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To je lokalni AI sistem koji može da razume zahtev, pregleda podržano stanje računara, izabere alat ili dodatak i zatim izvrši stvarnu radnju kao što je promena DLSS podešavanja, provera drajvera, podešavanje profila ventilatora ili upravljanje perifernim uređajem.\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\">Direktan odgovor\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">\u003Cstrong>G-Assist nije samo chatbot za vašu grafičku karticu.\u003C\u002Fstrong> To je lokalni mali jezički model povezan sa skupom dozvoljenih alata. Model tumači šta želite, bira podržanu funkciju, prosleđuje argumente toj funkciji, a alat na strani računara izvršava radnju.\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\">Najlakši mentalni model\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">\u003Cstrong>SLM = razume zahtev.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Znanje = objašnjava podržane NVIDIA\u002FPC koncepte.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Alati = izvršavaju radnje.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Dodaci = dodaju nove alate.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Vaš računar = okruženje koje se pregleda ili menja.\u003C\u002Fstrong>\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Cnav class=\"editorjs-toc\" data-editorjs-toc=\"true\" aria-label=\"Sadržaj\">\u003Cstrong class=\"editorjs-toc__title\">Sadržaj\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\">Prvo: šta AI model zapravo radi?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-10\" class=\"editorjs-toc__link\">G-Assist tok izvršavanja radnji\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-12\" class=\"editorjs-toc__link\">Ovo je pozivanje alata, a ne magična kontrola računara\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-17\" class=\"editorjs-toc__link\">Šta je sloj znanja?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-24\" class=\"editorjs-toc__link\">Da li G-Assist koristi RAG?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-28\" class=\"editorjs-toc__link\">Zašto G-Assist može da radi van mreže\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-33\" class=\"editorjs-toc__link\">Cena lokalne AI: G-Assist koristi vaš GPU i VRAM\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-40\" class=\"editorjs-toc__link\">Reasoning Mode naspram Flash Mode\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-44\" class=\"editorjs-toc__link\">Šta plug-inovi zapravo dodaju\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-49\" class=\"editorjs-toc__link\">G-Assist Protocol V2 je JSON-RPC 2.0\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-54\" class=\"editorjs-toc__link\">Gde MCP ulazi u sliku\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-59\" class=\"editorjs-toc__link\">Zašto je ovo važno van RGB svetala\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-63\" class=\"editorjs-toc__link\">Lokalni agentski stek\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-65\" class=\"editorjs-toc__link\">Zašto su granice alata bezbednosna karakteristika\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-70\" class=\"editorjs-toc__link\">Granica ovlašćenja alata\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-72\" class=\"editorjs-toc__link\">Zašto G-Assist može privremeno da smanji performanse igre\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-77\" class=\"editorjs-toc__link\">Test resursa lokalnog asistenta\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-79\" class=\"editorjs-toc__link\">Zašto plug-inovi zaslužuju isto ispitivanje kao i svaki drugi softver\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-84\" class=\"editorjs-toc__link\">G-Assist je bliži agentu nego chatbot-u\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-89\" class=\"editorjs-toc__link\">Šta G-Assist još uvek nije\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-93\" class=\"editorjs-toc__link\">Šta se promenilo u trenutnim verzijama?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-96\" class=\"editorjs-toc__link\">Šta bi promenilo ovaj odgovor?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-100\" class=\"editorjs-toc__link\">Ograničenja\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-104\" class=\"editorjs-toc__link\">Zaključak\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-109\" class=\"editorjs-toc__link\">Često postavljana pitanja\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-111\" class=\"editorjs-toc__link\">Pojmovnik\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-113\" class=\"editorjs-toc__link\">Primarni izvori\u003C\u002Fa>\u003C\u002Fli>\u003C\u002Fol>\u003C\u002Fnav>\n\u003Ch2 id=\"section-5\">Prvo: šta AI model zapravo radi?