\u003Ca href=\"https:\u002F\u002Ffigure.rocks\u002Ffr\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'utilisation de la VRAM n'est pas une exigence de VRAM : pourquoi une jauge de mémoire pleine ne raconte pas toute l'histoire\u003C\u002Fstrong>\u003Cp class=\"mt-2 text-sm text-gray-600 dark:text-gray-300\">Pourquoi la VRAM installée, l'utilisation actuelle, les budgets de résidence et la pression mémoire réelle sont des choses différentes.\u003C\u002Fp>\u003Cspan class=\"mt-3 inline-flex text-sm font-medium text-primary-600 dark:text-primary-400\">Lire le guide de la VRAM →\u003C\u002Fspan>\u003C\u002Fdiv>\u003C\u002Fa>\u003C\u002Faside>\n\u003Ch2 id=\"section-40\">Mode Reasoning vs mode Flash\u003C\u002Fh2>\n\u003Cp>Les versions actuelles de G-Assist séparent un mode Reasoning plus capable d'un mode Flash plus rapide.\u003C\u002Fp>\n\u003Cp>Le mode Reasoning est conçu pour des décisions de meilleure qualité et peut coordonner plusieurs actions à partir d'une seule invite. Le mode Flash est optimisé pour des réponses plus rapides et une demande de ressources moindre.\u003C\u002Fp>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Mode Reasoning vs mode 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\">Mode Reasoning\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\">Mode 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\">Objectif principal\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 libre recommandée\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\">Idéal pour\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\">Ce que les plug-ins ajoutent réellement\u003C\u002Fh2>\n\u003Cp>Un plug-in ne remplace pas le modèle de langage. Il donne au modèle une nouvelle action qu'il est autorisé à appeler.\u003C\u002Fp>\n\u003Cp>Le plug-in définit des fonctions, des descriptions et des paramètres. G-Assist lit ces descriptions, fait correspondre une demande de l'utilisateur à la fonction appropriée et lui envoie des arguments structurés.\u003C\u002Fp>\n\u003Cp>Cela permet à l'assistant de dépasser les fonctions intégrées de NVIDIA.\u003C\u002Fp>\n\u003Csection class=\"editorjs-process my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Comment fonctionne un plug-in 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. Le plug-in déclare une fonction\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Par exemple : 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. Le manifeste décrit la fonction\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Le manifeste indique à G-Assist ce que fait la fonction et quels paramètres elle nécessite.\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'utilisateur demande naturellement\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Par exemple : « Rends mon clavier vert. »\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. Le SLM sélectionne la fonction\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Le modèle associe la demande à la fonction du plug-in et extrait vert comme paramètre.\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. Le plug-in s'exécute\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Le plug-in communique avec le logiciel du périphérique ou le service externe.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-49\">Le protocole G-Assist V2 est JSON-RPC 2.0\u003C\u002Fh2>\n\u003Cp>Le dépôt public actuel de plug-ins de NVIDIA utilise le protocole V2.\u003C\u002Fp>\n\u003Cp>Le protocole V2 utilise JSON-RPC 2.0 avec des messages préfixés par leur longueur entre le moteur G-Assist et les plug-ins.\u003C\u002Fp>\n\u003Cp>Le moteur peut initialiser un plug-in, vérifier son état, exécuter une fonction, envoyer une entrée utilisateur et l'arrêter. Les plug-ins peuvent renvoyer des résultats, diffuser la progression ou signaler des erreurs.\u003C\u002Fp>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Les messages importants du protocole 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\">Direction\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\">Objectif\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\">Où MCP entre en jeu\u003C\u002Fh2>\n\u003Cp>Le propre protocole de plug-in de G-Assist n'est pas MCP. Son système actuel de plug-ins publics utilise JSON-RPC 2.0.\u003C\u002Fp>\n\u003Cp>Cependant, un plug-in G-Assist peut se connecter à un serveur MCP.\u003C\u002Fp>\n\u003Cp>La version actuelle 0.2.2 de NVIDIA inclut une intégration Elgato qui peut invoquer des actions exposées via le serveur MCP 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\">Distinction importante des protocoles\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">\u003Cstrong>G-Assist ↔ son plug-in :\u003C\u002Fstrong> NVIDIA Protocol V2 \u002F JSON-RPC 2.0.\u003Cbr>\u003Cstrong>Plug-in ↔ un autre écosystème d'outils :\u003C\u002Fstrong> peut utiliser MCP lorsque cette intégration le prend en charge.\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Ch2 id=\"section-59\">Pourquoi cela compte au-delà des lumières RGB\u003C\u002Fh2>\n\u003Cp>L'architecture de plug-in transforme G-Assist d'un assistant fixe en un routeur d'outils local.\u003C\u002Fp>\n\u003Cp>Le même modèle peut connecter un SLM à des outils de surveillance, des périphériques, des API, des systèmes d'automatisation, des applications locales ou des services externes.\u003C\u002Fp>\n\u003Cp>L'unité architecturale importante n'est donc pas la fenêtre de chat. C'est la frontière entre l'intention en langage naturel et l'exécution structurée des outils.\u003C\u002Fp>\n\u003Ch2 id=\"section-63\">La pile d'agents locaux\u003C\u002Fh2>\n\u003Csection class=\"editorjs-process my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Une façon utile de penser à 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. Intention de l'utilisateur\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Commande en langage naturel ou 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 local\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Comprend la demande et choisit une capacité.\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. Connaissances \u002F contexte\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Fournit les connaissances produit, les recommandations ou les informations nécessaires à la décision.\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. État du système en direct\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Fournit les informations actuelles sur le matériel, les pilotes, les performances ou la configuration lorsque cela est pris en charge.\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. Sélection d'outil\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Une fonction intégrée ou un plug-in est choisi.\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. Exécution structurée\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">La fonction reçoit des arguments et effectue l'action réelle.\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. Vérification du résultat\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">L'outil renvoie un statut ou des données et le modèle explique ce qui s'est passé.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-65\">Pourquoi les frontières des outils sont une fonction de sécurité\u003C\u002Fh2>\n\u003Cp>Un assistant IA qui pourrait exécuter des commandes arbitraires du système d'exploitation serait bien plus puissant, mais aussi beaucoup plus difficile à contraindre.\u003C\u002Fp>\n\u003Cp>G-Assist expose plutôt des fonctions définies avec des paramètres connus.\u003C\u002Fp>\n\u003Cp>Cela signifie que le modèle ne peut effectuer que les actions que l'ensemble des fonctions intégrées ou les plug-ins installés rendent disponibles.\u003C\u002Fp>\n\u003Cp>Cela n'élimine pas tous les risques, en particulier avec les plug-ins tiers, mais cela crée une frontière de permission et de capacité plus claire qu'un accès shell non restreint.\u003C\u002Fp>\n\u003Ch2 id=\"section-70\">La frontière d'autorité des outils\u003C\u002Fh2>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Ce que l'assistant peut comprendre vs ce qu'il est autorisé à faire\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\">Le modèle peut comprendre\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\">Autorité de l'outil\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\">Réglage 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\">Fichiers\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\">Contrôle des périphériques\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\">Pourquoi G-Assist peut temporairement réduire les performances de jeu\u003C\u002Fh2>\n\u003Cp>L'architecture de modèle local a une conséquence directe : l'IA et le jeu peuvent se disputer le même GPU.\u003C\u002Fp>\n\u003Cp>NVIDIA avertit explicitement que le taux de rendu ou la vitesse d'inférence peut brièvement chuter pendant que G-Assist traite une requête lors d'une charge de travail GPU intensive.\u003C\u002Fp>\n\u003Cp>Une fois l'inférence terminée, ces ressources GPU reviennent au jeu.\u003C\u002Fp>\n\u003Cp>Cela diffère d'un assistant cloud, où la plupart de l'inférence du modèle se produit sur un serveur distant et ne consomme pas le GPU de jeu.