\u003C\u002Fh2>\n\u003Cp>G-Assist koristi lokalni mali jezički model, ili SLM. NVIDIA trenutno opisuje sistem kao korišćenje Llama-baziranog instrukcionog modela sa 8 milijardi parametara.\u003C\u002Fp>\n\u003Cp>Glavni zadatak modela nije da renderuje grafiku ili direktno menja hardverske registre. Njegov zadatak je da razume jezik korisnika, odluči koja podržana mogućnost odgovara zahtevu i pripremi poziv toj mogućnosti.\u003C\u002Fp>\n\u003Cp>Na primer, ako kažete „postavi DLSS Super Resolution na režim performansi“, jezički model sam ne menja DLSS. On tumači komandu i usmerava je ka podržanoj funkciji koja može da promeni podešavanje.\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\">Važna razlika\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">AI model \u003Cstrong>odlučuje koji alat pozvati\u003C\u002Fstrong>. Alat \u003Cstrong>obavlja pravi posao\u003C\u002Fstrong>.\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Ch2 id=\"section-10\">G-Assist tok izvršavanja radnji\u003C\u002Fh2>\n\u003Csection class=\"editorjs-process my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Šta se dešava nakon što date G-Assist-u komandu\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. Dajete zahtev prirodnim jezikom\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Na primer: „Optimizuj ovu igru za performanse.“\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. Lokalni SLM tumači zahtev\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Određuje nameru korisnika i identifikuje koja je podržana funkcija ili dodatak relevantan.\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. Sistem bira alat\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">To može biti ugrađena funkcija za grafička podešavanja, provera drajvera, funkcija nadzora ili dodatak zajednice.\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. Argumenti se izvlače\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Model pretvara zahtev u strukturisane vrednosti kao što su naziv igre, režim, profil ventilatora ili DLSS podešavanje.\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. Alat se izvršava\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Alat komunicira sa NVIDIA aplikacijom, operativnim sistemom, softverom perifernog uređaja ili drugim servisom.\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. Rezultat se vraća\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">G-Assist prijavljuje šta se dogodilo ili vraća podatke koje model može da objasni.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-12\">Ovo je pozivanje alata, a ne magična kontrola računara\u003C\u002Fh2>\n\u003Cp>Jezički model ne može bezbedno da kontroliše proizvoljan računar samo zato što razume engleski.\u003C\u002Fp>\n\u003Cp>Potreban mu je definisan interfejs koji kaže koje radnje postoje, koje argumente prihvataju i šta alat vraća.\u003C\u002Fp>\n\u003Cp>Trenutne ugrađene mogućnosti G-Assist-a uključuju funkcije kao što su optimizacija grafičkih podešavanja, promena podržanih RTX opcija, provera ili preuzimanje drajvera, prikaz informacija o performansama, promena nekih funkcija napajanja na laptopu, upravljanje podržanim funkcijama monitora i korišćenje podržanih dodataka za periferne uređaje.\u003C\u002Fp>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Jezički model naspram alata\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\">Jezički model\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\">Alat \u002F dodatak\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\">Razume „uključi 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\">Bira ispravnu funkciju\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\">Zaista menja podešavanje\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\">Objašnjava rezultat\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\">Šta je sloj znanja?\u003C\u002Fh2>\n\u003Cp>G-Assist takođe ima sloj znanja za odgovaranje na pitanja i davanje preporuka.\u003C\u002Fp>\n\u003Cp>NVIDIA kaže da je verzija 0.2.1 uvela poboljšani sistem znanja koji pomaže G-Assist-u da daje tačnije preporuke za podešavanja.\u003C\u002Fp>\n\u003Cp>Taj sloj znanja se razlikuje od trenutnog stanja vašeg računara.\u003C\u002Fp>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Znanje naspram trenutnog stanja računara\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\">Znanje\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\">Trenutno stanje\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\">Podešavanja igre\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\">Performanse\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 mešajte znanje sa stanjem\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">\u003Cstrong>Znanje\u003C\u002Fstrong> govori asistentu šta neka funkcija znači ili šta je obično važno.\u003Cbr>\u003Cstrong>Stanje\u003C\u002Fstrong> mu govori šta je trenutno tačno na vašoj mašini.\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\">Šta je RAG? Najjednostavnije objašnjenje kako funkcioniše\u003C\u002Fstrong>\u003Cp class=\"mt-2 text-sm text-gray-600 dark:text-gray-300\">Jednostavno objašnjenje na engleskom o pronalaženju znanja, stanju, memoriji, kontekstu i jezičkom modelu.\u003C\u002Fp>\u003Cspan class=\"mt-3 inline-flex text-sm font-medium text-primary-600 dark:text-primary-400\">Pročitajte jednostavan vodič o RAG-u →\u003C\u002Fspan>\u003C\u002Fdiv>\u003C\u002Fa>\u003C\u002Faside>\n\u003Ch2 id=\"section-24\">Da li G-Assist koristi RAG?\u003C\u002Fh2>\n\u003Cp>Najsigurniji odgovor je: G-Assist očigledno ima sistem znanja, ali NVIDIA-ina javna stranica proizvoda ne dokumentuje svaki interni mehanizam pronalaženja dovoljno detaljno da bi se moglo reći da svaki odgovor zasnovan na znanju specifično proizvodi RAG.\u003C\u002Fp>\n\u003Cp>Arhitektonska razlika je i dalje važna. Sloj za pronalaženje može da pruži relevantno znanje, dok sistemski alati pružaju trenutno stanje računara i izvršavaju radnje.\u003C\u002Fp>\n\u003Cp>To je isto razdvajanje koje se koristi u mnogim modernim agentima: znanje je jedan izvor konteksta, trenutna zapažanja su drugi, a izvršavanje alata je treći.\u003C\u002Fp>\n\u003Ch2 id=\"section-28\">Zašto G-Assist može da radi van mreže\u003C\u002Fh2>\n\u003Cp>NVIDIA pokreće jezički model lokalno na GeForce RTX GPU.\u003C\u002Fp>\n\u003Cp>To znači da osnovni asistent ne zahteva jezički model hostovan u oblaku za svaki upit.\u003C\u002Fp>\n\u003Cp>NVIDIA eksplicitno navodi da G-Assist može da radi van mreže za svoje lokalne mogućnosti.\u003C\u002Fp>\n\u003Cp>Dodatak i dalje može da koristi internet ako taj dodatak poziva onlajn servis. Lokalno izvršavanje modela i onlajn pristup dodataka su odvojena pitanja.\u003C\u002Fp>\n\u003Ch2 id=\"section-33\">Cena lokalne AI: G-Assist koristi vaš GPU i VRAM\u003C\u002Fh2>\n\u003Cp>Lokalno pokretanje pruža privatnost i nezavisnost od modela u oblaku, ali rad mora negde da se izvrši.\u003C\u002Fp>\n\u003Cp>Za G-Assist, to negde je isti GeForce RTX GPU koji možda već renderuje vašu igru.\u003C\u002Fp>\n\u003Cp>NVIDIA upozorava da GPU nakratko dodeljuje računarske resurse za AI inferenciju kada G-Assist odgovara. Ako se istovremeno pokreće zahtevna igra, igra može privremeno da izgubi deo performansi renderovanja dok je model aktivan.\u003C\u002Fp>\n\u003Cp>Trenutni zahtevi takođe navode ciljne vrednosti slobodne VRAM memorije koja prevazilazi memoriju koju igra već koristi: približno 6 GB slobodne VRAM memorije za Reasoning Mode i 4,5 GB za Flash Mode.\u003C\u002Fp>\n\u003Caside class=\"editorjs-callout editorjs-callout--warning my-6 rounded-xl border p-5 border-amber-300 bg-amber-50 dark:border-amber-900 dark:bg-amber-950\u002F20\" role=\"note\">\u003Cstrong class=\"block mb-2 text-gray-900 dark:text-gray-100\">8 GB VRAM ne znači da je 8 GB dostupno za G-Assist\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">Igra, Windows, drajver i druge aplikacije već troše VRAM. G-Assist sopstveni zahtev odnosi se na \u003Cstrong>slobodnu VRAM memoriju pored one koju pokrenuti radni zadatak već koristi\u003C\u002Fstrong>.\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Caside class=\"editorjs-referral my-6\">\u003Ca href=\"https:\u002F\u002Ffigure.rocks\u002Fsr\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\">Korišćenje VRAM nije isto što i zahtev za VRAM: Zašto pun memorni merač ne govori celu priču\u003C\u002Fstrong>\u003Cp class=\"mt-2 text-sm text-gray-600 dark:text-gray-300\">Zašto su instalirana VRAM, trenutno korišćenje, budžeti za rezidentnost i stvarni memorni pritisak različite stvari.\u003C\u002Fp>\u003Cspan class=\"mt-3 inline-flex text-sm font-medium text-primary-600 dark:text-primary-400\">Pročitajte vodič za VRAM →\u003C\u002Fspan>\u003C\u002Fdiv>\u003C\u002Fa>\u003C\u002Faside>\n\u003Ch2 id=\"section-40\">Reasoning Mode naspram Flash Mode\u003C\u002Fh2>\n\u003Cp>Trenutne verzije G-Assist razdvajaju sposobniji Reasoning Mode od bržeg Flash Mode.