\u003C\u002Fp>\n\u003Ch2 id=\"section-77\">Le test des ressources de l'assistant local\u003C\u002Fh2>\n\u003Csection class=\"editorjs-process my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Comment juger si un assistant de jeu local convient à votre 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. Vérifier la VRAM installée\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">La configuration de base actuelle de G-Assist est un GPU RTX avec au moins 6 Go de 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. Vérifier la VRAM libre pendant le jeu réel\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">La capacité installée n'est pas la même que la capacité libre.\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. Choisir le mode Raisonnement ou Flash de manière appropriée\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Utilisez le mode plus léger lorsque la pression sur les ressources importe plus que le raisonnement approfondi.\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. Mesurer les baisses de fréquence d'images pendant l'inférence\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Surveillez le jeu tout en demandant à G-Assist d'effectuer des tâches.\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. Inspecter l'autorité des outils\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Sachez exactement quelles fonctions intégrées et quels plug-ins peuvent modifier votre système.\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. Traiter les plug-ins tiers comme des logiciels\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Examinez leur source, leurs permissions, leur accès réseau et leurs identifiants stockés.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-79\">Pourquoi les plug-ins méritent le même examen que tout autre logiciel\u003C\u002Fh2>\n\u003Cp>Un plug-in peut connecter l'assistant à des API, des applications périphériques et des services en ligne.\u003C\u002Fp>\n\u003Cp>Cela signifie qu'un plug-in peut gérer des valeurs de configuration, des identifiants ou des requêtes externes selon ce pour quoi il a été conçu.\u003C\u002Fp>\n\u003Cp>Le dépôt de NVIDIA fournit explicitement un emplacement config.json pour les paramètres des plug-ins et avertit les développeurs de ne pas valider les identifiants.\u003C\u002Fp>\n\u003Cp>La bonne question de sécurité n'est donc pas seulement « G-Assist est-il local ? » mais aussi « À quoi se connecte chaque plug-in installé ? »\u003C\u002Fp>\n\u003Ch2 id=\"section-84\">G-Assist est plus proche d'un agent que d'un chatbot\u003C\u002Fh2>\n\u003Cp>Un chatbot produit principalement du langage.\u003C\u002Fp>\n\u003Cp>Un agent interprète un objectif, observe les informations pertinentes, choisit une action, appelle un outil et évalue le résultat.\u003C\u002Fp>\n\u003Cp>G-Assist correspond désormais beaucoup plus étroitement à cette seconde description, car il peut coordonner plusieurs actions, inspecter l'état pris en charge du PC et invoquer de véritables outils.\u003C\u002Fp>\n\u003Caside class=\"editorjs-referral my-6\">\u003Ca href=\"https:\u002F\u002Ffigure.rocks\u002Ffr\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 montre pourquoi les coéquipiers IA ont besoin de deux cerveaux : des réflexes rapides et un raisonnement lent\u003C\u002Fstrong>\u003Cp class=\"mt-2 text-sm text-gray-600 dark:text-gray-300\">Un exemple d'architecture d'agent de jeu montrant la séparation entre le raisonnement, l'état en direct, les outils et l'exécution déterministe.\u003C\u002Fp>\u003Cspan class=\"mt-3 inline-flex text-sm font-medium text-primary-600 dark:text-primary-400\">Lire le guide d'architecture de PUBG Ally →\u003C\u002Fspan>\u003C\u002Fdiv>\u003C\u002Fa>\u003C\u002Faside>\n\u003Ch2 id=\"section-89\">Ce que G-Assist n'est toujours pas\u003C\u002Fh2>\n\u003Cp>NVIDIA décrit explicitement G-Assist comme un assistant local spécialisé, et non comme une IA conversationnelle polyvalente.\u003C\u002Fp>\n\u003Cp>Sa valeur vient de la compréhension d'un ensemble ciblé de tâches PC et de gaming et de la présence d'outils connectés à ces tâches.\u003C\u002Fp>\n\u003Cp>Cette focalisation est importante car un modèle local plus petit peut être utile lorsque le système environnant lui fournit des outils puissants et des limites claires.\u003C\u002Fp>\n\u003Ch2 id=\"section-93\">Qu'est-ce qui a changé dans les versions actuelles ?\u003C\u002Fh2>\n\u003Cp>L'historique des versions publiques actuelles montre que G-Assist évolue régulièrement vers un agent local plus performant.\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\">Version\u003C\u002Fth>\u003Cth class=\"border border-gray-300 px-4 py-2 text-left font-semibold\">Changement important\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\">Modèle plus léger, toutes les GPU RTX avec 6 Go+ de VRAM, plug-ins communautaires\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\">Optimisation pour ordinateurs portables, contrôles BatteryBoost et 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\">Mode raisonnement, mode Flash, invites multi-actions, nouveaux contrôles d'appareils\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\">Système de connaissances amélioré, meilleures recommandations, contrôles des fonctionnalités 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\">Intégration Elgato Stream Deck via un serveur MCP\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003C\u002Fdiv>\n\u003Ch2 id=\"section-96\">Qu'est-ce qui pourrait changer cette réponse ?\u003C\u002Fh2>\n\u003Cp>G-Assist est encore expérimental et son architecture évolue.\u003C\u002Fp>\n\u003Cp>La taille du modèle, les exigences de VRAM, l'ensemble d'outils, le protocole de plug-in et la prise en charge matérielle peuvent tous changer dans les futures versions.\u003C\u002Fp>\n\u003Cp>Une future version pourrait également déplacer une partie de l'inférence vers un NPU ou introduire une intégration MCP plus large, mais cela ne doit pas être supposé tant que NVIDIA ne le documente pas.\u003C\u002Fp>\n\u003Ch2 id=\"section-100\">Limites\u003C\u002Fh2>\n\u003Cp>Cet article décrit la documentation publique du produit G-Assist de NVIDIA et l'architecture publique des plug-ins en date de septembre 2026.\u003C\u002Fp>\n\u003Cp>NVIDIA ne documente pas publiquement chaque détail interne de son pipeline de connaissances et de recommandations, donc cet article ne prétend pas que chaque réponse de connaissances utilise RAG ou toute autre implémentation de récupération spécifique.\u003C\u002Fp>\n\u003Cp>Les plug-ins tiers peuvent avoir un comportement et un accès réseau au-delà des fonctions intégrées de NVIDIA, donc chaque plug-in doit être évalué séparément.\u003C\u002Fp>\n\u003Ch2 id=\"section-104\">Conclusion\u003C\u002Fh2>\n\u003Cp>La façon la plus simple de comprendre Project G-Assist est d'arrêter de le considérer comme un chatbot.\u003C\u002Fp>\n\u003Cp>Le SLM local interprète votre demande. Les connaissances l'aident à comprendre le problème. Les informations système en direct lui indiquent ce qui est vrai sur votre PC. Une fonction intégrée ou un plug-in définit ce qu'il est réellement autorisé à faire. L'outil effectue l'action et renvoie le résultat.\u003C\u002Fp>\n\u003Cp>C'est une architecture d'agent local.\u003C\u002Fp>\n\u003Cp>Son idée la plus forte n'est pas qu'un modèle de 8 milliards de paramètres puisse parler de votre GPU. C'est qu'un modèle local relativement petit peut devenir utile lorsqu'il est connecté à des outils bien définis, à l'état actuel et à une frontière d'action contrôlée.\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 en clair\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 est-il un chatbot cloud ?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Non. Son modèle de langage principal s'exécute localement sur le GPU GeForce RTX et peut fonctionner hors ligne pour les fonctions locales prises en charge.\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\">Quel modèle G-Assist utilise-t-il ?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">NVIDIA le décrit actuellement comme un modèle instruct local basé sur Llama avec 8 milliards de paramètres.\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\">Le modèle d'IA modifie-t-il directement les paramètres de mon GPU ?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Non. Le modèle sélectionne une fonction intégrée ou un plug-in pris en charge, et cet outil effectue la modification réelle.\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 utilise-t-il de la VRAM pendant le jeu ?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Oui. NVIDIA recommande de la VRAM libre supplémentaire pour l'assistant et avertit que l'inférence peut réduire brièvement les performances de rendu du jeu.\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\">Les plug-ins G-Assist sont-ils des plug-ins MCP ?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Pas directement. Le protocole de plug-in actuel de G-Assist utilise JSON-RPC 2.0, bien qu'un plug-in puisse se connecter à un serveur 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 peut-il fonctionner hors ligne ?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Son assistant local le peut, mais les plug-ins individuels peuvent encore nécessiter un accès Internet s'ils appellent des services en ligne.\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 est-il un assistant IA généraliste ?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">NVIDIA le décrit comme un assistant spécialisé pour PC et jeux plutôt qu'un modèle conversationnel généraliste polyvalent.