\u003C\u002Fp>\n\u003Cp>Reasoning Mode je dizajniran za odluke višeg kvaliteta i može da koordinira više radnji iz jednog upita. Flash Mode je optimizovan za brže odgovore i manju potrošnju resursa.\u003C\u002Fp>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Reasoning Mode naspram Flash Mode\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\">Reasoning Mode\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\">Flash Mode\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\">Primarni cilj\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\">Preporučena slobodna VRAM\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\">Najbolje odgovara\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\">Šta plug-inovi zapravo dodaju\u003C\u002Fh2>\n\u003Cp>Plug-in ne zamenjuje jezički model. On daje modelu novu radnju koju sme da pozove.\u003C\u002Fp>\n\u003Cp>Plug-in definiše funkcije, opise i parametre. G-Assist čita te opise, uparuje korisnički zahtev sa odgovarajućom funkcijom i šalje joj strukturisane argumente.\u003C\u002Fp>\n\u003Cp>To omogućava asistentu da raste izvan NVIDIA ugrađenih funkcija.\u003C\u002Fp>\n\u003Csection class=\"editorjs-process my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Kako funkcioniše G-Assist plug-in\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. Plug-in deklariše funkciju\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Na primer: 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. Manifest opisuje funkciju\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Manifest govori G-Assist-u šta funkcija radi i koje parametre zahteva.\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. Korisnik pita prirodno\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Na primer: „Napravi moju tastaturu zelenom.“\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. SLM bira funkciju\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Model mapira zahtev na funkciju plug-ina i izvlači zeleno kao parametar.\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. Plug-in izvršava\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Plug-in komunicira sa softverom perifernog uređaja ili eksternim servisom.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-49\">G-Assist Protocol V2 je JSON-RPC 2.0\u003C\u002Fh2>\n\u003Cp>NVIDIA trenutni javni repozitorijum plug-inova koristi Protocol V2.\u003C\u002Fp>\n\u003Cp>Protocol V2 koristi JSON-RPC 2.0 sa porukama prefiksiranim dužinom između G-Assist engine-a i plug-inova.\u003C\u002Fp>\n\u003Cp>Engine može da inicijalizuje plug-in, proveri njegovo zdravlje, izvrši funkciju, pošalje korisnički unos i isključi ga. Plug-inovi mogu da vrate rezultate, strimuju napredak ili prijave greške.\u003C\u002Fp>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Važne Protocol V2 poruke\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\">Smer\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\">Svrha\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\">Gde MCP ulazi u sliku\u003C\u002Fh2>\n\u003Cp>G-Assist sopstveni protokol za dodatke nije MCP. Njegov trenutni javni sistem dodataka koristi JSON-RPC 2.0.\u003C\u002Fp>\n\u003Cp>Međutim, G-Assist dodatak može da se poveže sa MCP serverom.\u003C\u002Fp>\n\u003Cp>NVIDIA trenutna verzija 0.2.2 uključuje Elgato integraciju koja može da pozove radnje izložene putem Elgato Stream Deck MCP servera.\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\">Važna razlika u protokolu\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">\u003Cstrong>G-Assist ↔ njegov dodatak:\u003C\u002Fstrong> NVIDIA Protocol V2 \u002F JSON-RPC 2.0.\u003Cbr>\u003Cstrong>Dodatak ↔ drugi ekosistem alata:\u003C\u002Fstrong> može da koristi MCP kada ta integracija to podržava.\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Ch2 id=\"section-59\">Zašto je ovo važno van RGB svetala\u003C\u002Fh2>\n\u003Cp>Arhitektura dodataka pretvara G-Assist iz fiksnog asistenta u lokalni usmerivač alata.\u003C\u002Fp>\n\u003Cp>Isti obrazac može da poveže SLM sa alatima za nadzor, perifernim uređajima, API-jevima, automatizovanim sistemima, lokalnim aplikacijama ili eksternim servisima.\u003C\u002Fp>\n\u003Cp>Važna arhitektonska jedinica stoga nije prozor za ćaskanje. To je granica između namere na prirodnom jeziku i strukturisanog izvršavanja alata.