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-111\">Glossaire\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\">Termes clés de 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 modèle de langage compact conçu pour s'exécuter localement avec des exigences matérielles inférieures à celles des grands modèles 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\">Appel d'outils\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Le processus par lequel un modèle de langage choisit une fonction définie et fournit des arguments structurés afin qu'un autre composant puisse effectuer une action.\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\">Une extension qui expose des fonctions ou des intégrations supplémentaires à 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\">Le protocole de messages structurés utilisé par le système de plug-ins actuel 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 protocole distinct d'interopérabilité d'outils et de contexte que certaines intégrations externes peuvent exposer.\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\">Frontière outil-autorité\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Un modèle Figure Rocks séparant ce qu'un modèle d'IA peut comprendre de ce que ses outils connectés lui permettent réellement de faire.\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\">Pile d'agents locaux\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Un modèle Figure Rocks combinant l'intention de l'utilisateur, le SLM local, les connaissances, l'état en direct, la sélection d'outils, l'exécution et la vérification des résultats.\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\">Test de ressources de l'assistant local\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Un flux de travail Figure Rocks pour évaluer la VRAM, le coût d'inférence, les autorisations d'outils et le risque des plug-ins avant d'utiliser un assistant de jeu local.\u003C\u002Fdd>\u003C\u002Fdiv>\u003C\u002Fdl>\u003C\u002Fsection>\n\u003Ch2 id=\"section-113\">Sources principales\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\">Page produit officielle actuelle couvrant le modèle local, les fonctions prises en charge, les modes Reasoning et Flash, les exigences de VRAM, les contrôles RTX, les plug-ins et l'intégration Elgato basée sur MCP version 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\">Dépôt public officiel de plug-ins documentant l'architecture des modules de G-Assist, la découverte des plug-ins et le 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 — Guide de migration vers G-Assist Protocol V2\u003C\u002Fstrong>\u003Cp class=\"text-sm text-gray-600 dark:text-gray-400\">Documentation officielle du protocole couvrant JSON-RPC 2.0, l'initialisation, les contrôles de santé, l'exécution, le streaming, l'achèvement et le comportement du SDK de 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\">Blog NVIDIA — Modèle G-Assist léger\u003C\u002Fstrong>\u003Cp class=\"text-sm text-gray-600 dark:text-gray-400\">Contexte officiel sur le modèle G-Assist à mémoire réduite, la prise en charge des GPU RTX de 6 Go et le hub de plug-ins communautaire.\u003C\u002Fp>\u003C\u002Fa>",{"time":538,"blocks":539,"version":1438},1790407950121,[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 ressemble à un chatbot, mais cette description passe à côté de l'essentiel. Il s'agit d'un système d'IA local capable de comprendre une requête, d'inspecter l'état pris en charge du PC, de choisir un outil ou un plug-in, puis d'effectuer une action réelle comme modifier les paramètres DLSS, vérifier un pilote, ajuster un profil de ventilateur ou contrôler un périphérique.","paragraph",{},{"id":547,"data":548,"type":552,"tunes":553},"24a1733ca8",{"body":549,"title":550,"variant":551},"\u003Cstrong>G-Assist n'est pas simplement un chatbot pour votre GPU.\u003C\u002Fstrong> C'est un petit modèle de langage local connecté à un ensemble d'outils autorisés. Le modèle interprète ce que vous voulez, sélectionne une fonction prise en charge, transmet des arguments à cette fonction, et l'outil côté PC exécute l'action.","Réponse directe","info","callout",{},{"id":555,"data":556,"type":552,"tunes":560},"1fcbe512dc",{"body":557,"title":558,"variant":559},"\u003Cstrong>SLM = comprend la requête.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Connaissances = explique les concepts NVIDIA\u002FPC pris en charge.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Outils = effectuent des actions.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Plug-ins = ajoutent de nouveaux outils.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Votre PC = l'environnement inspecté ou modifié.\u003C\u002Fstrong>","Le modèle mental le plus simple","note",{},{"id":562,"data":563,"type":566,"tunes":567},"2a609230a5",{"title":564,"maxLevel":565,"minLevel":47},"Sommaire",3,"tableOfContents",{},{"id":569,"data":570,"type":572,"tunes":573},"a52f97cb62",{"text":571,"level":47},"D'abord : que fait réellement le modèle d'IA ?","header",{},{"id":575,"data":576,"type":544,"tunes":578},"1871a0d8e6",{"text":577},"G-Assist utilise un petit modèle de langage local, ou SLM. NVIDIA décrit actuellement le système comme utilisant un modèle instruct basé sur Llama de 8 milliards de paramètres.",{},{"id":580,"data":581,"type":544,"tunes":583},"cfbc6473c4",{"text":582},"Le rôle principal du modèle n'est pas de rendre des graphiques ou de modifier directement les registres matériels. Son rôle est de comprendre le langage de l'utilisateur, de décider quelle capacité prise en charge correspond à la requête, et de préparer l'appel à cette capacité.",{},{"id":585,"data":586,"type":544,"tunes":588},"53cadaaeb6",{"text":587},"Par exemple, si vous dites « définir DLSS Super Resolution en mode Performance », le modèle de langage ne modifie pas lui-même DLSS. Il interprète la commande et la dirige vers la fonction prise en charge qui peut modifier le paramètre.",{},{"id":590,"data":591,"type":552,"tunes":595},"5d8e508019",{"body":592,"title":593,"variant":594},"Le modèle d'IA \u003Cstrong>décide quel outil appeler\u003C\u002Fstrong>. L'outil \u003Cstrong>fait le vrai travail\u003C\u002Fstrong>.","La distinction importante","success",{},{"id":597,"data":598,"type":572,"tunes":600},"9ce7e91c28",{"text":599,"level":47},"Le pipeline d'action de 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. Vous donnez une requête en langage naturel","Par exemple : « Optimise ce jeu pour la performance. »",{"label":609,"description":610},"2. Le SLM local interprète la requête","Il détermine l'intention de l'utilisateur et identifie quelle fonction ou plug-in pris en charge est pertinent.",{"label":612,"description":613},"3. Le système choisit un outil","Cela peut être une fonction intégrée de paramètres graphiques, une vérification de pilote, une fonction de surveillance ou un plug-in communautaire.",{"label":615,"description":616},"4. Les arguments sont extraits","Le modèle convertit la requête en valeurs structurées telles que le nom du jeu, le mode, le profil de ventilateur ou le paramètre DLSS.",{"label":618,"description":619},"5. L'outil s'exécute","L'outil communique avec l'application NVIDIA, le système d'exploitation, le logiciel du périphérique ou un autre service.",{"label":621,"description":622},"6. Le résultat est renvoyé","G-Assist rapporte ce qui s'est passé, ou renvoie des données que le modèle peut expliquer.","Ce qui se passe après avoir donné une commande à G-Assist","auto","processFlow",{},{"id":628,"data":629,"type":572,"tunes":631},"aba1e38958",{"text":630,"level":47},"C'est de l'appel d'outils, pas du contrôle magique du PC",{},{"id":633,"data":634,"type":544,"tunes":636},"0a7cb6107d",{"text":635},"Un modèle de langage ne peut pas contrôler en toute sécurité un ordinateur arbitraire simplement parce qu'il comprend l'anglais.",{},{"id":638,"data":639,"type":544,"tunes":641},"31191a478c",{"text":640},"Il a besoin d'une interface définie qui indique quelles actions existent, quels arguments elles acceptent et ce que l'outil renvoie.",{},{"id":643,"data":644,"type":544,"tunes":646},"af3d1a846f",{"text":645},"Les capacités intégrées actuelles de G-Assist incluent des fonctions telles que l'optimisation des paramètres graphiques, la modification des options RTX prises en charge, la vérification ou le téléchargement de pilotes, l'affichage d'informations de performance, la modification de certaines fonctionnalités d'alimentation des ordinateurs portables, le contrôle des fonctions d'écran prises en charge et l'utilisation de plug-ins de périphériques pris en charge.",{},{"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","Comprendre « activer DLSS »",[13,13],{"id":656,"label":657,"values":658},"decide","Choisir la bonne fonction",[13,13],{"id":660,"label":661,"values":662},"change","Modifier réellement le paramètre",[13,13],{"id":664,"label":665,"values":666},"explain","Expliquer le résultat",[13,13],"Modèle de langage vs outil","table",[670,673],{"id":671,"label":672},"model","Modèle de langage",{"id":674,"label":675},"tool","Outil \u002F plug-in","comparison",{},{"id":679,"data":680,"type":572,"tunes":682},"1537be641c",{"text":681,"level":47},"Qu'est-ce que la couche de connaissances ?",{},{"id":684,"data":685,"type":544,"tunes":687},"1db6e2e4b5",{"text":686},"G-Assist dispose également d'une couche de connaissances pour répondre aux questions et faire des recommandations.",{},{"id":689,"data":690,"type":544,"tunes":692},"616d72b881",{"text":691},"NVIDIA indique que la version 0.2.1 a introduit un système de connaissances amélioré qui aide G-Assist à formuler des recommandations de réglages plus précises.",{},{"id":694,"data":695,"type":544,"tunes":697},"eb987c41e5",{"text":696},"Cette couche de connaissances est différente de l'état en direct de votre 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","Réglages du jeu",[13,13],{"id":711,"label":712,"values":713},"system","Performance",[13,13],"Connaissances vs état en direct du PC",[716,719],{"id":717,"label":718},"knowledge","Connaissances",{"id":720,"label":721},"state","État en direct",{},{"id":724,"data":725,"type":552,"tunes":729},"2bac13ef99",{"body":726,"title":727,"variant":728},"\u003Cstrong>Les connaissances\u003C\u002Fstrong> indiquent à l'assistant ce que signifie une fonctionnalité ou ce qui compte généralement.\u003Cbr>\u003Cstrong>L'état\u003C\u002Fstrong> lui indique ce qui est vrai sur votre machine en ce moment.","Ne mélangez pas les connaissances et l'état","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","Qu'est-ce que le RAG ? L'explication la plus simple de son fonctionnement","Une explication en langage clair de la récupération de connaissances, de l'état, de la mémoire, du contexte et du modèle de langage.","Lire le guide simple sur le RAG","referralArticle",{},{"id":740,"data":741,"type":572,"tunes":743},"acbb9b7940",{"text":742,"level":47},"G-Assist utilise-t-il le RAG ?",{},{"id":745,"data":746,"type":544,"tunes":748},"ce0371e492",{"text":747},"La réponse la plus prudente est la suivante : G-Assist possède clairement un système de connaissances, mais la page produit publique de NVIDIA ne documente pas suffisamment en détail chaque mécanisme de récupération interne pour affirmer que chaque réponse de connaissances est spécifiquement produite par le RAG.",{},{"id":750,"data":751,"type":544,"tunes":753},"c2226e5ec5",{"text":752},"La distinction architecturale reste importante. Une couche de récupération peut fournir des connaissances pertinentes, tandis que les outils système fournissent l'état actuel du PC et exécutent des actions.",{},{"id":755,"data":756,"type":544,"tunes":758},"e5137fc2c8",{"text":757},"C'est la même séparation utilisée dans de nombreux agents modernes : les connaissances sont une source de contexte, les observations en direct en sont une autre, et l'exécution d'outils en est une troisième.",{},{"id":760,"data":761,"type":572,"tunes":763},"059b89dedb",{"text":762,"level":47},"Pourquoi G-Assist peut fonctionner hors ligne",{},{"id":765,"data":766,"type":544,"tunes":768},"19447df6a4",{"text":767},"NVIDIA exécute le modèle de langage localement sur le GPU GeForce RTX.",{},{"id":770,"data":771,"type":544,"tunes":773},"55aee6ada7",{"text":772},"Cela signifie que l'assistant principal ne nécessite pas de modèle de langage hébergé dans le cloud pour chaque requête.",{},{"id":775,"data":776,"type":544,"tunes":778},"f265d1fd96",{"text":777},"NVIDIA déclare explicitement que G-Assist peut fonctionner hors ligne pour ses capacités locales.",{},{"id":780,"data":781,"type":544,"tunes":783},"1dc8613200",{"text":782},"Un plug-in peut toujours utiliser Internet si ce plug-in appelle un service en ligne. L'exécution locale du modèle et l'accès en ligne des plug-ins sont deux questions distinctes.",{},{"id":785,"data":786,"type":572,"tunes":788},"ee01c97a66",{"text":787,"level":47},"Le coût de l'IA locale : G-Assist utilise votre GPU et votre VRAM",{},{"id":790,"data":791,"type":544,"tunes":793},"1784ad3fcf",{"text":792},"L'exécution locale offre la confidentialité et l'indépendance vis-à-vis d'un modèle cloud, mais le travail doit s'exécuter quelque part.",{},{"id":795,"data":796,"type":544,"tunes":798},"1275ab759f",{"text":797},"Pour G-Assist, ce quelque part est le même GPU GeForce RTX qui est peut-être déjà en train de rendre votre jeu.",{},{"id":800,"data":801,"type":544,"tunes":803},"cec86f847a",{"text":802},"NVIDIA avertit que le GPU alloue brièvement des ressources de calcul à l'inférence IA lorsque G-Assist répond. Si un jeu exigeant tourne en même temps, le jeu peut temporairement perdre une partie de ses performances de rendu pendant que le modèle est actif.",{},{"id":805,"data":806,"type":544,"tunes":808},"e6ea700df6",{"text":807},"Les exigences actuelles spécifient également des cibles de VRAM libre au-delà de la mémoire déjà utilisée par le jeu : environ 6 Go de VRAM libre pour le mode Reasoning et 4,5 Go pour le mode Flash.",{},{"id":810,"data":811,"type":552,"tunes":814},"2126f74de5",{"body":812,"title":813,"variant":728},"Le jeu, Windows, le pilote et d'autres applications consomment déjà de la VRAM. L'exigence propre de G-Assist concerne la \u003Cstrong>VRAM libre en plus de ce que la charge de travail en cours utilise déjà\u003C\u002Fstrong>.","8 Go de VRAM ne signifie pas que 8 Go sont disponibles pour G-Assist",{},{"id":816,"data":817,"type":737,"tunes":822},"13c0dcb3f3",{"url":818,"title":819,"excerpt":820,"ctaLabel":821},"https:\u002F\u002Ffigure.rocks\u002Ffr\u002Fblog\u002Fvram-usage-is-not-vram-requirement-why-a-full-memory-meter-does-not-tell-the-whole-story","L'utilisation de la VRAM n'est pas une exigence de VRAM : pourquoi une jauge de mémoire pleine ne raconte pas toute l'histoire","Pourquoi la VRAM installée, l'utilisation actuelle, les budgets de résidence et la pression mémoire réelle sont des choses différentes.","Lire le guide de la VRAM",{},{"id":824,"data":825,"type":572,"tunes":827},"d684b2c1c8",{"text":826,"level":47},"Mode Reasoning vs mode Flash",{},{"id":829,"data":830,"type":544,"tunes":832},"3c1f2379db",{"text":831},"Les versions actuelles de G-Assist séparent un mode Reasoning plus capable d'un mode Flash plus rapide.",{},{"id":834,"data":835,"type":544,"tunes":837},"86f50ebd33",{"text":836},"Le mode Reasoning est conçu pour des décisions de meilleure qualité et peut coordonner plusieurs actions à partir d'une seule invite. Le mode Flash est optimisé pour des réponses plus rapides et une demande de ressources moindre.",{},{"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","Objectif principal",[13,13],{"id":847,"label":848,"values":849},"vram","VRAM libre recommandée",[13,13],{"id":851,"label":852,"values":853},"use","Idéal pour",[13,13],[855,858],{"id":856,"label":857},"reasoning","Mode Reasoning",{"id":859,"label":860},"flash","Mode Flash",{},{"id":863,"data":864,"type":572,"tunes":866},"cef1bcf553",{"text":865,"level":47},"Ce que les plug-ins ajoutent réellement",{},{"id":868,"data":869,"type":544,"tunes":871},"d380d5e28b",{"text":870},"Un plug-in ne remplace pas le modèle de langage. Il donne au modèle une nouvelle action qu'il est autorisé à appeler.",{},{"id":873,"data":874,"type":544,"tunes":876},"434979ebda",{"text":875},"Le plug-in définit des fonctions, des descriptions et des paramètres. G-Assist lit ces descriptions, fait correspondre une demande de l'utilisateur à la fonction appropriée et lui envoie des arguments structurés.",{},{"id":878,"data":879,"type":544,"tunes":881},"21ebe69c79",{"text":880},"Cela permet à l'assistant de dépasser les fonctions intégrées de 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. Le plug-in déclare une fonction","Par exemple : set_keyboard_color(color).",{"label":890,"description":891},"2. Le manifeste décrit la fonction","Le manifeste indique à G-Assist ce que fait la fonction et quels paramètres elle nécessite.",{"label":893,"description":894},"3. L'utilisateur demande naturellement","Par exemple : « Rends mon clavier vert. »",{"label":896,"description":897},"4. Le SLM sélectionne la fonction","Le modèle associe la demande à la fonction du plug-in et extrait vert comme paramètre.",{"label":899,"description":900},"5. Le plug-in s'exécute","Le plug-in communique avec le logiciel du périphérique ou le service externe.","Comment fonctionne un plug-in G-Assist",{},{"id":904,"data":905,"type":572,"tunes":907},"1dc857ce2f",{"text":906,"level":47},"Le protocole G-Assist V2 est JSON-RPC 2.0",{},{"id":909,"data":910,"type":544,"tunes":912},"02bdb0566d",{"text":911},"Le dépôt public actuel de plug-ins de NVIDIA utilise le protocole V2.",{},{"id":914,"data":915,"type":544,"tunes":917},"f82da294cf",{"text":916},"Le protocole V2 utilise JSON-RPC 2.0 avec des messages préfixés par leur longueur entre le moteur G-Assist et les plug-ins.",{},{"id":919,"data":920,"type":544,"tunes":922},"530c3cf9b9",{"text":921},"Le moteur peut initialiser un plug-in, vérifier son état, exécuter une fonction, envoyer une entrée utilisateur et l'arrêter. Les plug-ins peuvent renvoyer des résultats, diffuser la progression ou signaler des erreurs.",{},{"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],"Les messages importants du protocole V2",[944,947],{"id":945,"label":946},"direction","Direction",{"id":948,"label":949},"purpose","Objectif",{},{"id":952,"data":953,"type":572,"tunes":955},"304fbd9944",{"text":954,"level":47},"Où MCP entre en jeu",{},{"id":957,"data":958,"type":544,"tunes":960},"fae73881e4",{"text":959},"Le propre protocole de plug-in de G-Assist n'est pas MCP. Son système actuel de plug-ins publics utilise JSON-RPC 2.0.",{},{"id":962,"data":963,"type":544,"tunes":965},"551d11710a",{"text":964},"Cependant, un plug-in G-Assist peut se connecter à un serveur MCP.",{},{"id":967,"data":968,"type":544,"tunes":970},"0537fb222a",{"text":969},"La version actuelle 0.2.2 de NVIDIA inclut une intégration Elgato qui peut invoquer des actions exposées via le serveur MCP Elgato Stream Deck.",{},{"id":972,"data":973,"type":552,"tunes":976},"760a86ad19",{"body":974,"title":975,"variant":594},"\u003Cstrong>G-Assist ↔ son plug-in :\u003C\u002Fstrong> NVIDIA Protocol V2 \u002F JSON-RPC 2.0.\u003Cbr>\u003Cstrong>Plug-in ↔ un autre écosystème d'outils :\u003C\u002Fstrong> peut utiliser MCP lorsque cette intégration le prend en charge.","Distinction importante des protocoles",{},{"id":978,"data":979,"type":572,"tunes":981},"bd182f72b0",{"text":980,"level":47},"Pourquoi cela compte au-delà des lumières RGB",{},{"id":983,"data":984,"type":544,"tunes":986},"d072506ce2",{"text":985},"L'architecture de plug-in transforme G-Assist d'un assistant fixe en un routeur d'outils local.",{},{"id":988,"data":989,"type":544,"tunes":991},"2876e067dc",{"text":990},"Le même modèle peut connecter un SLM à des outils de surveillance, des périphériques, des API, des systèmes d'automatisation, des applications locales ou des services externes.",{},{"id":993,"data":994,"type":544,"tunes":996},"37689640e9",{"text":995},"L'unité architecturale importante n'est donc pas la fenêtre de chat. C'est la frontière entre l'intention en langage naturel et l'exécution structurée des outils.",{},{"id":998,"data":999,"type":572,"tunes":1001},"550fbb42d4",{"text":1000,"level":47},"La pile d'agents locaux",{},{"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. Intention de l'utilisateur","Commande en langage naturel ou vocale.",{"label":1010,"description":1011},"2. SLM local","Comprend la demande et choisit une capacité.",{"label":1013,"description":1014},"3. Connaissances \u002F contexte","Fournit les connaissances produit, les recommandations ou les informations nécessaires à la décision.",{"label":1016,"description":1017},"4. État du système en direct","Fournit les informations actuelles sur le matériel, les pilotes, les performances ou la configuration lorsque cela est pris en charge.",{"label":1019,"description":1020},"5. Sélection d'outil","Une fonction intégrée ou un plug-in est choisi.",{"label":1022,"description":1023},"6. Exécution structurée","La fonction reçoit des arguments et effectue l'action réelle.",{"label":1025,"description":1026},"7. Vérification du résultat","L'outil renvoie un statut ou des données et le modèle explique ce qui s'est passé.","Une façon utile de penser à G-Assist",{},{"id":1030,"data":1031,"type":572,"tunes":1033},"6c976db763",{"text":1032,"level":47},"Pourquoi les frontières des outils sont une fonction de sécurité",{},{"id":1035,"data":1036,"type":544,"tunes":1038},"ba65a3b467",{"text":1037},"Un assistant IA qui pourrait exécuter des commandes arbitraires du système d'exploitation serait bien plus puissant, mais aussi beaucoup plus difficile à contraindre.",{},{"id":1040,"data":1041,"type":544,"tunes":1043},"a932df9663",{"text":1042},"G-Assist expose plutôt des fonctions définies avec des paramètres connus.",{},{"id":1045,"data":1046,"type":544,"tunes":1048},"7d1d45c83d",{"text":1047},"Cela signifie que le modèle ne peut effectuer que les actions que l'ensemble des fonctions intégrées ou les plug-ins installés rendent disponibles.",{},{"id":1050,"data":1051,"type":544,"tunes":1053},"10460fda21",{"text":1052},"Cela n'élimine pas tous les risques, en particulier avec les plug-ins tiers, mais cela crée une frontière de permission et de capacité plus claire qu'un accès shell non restreint.",{},{"id":1055,"data":1056,"type":572,"tunes":1058},"25049448ea",{"text":1057,"level":47},"La frontière d'autorité des outils",{},{"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},"Réglage GPU",[13,13],{"id":1067,"label":1068,"values":1069},"files","Fichiers",[13,13],{"id":1071,"label":1072,"values":1073},"web","Internet",[13,13],{"id":1075,"label":1076,"values":1077},"device","Contrôle des périphériques",[13,13],"Ce que l'assistant peut comprendre vs ce qu'il est autorisé à faire",[1080,1082],{"id":652,"label":1081},"Le modèle peut comprendre",{"id":1083,"label":1084},"authority","Autorité de l'outil",{},{"id":1087,"data":1088,"type":572,"tunes":1090},"8fd8e35c51",{"text":1089,"level":47},"Pourquoi G-Assist peut temporairement réduire les performances de jeu",{},{"id":1092,"data":1093,"type":544,"tunes":1095},"f75234546f",{"text":1094},"L'architecture de modèle local a une conséquence directe : l'IA et le jeu peuvent se disputer le même GPU.",{},{"id":1097,"data":1098,"type":544,"tunes":1100},"28bc054afa",{"text":1099},"NVIDIA avertit explicitement que le taux de rendu ou la vitesse d'inférence peut brièvement chuter pendant que G-Assist traite une requête lors d'une charge de travail GPU intensive.",{},{"id":1102,"data":1103,"type":544,"tunes":1105},"0823573513",{"text":1104},"Une fois l'inférence terminée, ces ressources GPU reviennent au jeu.",{},{"id":1107,"data":1108,"type":544,"tunes":1110},"905eed843d",{"text":1109},"Cela diffère d'un assistant cloud, où la plupart de l'inférence du modèle se produit sur un serveur distant et ne consomme pas le GPU de jeu.",{},{"id":1112,"data":1113,"type":572,"tunes":1115},"839c0e3988",{"text":1114,"level":47},"Le test des ressources de l'assistant local",{},{"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. Vérifier la VRAM installée","La configuration de base actuelle de G-Assist est un GPU RTX avec au moins 6 Go de VRAM.",{"label":1124,"description":1125},"2. Vérifier la VRAM libre pendant le jeu réel","La capacité installée n'est pas la même que la capacité libre.",{"label":1127,"description":1128},"3. Choisir le mode Raisonnement ou Flash de manière appropriée","Utilisez le mode plus léger lorsque la pression sur les ressources importe plus que le raisonnement approfondi.",{"label":1130,"description":1131},"4. Mesurer les baisses de fréquence d'images pendant l'inférence","Surveillez le jeu tout en demandant à G-Assist d'effectuer des tâches.",{"label":1133,"description":1134},"5. Inspecter l'autorité des outils","Sachez exactement quelles fonctions intégrées et quels plug-ins peuvent modifier votre système.",{"label":1136,"description":1137},"6. Traiter les plug-ins tiers comme des logiciels","Examinez leur source, leurs permissions, leur accès réseau et leurs identifiants stockés.","Comment juger si un assistant de jeu local convient à votre PC",{},{"id":1141,"data":1142,"type":572,"tunes":1144},"ca52c48d2e",{"text":1143,"level":47},"Pourquoi les plug-ins méritent le même examen que tout autre logiciel",{},{"id":1146,"data":1147,"type":544,"tunes":1149},"8e6a760529",{"text":1148},"Un plug-in peut connecter l'assistant à des API, des applications périphériques et des services en ligne.",{},{"id":1151,"data":1152,"type":544,"tunes":1154},"be793240e1",{"text":1153},"Cela signifie qu'un plug-in peut gérer des valeurs de configuration, des identifiants ou des requêtes externes selon ce pour quoi il a été conçu.",{},{"id":1156,"data":1157,"type":544,"tunes":1159},"3c6c4c9aaf",{"text":1158},"Le dépôt de NVIDIA fournit explicitement un emplacement config.json pour les paramètres des plug-ins et avertit les développeurs de ne pas valider les identifiants.",{},{"id":1161,"data":1162,"type":544,"tunes":1164},"03413f935a",{"text":1163},"La bonne question de sécurité n'est donc pas seulement « G-Assist est-il local ? » mais aussi « À quoi se connecte chaque plug-in installé ? »",{},{"id":1166,"data":1167,"type":572,"tunes":1169},"f473162e86",{"text":1168,"level":47},"G-Assist est plus proche d'un agent que d'un chatbot",{},{"id":1171,"data":1172,"type":544,"tunes":1174},"59dd3df9c2",{"text":1173},"Un chatbot produit principalement du langage.",{},{"id":1176,"data":1177,"type":544,"tunes":1179},"188cb4bb40",{"text":1178},"Un agent interprète un objectif, observe les informations pertinentes, choisit une action, appelle un outil et évalue le résultat.",{},{"id":1181,"data":1182,"type":544,"tunes":1184},"117d1032f1",{"text":1183},"G-Assist correspond désormais beaucoup plus étroitement à cette seconde description, car il peut coordonner plusieurs actions, inspecter l'état pris en charge du PC et invoquer de véritables outils.",{},{"id":1186,"data":1187,"type":737,"tunes":1192},"ef132fc518",{"url":1188,"title":1189,"excerpt":1190,"ctaLabel":1191},"https:\u002F\u002Ffigure.rocks\u002Ffr\u002Fblog\u002Fpubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning","PUBG Ally montre pourquoi les coéquipiers IA ont besoin de deux cerveaux : des réflexes rapides et un raisonnement lent","Un exemple d'architecture d'agent de jeu montrant la séparation entre le raisonnement, l'état en direct, les outils et l'exécution déterministe.","Lire le guide d'architecture de PUBG Ally",{},{"id":1194,"data":1195,"type":572,"tunes":1197},"9f8fa308a5",{"text":1196,"level":47},"Ce que G-Assist n'est toujours pas",{},{"id":1199,"data":1200,"type":544,"tunes":1202},"f5f24e8aa3",{"text":1201},"NVIDIA décrit explicitement G-Assist comme un assistant local spécialisé, et non comme une IA conversationnelle polyvalente.",{},{"id":1204,"data":1205,"type":544,"tunes":1207},"e4d187593f",{"text":1206},"Sa valeur vient de la compréhension d'un ensemble ciblé de tâches PC et de gaming et de la présence d'outils connectés à ces tâches.",{},{"id":1209,"data":1210,"type":544,"tunes":1212},"0c1b7f8948",{"text":1211},"Cette focalisation est importante car un modèle local plus petit peut être utile lorsque le système environnant lui fournit des outils puissants et des limites claires.",{},{"id":1214,"data":1215,"type":572,"tunes":1217},"79a5920e77",{"text":1216,"level":47},"Qu'est-ce qui a changé dans les versions actuelles ?",{},{"id":1219,"data":1220,"type":544,"tunes":1222},"e78d96ef6c",{"text":1221},"L'historique des versions publiques actuelles montre que G-Assist évolue régulièrement vers un agent local plus performant.",{},{"id":1224,"data":1225,"type":668,"tunes":1246},"87dd1d3d3c",{"content":1226,"stretched":1245,"withHeadings":15},[1227,1230,1233,1236,1239,1242],[1228,1229],"Version","Changement important",[1231,1232],"0.1.17","Modèle plus léger, toutes les GPU RTX avec 6 Go+ de VRAM, plug-ins communautaires",[1234,1235],"0.1.18","Optimisation pour ordinateurs portables, contrôles BatteryBoost et WhisperMode",[1237,1238],"0.2","Mode raisonnement, mode Flash, invites multi-actions, nouveaux contrôles d'appareils",[1240,1241],"0.2.1","Système de connaissances amélioré, meilleures recommandations, contrôles des fonctionnalités RTX",[1243,1244],"0.2.2","Intégration Elgato Stream Deck via un serveur MCP",false,{},{"id":1248,"data":1249,"type":572,"tunes":1251},"09bde21a8d",{"text":1250,"level":47},"Qu'est-ce qui pourrait changer cette réponse ?",{},{"id":1253,"data":1254,"type":544,"tunes":1256},"b0e7ca01a4",{"text":1255},"G-Assist est encore expérimental et son architecture évolue.",{},{"id":1258,"data":1259,"type":544,"tunes":1261},"537568c224",{"text":1260},"La taille du modèle, les exigences de VRAM, l'ensemble d'outils, le protocole de plug-in et la prise en charge matérielle peuvent tous changer dans les futures versions.",{},{"id":1263,"data":1264,"type":544,"tunes":1266},"fe24516c11",{"text":1265},"Une future version pourrait également déplacer une partie de l'inférence vers un NPU ou introduire une intégration MCP plus large, mais cela ne doit pas être supposé tant que NVIDIA ne le documente pas.",{},{"id":1268,"data":1269,"type":572,"tunes":1271},"0e31e2d54d",{"text":1270,"level":47},"Limites",{},{"id":1273,"data":1274,"type":544,"tunes":1276},"a7881e11e1",{"text":1275},"Cet article décrit la documentation publique du produit G-Assist de NVIDIA et l'architecture publique des plug-ins en date de septembre 2026.",{},{"id":1278,"data":1279,"type":544,"tunes":1281},"71ebc16fda",{"text":1280},"NVIDIA ne documente pas publiquement chaque détail interne de son pipeline de connaissances et de recommandations, donc cet article ne prétend pas que chaque réponse de connaissances utilise RAG ou toute autre implémentation de récupération spécifique.",{},{"id":1283,"data":1284,"type":544,"tunes":1286},"add780d6ba",{"text":1285},"Les plug-ins tiers peuvent avoir un comportement et un accès réseau au-delà des fonctions intégrées de NVIDIA, donc chaque plug-in doit être évalué séparément.",{},{"id":1288,"data":1289,"type":572,"tunes":1291},"f7a38af5be",{"text":1290,"level":47},"Conclusion",{},{"id":1293,"data":1294,"type":544,"tunes":1296},"f1308f3e80",{"text":1295},"La façon la plus simple de comprendre Project G-Assist est d'arrêter de le considérer comme un chatbot.",{},{"id":1298,"data":1299,"type":544,"tunes":1301},"b102a861bb",{"text":1300},"Le SLM local interprète votre demande. Les connaissances l'aident à comprendre le problème. Les informations système en direct lui indiquent ce qui est vrai sur votre PC. Une fonction intégrée ou un plug-in définit ce qu'il est réellement autorisé à faire. L'outil effectue l'action et renvoie le résultat.",{},{"id":1303,"data":1304,"type":544,"tunes":1306},"da805fabf0",{"text":1305},"C'est une architecture d'agent local.",{},{"id":1308,"data":1309,"type":544,"tunes":1311},"675aecee06",{"text":1310},"Son idée la plus forte n'est pas qu'un modèle de 8 milliards de paramètres puisse parler de votre GPU. C'est qu'un modèle local relativement petit peut devenir utile lorsqu'il est connecté à des outils bien définis, à l'état actuel et à une frontière d'action contrôlée.",{},{"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","Non. Son modèle de langage principal s'exécute localement sur le GPU GeForce RTX et peut fonctionner hors ligne pour les fonctions locales prises en charge.","G-Assist est-il un chatbot cloud ?",{"id":1326,"answer":1327,"question":1328},"faq2","NVIDIA le décrit actuellement comme un modèle instruct local basé sur Llama avec 8 milliards de paramètres.","Quel modèle G-Assist utilise-t-il ?",{"id":1330,"answer":1331,"question":1332},"faq3","Non. Le modèle sélectionne une fonction intégrée ou un plug-in pris en charge, et cet outil effectue la modification réelle.","Le modèle d'IA modifie-t-il directement les paramètres de mon GPU ?",{"id":1334,"answer":1335,"question":1336},"faq4","Oui. NVIDIA recommande de la VRAM libre supplémentaire pour l'assistant et avertit que l'inférence peut réduire brièvement les performances de rendu du jeu.","G-Assist utilise-t-il de la VRAM pendant le jeu ?",{"id":1338,"answer":1339,"question":1340},"faq5","Pas directement. Le protocole de plug-in actuel de G-Assist utilise JSON-RPC 2.0, bien qu'un plug-in puisse se connecter à un serveur MCP.","Les plug-ins G-Assist sont-ils des plug-ins MCP ?",{"id":1342,"answer":1343,"question":1344},"faq6","Son assistant local le peut, mais les plug-ins individuels peuvent encore nécessiter un accès Internet s'ils appellent des services en ligne.","G-Assist peut-il fonctionner hors ligne ?",{"id":1346,"answer":1347,"question":1348},"faq7","NVIDIA le décrit comme un assistant spécialisé pour PC et jeux plutôt qu'un modèle conversationnel généraliste polyvalent.","G-Assist est-il un assistant IA généraliste ?","NVIDIA Project G-Assist en clair","faq",{},{"id":1353,"data":1354,"type":572,"tunes":1356},"8733f298cd",{"text":1355,"level":47},"Glossaire",{},{"id":1358,"data":1359,"type":1394,"tunes":1395},"407257a6d1",{"title":1360,"entries":1361},"Termes clés de G-Assist",[1362,1366,1370,1374,1378,1382,1386,1390],{"term":1363,"anchor":1364,"definition":1365},"SLM","slm","Small Language Model, un modèle de langage compact conçu pour s'exécuter localement avec des exigences matérielles inférieures à celles des grands modèles cloud.",{"term":1367,"anchor":1368,"definition":1369},"Appel d'outils","tool-calling","Le processus par lequel un modèle de langage choisit une fonction définie et fournit des arguments structurés afin qu'un autre composant puisse effectuer une action.",{"term":1371,"anchor":1372,"definition":1373},"Plug-in","plugin","Une extension qui expose des fonctions ou des intégrations supplémentaires à G-Assist.",{"term":1375,"anchor":1376,"definition":1377},"JSON-RPC 2.0","json-rpc","Le protocole de messages structurés utilisé par le système de plug-ins actuel G-Assist Protocol V2.",{"term":1379,"anchor":1380,"definition":1381},"MCP","mcp","Model Context Protocol, un protocole distinct d'interopérabilité d'outils et de contexte que certaines intégrations externes peuvent exposer.",{"term":1383,"anchor":1384,"definition":1385},"Frontière outil-autorité","tool-authority-boundary","Un modèle Figure Rocks séparant ce qu'un modèle d'IA peut comprendre de ce que ses outils connectés lui permettent réellement de faire.",{"term":1387,"anchor":1388,"definition":1389},"Pile d'agents locaux","local-agent-stack","Un modèle Figure Rocks combinant l'intention de l'utilisateur, le SLM local, les connaissances, l'état en direct, la sélection d'outils, l'exécution et la vérification des résultats.",{"term":1391,"anchor":1392,"definition":1393},"Test de ressources de l'assistant local","local-assistant-resource-test","Un flux de travail Figure Rocks pour évaluer la VRAM, le coût d'inférence, les autorisations d'outils et le risque des plug-ins avant d'utiliser un assistant de jeu local.","glossary",{},{"id":1397,"data":1398,"type":572,"tunes":1400},"3ab856f2b4",{"text":1399,"level":47},"Sources principales",{},{"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","Page produit officielle actuelle couvrant le modèle local, les fonctions prises en charge, les modes Reasoning et Flash, les exigences de VRAM, les contrôles RTX, les plug-ins et l'intégration Elgato basée sur MCP version 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","Dépôt public officiel de plug-ins documentant l'architecture des modules de G-Assist, la découverte des plug-ins et le 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 — Guide de migration vers G-Assist Protocol V2","Documentation officielle du protocole couvrant JSON-RPC 2.0, l'initialisation, les contrôles de santé, l'exécution, le streaming, l'achèvement et le comportement du SDK de 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},"Blog NVIDIA — Modèle G-Assist léger","Contexte officiel sur le modèle G-Assist à mémoire réduite, la prise en charge des GPU RTX de 6 Go et le hub de plug-ins communautaire.",{},"2.31","NVIDIA Project G-Assist ressemble à un chatbot, mais son architecture réelle est plus proche d'un agent IA local. Un petit modèle de langage interprète votre demande, l'état du système fournit les informations actuelles du PC, les outils effectuent de véritables actions, et les plug-ins étendent ce que l'assistant est autorisé à contrôler.","\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",[1456,1460,1464,1468,1472],{"id":1457,"name":1458,"slug":1459},171,"GPU et pilotes","gpus-and-drivers",{"id":1461,"name":1462,"slug":1463},67,"Windows et pilotes","windows-and-drivers",{"id":1465,"name":1466,"slug":1467},68,"Paramètres en jeu","in-game-settings",{"id":1469,"name":1470,"slug":1471},69,"Paramètres d'affichage","display-settings",{"id":1473,"name":1474,"slug":1475},197,"Meilleurs réglages en priorité","best-settings-first",{"id":283,"login":1477,"email":1478,"displayName":1479},"aleksandar","aleksandar@stajic.de","Aleksandar Stajic",[1481,2187],{"lang":8,"title":1482,"content":1483,"contentJson":1484,"excerpt":2186},"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":1485,"blocks":1486,"version":2185},1790407740910,[1487,1491,1496,1501,1505,1509,1513,1517,1521,1526,1530,1553,1557,1561,1565,1569,1591,1595,1599,1603,1607,1624,1629,1635,1639,1643,1647,1651,1655,1659,1663,1667,1671,1675,1679,1683,1687,1691,1696,1703,1707,1711,1715,1733,1737,1741,1745,1749,1769,1773,1777,1781,1785,1804,1808,1812,1816,1820,1825,1829,1833,1837,1841,1845,1871,1875,1879,1883,1887,1891,1895,1916,1920,1924,1928,1932,1936,1940,1963,1967,1971,1975,1979,1983,1987,1991,1995,1999,2006,2010,2014,2018,2022,2026,2030,2046,2050,2054,2058,2062,2066,2070,2074,2078,2081,2085,2089,2093,2097,2100,2126,2130,2155,2159,2165,2171,2178],{"id":541,"data":1488,"type":544,"tunes":1490},{"text":1489},"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":1492,"type":552,"tunes":1495},{"body":1493,"title":1494,"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":1497,"type":552,"tunes":1500},{"body":1498,"title":1499,"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":1502,"type":566,"tunes":1504},{"title":1503,"maxLevel":565,"minLevel":47},"Contents",{},{"id":569,"data":1506,"type":572,"tunes":1508},{"text":1507,"level":47},"First: what is the AI model actually doing?",{},{"id":575,"data":1510,"type":544,"tunes":1512},{"text":1511},"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":1514,"type":544,"tunes":1516},{"text":1515},"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":1518,"type":544,"tunes":1520},{"text":1519},"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":1522,"type":552,"tunes":1525},{"body":1523,"title":1524,"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":1527,"type":572,"tunes":1529},{"text":1528,"level":47},"The G-Assist action pipeline",{},{"id":602,"data":1531,"type":625,"tunes":1552},{"steps":1532,"title":1551,"orientation":624},[1533,1536,1539,1542,1545,1548],{"label":1534,"description":1535},"1. You give a natural-language request","For example: “Optimize this game for performance.”",{"label":1537,"description":1538},"2. The local SLM interprets the request","It determines the user's intent and identifies which supported function or plug-in is relevant.",{"label":1540,"description":1541},"3. The system chooses a tool","That could be a built-in graphics-setting function, driver check, monitoring function or community plug-in.",{"label":1543,"description":1544},"4. Arguments are extracted","The model converts the request into structured values such as game name, mode, fan profile or DLSS setting.",{"label":1546,"description":1547},"5. The tool executes","The tool talks to the NVIDIA App, operating system, peripheral software or another service.",{"label":1549,"description":1550},"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":1554,"type":572,"tunes":1556},{"text":1555,"level":47},"This is tool calling, not magic PC control",{},{"id":633,"data":1558,"type":544,"tunes":1560},{"text":1559},"A language model cannot safely control an arbitrary computer simply because it understands English.",{},{"id":638,"data":1562,"type":544,"tunes":1564},{"text":1563},"It needs a defined interface that says which actions exist, which arguments they accept and what the tool returns.",{},{"id":643,"data":1566,"type":544,"tunes":1568},{"text":1567},"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":1570,"type":676,"tunes":1590},{"rows":1571,"title":1584,"layout":668,"columns":1585},[1572,1575,1578,1581],{"id":652,"label":1573,"values":1574},"Understand “turn on DLSS”",[13,13],{"id":656,"label":1576,"values":1577},"Choose the correct function",[13,13],{"id":660,"label":1579,"values":1580},"Actually change the setting",[13,13],{"id":664,"label":1582,"values":1583},"Explain the result",[13,13],"Language model vs tool",[1586,1588],{"id":671,"label":1587},"Language model",{"id":674,"label":1589},"Tool \u002F plug-in",{},{"id":679,"data":1592,"type":572,"tunes":1594},{"text":1593,"level":47},"What is the knowledge layer?",{},{"id":684,"data":1596,"type":544,"tunes":1598},{"text":1597},"G-Assist also has a knowledge layer for answering questions and making recommendations.",{},{"id":689,"data":1600,"type":544,"tunes":1602},{"text":1601},"NVIDIA says version 0.2.1 introduced an improved knowledge system that helps G-Assist make more accurate settings recommendations.",{},{"id":694,"data":1604,"type":544,"tunes":1606},{"text":1605},"That knowledge layer is different from the live state of your PC.",{},{"id":699,"data":1608,"type":676,"tunes":1623},{"rows":1609,"title":1617,"layout":668,"columns":1618},[1610,1612,1615],{"id":703,"label":704,"values":1611},[13,13],{"id":707,"label":1613,"values":1614},"Game settings",[13,13],{"id":711,"label":712,"values":1616},[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":1803},{"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",[1800,1801],{"id":945,"label":946},{"id":948,"label":1802},"Purpose",{},{"id":952,"data":1805,"type":572,"tunes":1807},{"text":1806,"level":47},"Where MCP enters the picture",{},{"id":957,"data":1809,"type":544,"tunes":1811},{"text":1810},"G-Assist's own plug-in protocol is not MCP. Its current public plug-in system uses JSON-RPC 2.0.",{},{"id":962,"data":1813,"type":544,"tunes":1815},{"text":1814},"However, a G-Assist plug-in can connect to an MCP server.",{},{"id":967,"data":1817,"type":544,"tunes":1819},{"text":1818},"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":1821,"type":552,"tunes":1824},{"body":1822,"title":1823,"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":1826,"type":572,"tunes":1828},{"text":1827,"level":47},"Why this matters beyond RGB lights",{},{"id":983,"data":1830,"type":544,"tunes":1832},{"text":1831},"The plug-in architecture turns G-Assist from a fixed assistant into a local tool router.",{},{"id":988,"data":1834,"type":544,"tunes":1836},{"text":1835},"The same pattern can connect an SLM to monitoring tools, peripherals, APIs, automation systems, local applications or external services.",{},{"id":993,"data":1838,"type":544,"tunes":1840},{"text":1839},"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":1842,"type":572,"tunes":1844},{"text":1843,"level":47},"The Local Agent Stack",{},{"id":1003,"data":1846,"type":625,"tunes":1870},{"steps":1847,"title":1869,"orientation":624},[1848,1851,1854,1857,1860,1863,1866],{"label":1849,"description":1850},"1. User intent","Natural language or voice command.",{"label":1852,"description":1853},"2. Local SLM","Understands the request and chooses a capability.",{"label":1855,"description":1856},"3. Knowledge \u002F context","Provides product knowledge, recommendations or information needed for the decision.",{"label":1858,"description":1859},"4. Live system state","Provides current hardware, driver, performance or configuration information when supported.",{"label":1861,"description":1862},"5. Tool selection","Built-in function or plug-in is chosen.",{"label":1864,"description":1865},"6. Structured execution","The function receives arguments and performs the real action.",{"label":1867,"description":1868},"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":1872,"type":572,"tunes":1874},{"text":1873,"level":47},"Why tool boundaries are a safety feature",{},{"id":1035,"data":1876,"type":544,"tunes":1878},{"text":1877},"An AI assistant that could execute arbitrary operating-system commands would be far more powerful, but also much harder to constrain.",{},{"id":1040,"data":1880,"type":544,"tunes":1882},{"text":1881},"G-Assist instead exposes defined functions with known parameters.",{},{"id":1045,"data":1884,"type":544,"tunes":1886},{"text":1885},"That means the model can only perform actions that the built-in function set or installed plug-ins make available.",{},{"id":1050,"data":1888,"type":544,"tunes":1890},{"text":1889},"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":1892,"type":572,"tunes":1894},{"text":1893,"level":47},"The Tool-Authority Boundary",{},{"id":1060,"data":1896,"type":676,"tunes":1915},{"rows":1897,"title":1909,"layout":668,"columns":1910},[1898,1901,1904,1906],{"id":703,"label":1899,"values":1900},"GPU tuning",[13,13],{"id":1067,"label":1902,"values":1903},"Files",[13,13],{"id":1071,"label":1072,"values":1905},[13,13],{"id":1075,"label":1907,"values":1908},"Peripheral control",[13,13],"What the assistant can understand vs what it is allowed to do",[1911,1913],{"id":652,"label":1912},"Model may understand",{"id":1083,"label":1914},"Tool authority",{},{"id":1087,"data":1917,"type":572,"tunes":1919},{"text":1918,"level":47},"Why G-Assist can temporarily reduce game performance",{},{"id":1092,"data":1921,"type":544,"tunes":1923},{"text":1922},"The local-model architecture has a straightforward consequence: the AI and the game can compete for the same GPU.",{},{"id":1097,"data":1925,"type":544,"tunes":1927},{"text":1926},"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":1929,"type":544,"tunes":1931},{"text":1930},"Once inference finishes, those GPU resources return to the game.",{},{"id":1107,"data":1933,"type":544,"tunes":1935},{"text":1934},"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":1937,"type":572,"tunes":1939},{"text":1938,"level":47},"The Local Assistant Resource Test",{},{"id":1117,"data":1941,"type":625,"tunes":1962},{"steps":1942,"title":1961,"orientation":624},[1943,1946,1949,1952,1955,1958],{"label":1944,"description":1945},"1. Check installed VRAM","The current G-Assist baseline is an RTX GPU with at least 6 GB VRAM.",{"label":1947,"description":1948},"2. Check free VRAM during the actual game","Installed capacity is not the same as free capacity.",{"label":1950,"description":1951},"3. Choose Reasoning or Flash Mode appropriately","Use the lighter mode when resource pressure matters more than deep reasoning.",{"label":1953,"description":1954},"4. Measure inference-time frame-rate dips","Watch the game while asking G-Assist to perform tasks.",{"label":1956,"description":1957},"5. Inspect tool authority","Know exactly which built-in functions and plug-ins can change your system.",{"label":1959,"description":1960},"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":1964,"type":572,"tunes":1966},{"text":1965,"level":47},"Why plug-ins deserve the same scrutiny as any other software",{},{"id":1146,"data":1968,"type":544,"tunes":1970},{"text":1969},"A plug-in can connect the assistant to APIs, peripheral applications and online services.",{},{"id":1151,"data":1972,"type":544,"tunes":1974},{"text":1973},"That means a plug-in may handle configuration values, credentials or external requests depending on what it was built to do.",{},{"id":1156,"data":1976,"type":544,"tunes":1978},{"text":1977},"NVIDIA's repository explicitly provides a config.json location for plug-in settings and warns developers not to commit credentials.",{},{"id":1161,"data":1980,"type":544,"tunes":1982},{"text":1981},"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":1984,"type":572,"tunes":1986},{"text":1985,"level":47},"G-Assist is closer to an agent than a chatbot",{},{"id":1171,"data":1988,"type":544,"tunes":1990},{"text":1989},"A chatbot mainly produces language.",{},{"id":1176,"data":1992,"type":544,"tunes":1994},{"text":1993},"An agent interprets a goal, observes relevant information, chooses an action, calls a tool and evaluates the result.",{},{"id":1181,"data":1996,"type":544,"tunes":1998},{"text":1997},"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":2000,"type":737,"tunes":2005},{"url":2001,"title":2002,"excerpt":2003,"ctaLabel":2004},"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":2007,"type":572,"tunes":2009},{"text":2008,"level":47},"What G-Assist still is not",{},{"id":1199,"data":2011,"type":544,"tunes":2013},{"text":2012},"NVIDIA explicitly describes G-Assist as a specialized local assistant, not a general-purpose conversational AI.",{},{"id":1204,"data":2015,"type":544,"tunes":2017},{"text":2016},"Its value comes from understanding a focused set of PC and gaming tasks and having tools connected to those tasks.",{},{"id":1209,"data":2019,"type":544,"tunes":2021},{"text":2020},"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":2023,"type":572,"tunes":2025},{"text":2024,"level":47},"What changed in the current versions?",{},{"id":1219,"data":2027,"type":544,"tunes":2029},{"text":2028},"The current public release history shows G-Assist moving steadily toward a more capable local agent.",{},{"id":1224,"data":2031,"type":668,"tunes":2045},{"content":2032,"stretched":1245,"withHeadings":15},[2033,2035,2037,2039,2041,2043],[1228,2034],"Important change",[1231,2036],"Lighter model, all RTX GPUs with 6 GB+ VRAM, community plug-ins",[1234,2038],"Laptop optimization, BatteryBoost and WhisperMode controls",[1237,2040],"Reasoning Mode, Flash Mode, multi-action prompts, new device controls",[1240,2042],"Improved knowledge system, better recommendations, RTX feature controls",[1243,2044],"Elgato Stream Deck integration through an MCP server",{},{"id":1248,"data":2047,"type":572,"tunes":2049},{"text":2048,"level":47},"What would change this answer?",{},{"id":1253,"data":2051,"type":544,"tunes":2053},{"text":2052},"G-Assist is still experimental and its architecture is evolving.",{},{"id":1258,"data":2055,"type":544,"tunes":2057},{"text":2056},"The model size, VRAM requirements, tool set, plug-in protocol and hardware support can all change in future releases.",{},{"id":1263,"data":2059,"type":544,"tunes":2061},{"text":2060},"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":2063,"type":572,"tunes":2065},{"text":2064,"level":47},"Limitations",{},{"id":1273,"data":2067,"type":544,"tunes":2069},{"text":2068},"This article describes NVIDIA's public G-Assist product documentation and public plug-in architecture as of September 2026.",{},{"id":1278,"data":2071,"type":544,"tunes":2073},{"text":2072},"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":2075,"type":544,"tunes":2077},{"text":2076},"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":2079,"type":572,"tunes":2080},{"text":1290,"level":47},{},{"id":1293,"data":2082,"type":544,"tunes":2084},{"text":2083},"The easiest way to understand Project G-Assist is to stop thinking of it as a chatbot.",{},{"id":1298,"data":2086,"type":544,"tunes":2088},{"text":2087},"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":2090,"type":544,"tunes":2092},{"text":2091},"That is a local agent architecture.",{},{"id":1308,"data":2094,"type":544,"tunes":2096},{"text":2095},"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":2098,"type":572,"tunes":2099},{"text":1315,"level":47},{},{"id":1318,"data":2101,"type":1350,"tunes":2125},{"items":2102,"title":2124},[2103,2106,2109,2112,2115,2118,2121],{"id":1322,"answer":2104,"question":2105},"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":2107,"question":2108},"NVIDIA currently describes it as a local Llama-based instruct model with 8 billion parameters.","What model does G-Assist use?",{"id":1330,"answer":2110,"question":2111},"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":2113,"question":2114},"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":2116,"question":2117},"Not directly. 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Utilisez cette checklist pour routeur pour stabiliser la latence sous charge avant d'acheter du nouveau matériel.","2026-02-20T16:00:00.000Z",{"id":2693,"slug":2694,"title":2695,"excerpt":2696,"featuredImage":14,"publishedAt":2697},"142","display-cable-and-port-basics-fixing-120hz-vrr-and-hdr-handshake-issues","Bases des câbles et ports d'affichage : résoudre les problèmes de handshake 120Hz, VRR et HDR","De nombreux ‘problèmes de fonctionnalités’ sont des problèmes de handshake : mauvais port, mauvais câble, mauvais mode d'entrée. Utilisez cette base pour rétablir le 120Hz, le VRR et l'HDR.","2026-02-20T11:30:00.000Z",{"id":2699,"slug":2700,"title":2701,"excerpt":2702,"featuredImage":14,"publishedAt":2703},"172","display-modes-glossary-game-mode-pc-mode-filmmaker-mode-what-they-really-change","Glossaire des modes d'affichage : Mode Jeu, Mode PC, Mode Filmmaker (ce qu'ils changent vraiment)","Les modes d'affichage ne sont pas cosmétiques. Ils modifient le traitement, la gestion du chroma et la latence. Utilisez ce glossaire pour choisir le bon mode pour la clarté et le ressenti de jeu.","2026-02-20T14:00:00.000Z",{"id":2705,"slug":2706,"title":2707,"excerpt":2708,"featuredImage":14,"publishedAt":2709},"209","windows-audio-mixer-traps-why-pc-audio-feels-inconsistent-in-games","Pièges du mixeur audio Windows : pourquoi l'audio du PC semble incohérent dans les jeux","L'audio du PC semble aléatoire lorsque le routage change silencieusement. Découvrez les pièges du mélangeur (changement de périphérique par défaut, améliorations, routage des applications) et comment verrouiller un chemin stable.","2026-02-20T23:40:00.000Z",{"id":2711,"slug":2712,"title":2713,"excerpt":2714,"featuredImage":14,"publishedAt":2715},"207","120hz-feels-worse-the-diagnosis-checklist-wrong-mode-vrr-range-caps","120Hz semble moins fluide ? Liste de diagnostic (Mauvais mode, plage VRR, limitations)","Un taux de rafraîchissement plus élevé peut révéler une instabilité. Utilisez cette liste de contrôle pour diagnostiquer pourquoi le 120 Hz semble moins fluide : mauvais mode, mauvais chemin de rafraîchissement, problèmes de plage VRR ou limites manquantes.","2026-02-20T20:30:00.000Z",{"id":2717,"slug":2718,"title":2719,"excerpt":2720,"featuredImage":14,"publishedAt":2721},"159","ethernet-vs-wi-fi-for-gaming-the-real-reasons-ethernet-wins","Ethernet vs Wi-Fi pour le gaming : les vraies raisons pour lesquelles l'Ethernet l'emporte","L'Ethernet n'est pas une question de vitesse. C'est une question de régularité : moins de pics, moins d'interférences et une latence prévisible. Utilisez ceci pour décider quand le Wi-Fi est ‘assez bon’.","2026-02-20T13:00:00.000Z",{"id":2723,"slug":2724,"title":2725,"excerpt":2726,"featuredImage":14,"publishedAt":2727},"199","wi-fi-bands-decision-2-4-vs-5-vs-6e-gaming-stability-first","Choix des bandes Wi-Fi : 2,4 vs 5 vs 6E (Priorité à la stabilité en jeu)","Choisissez vos bandes Wi-Fi selon la stabilité, pas le battage médiatique. Utilisez ce guide de décision pour choisir entre le 2,4, le 5 ou le 6E en fonction de la distance, de l'encombrement et du comportement réel de la gigue.","2026-02-20T18:00:00.000Z",{"id":2729,"slug":2730,"title":2731,"excerpt":2732,"featuredImage":14,"publishedAt":2733},"246","router-checklist-for-gaming-the-settings-that-actually-matter","Checklist routeur pour le gaming : les paramètres qui comptent vraiment","La plupart des optimisations de routeur n'aident pas. Ces paramètres, oui : gestion des files d'attente sous charge, comportement Wi-Fi stable et éviter les fonctionnalités qui ajoutent de la latence ou de l'instabilité.","2026-02-21T01:30:00.000Z","fallback",[],[]]