\u003C\u002Fp>\n\u003Ch2 id=\"section-63\">Lokalni agentski stek\u003C\u002Fh2>\n\u003Csection class=\"editorjs-process my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Korisna perspektiva za razumevanje G-Assist-a\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. Korisnička namera\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Komanda na prirodnom jeziku ili glasovna komanda.\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. Lokalni SLM\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Razume zahtev i bira sposobnost.\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. Znanje \u002F kontekst\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Pruža znanje o proizvodu, preporuke ili informacije potrebne za odluku.\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. Stanje sistema uživo\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Pruža trenutne informacije o hardveru, drajverima, performansama ili konfiguraciji kada je to podržano.\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. Izbor alata\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Bira se ugrađena funkcija ili dodatak.\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. Strukturisano izvršavanje\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Funkcija prima argumente i izvršava stvarnu radnju.\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. Verifikacija rezultata\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Alat vraća status ili podatke, a model objašnjava šta se dogodilo.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-65\">Zašto su granice alata bezbednosna karakteristika\u003C\u002Fh2>\n\u003Cp>AI asistent koji bi mogao da izvršava proizvoljne komande operativnog sistema bio bi daleko moćniji, ali i mnogo teže ograničen.\u003C\u002Fp>\n\u003Cp>G-Assist umesto toga izlaže definisane funkcije sa poznatim parametrima.\u003C\u002Fp>\n\u003Cp>To znači da model može da izvrši samo radnje koje omogućava ugrađeni skup funkcija ili instalirani dodaci.\u003C\u002Fp>\n\u003Cp>Ovo ne uklanja sav rizik, posebno kod dodataka trećih strana, ali stvara jasniju granicu dozvola i sposobnosti od neograničenog pristupa ljusci.\u003C\u002Fp>\n\u003Ch2 id=\"section-70\">Granica ovlašćenja alata\u003C\u002Fh2>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Šta asistent može da razume naspram onoga što sme da uradi\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\">Model može da razume\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\">Ovlašćenje alata\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\">Podešavanje GPU-a\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\">Datoteke\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\">Kontrola perifernih uređaja\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\">Zašto G-Assist može privremeno da smanji performanse igre\u003C\u002Fh2>\n\u003Cp>Arhitektura lokalnog modela ima jednostavnu posledicu: AI i igra mogu da se takmiče za isti GPU.\u003C\u002Fp>\n\u003Cp>NVIDIA eksplicitno upozorava da brzina renderovanja ili brzina inferencije može nakratko da opadne dok G-Assist obrađuje zahtev tokom radnog opterećenja koje intenzivno koristi GPU.\u003C\u002Fp>\n\u003Cp>Kada se inferencija završi, ti GPU resursi se vraćaju igri.\u003C\u002Fp>\n\u003Cp>Ovo se razlikuje od cloud asistenta, gde se većina inferencije modela odvija na udaljenom serveru i ne troši gaming GPU.\u003C\u002Fp>\n\u003Ch2 id=\"section-77\">Test resursa lokalnog asistenta\u003C\u002Fh2>\n\u003Csection class=\"editorjs-process my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Kako proceniti da li lokalni gaming asistent odgovara vašem računaru\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. Proverite instaliranu VRAM\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Trenutni G-Assist baseline je RTX GPU sa najmanje 6 GB 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. Proverite slobodnu VRAM tokom same igre\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Instalirani kapacitet nije isto što i slobodan kapacitet.\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. Izaberite Reasoning ili Flash režim na odgovarajući način\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Koristite lakši režim kada je pritisak na resurse važniji od dubokog rezonovanja.\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. Izmerite padove frejma tokom inferencije\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Posmatrajte igru dok tražite od G-Assist da obavlja zadatke.\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. Proverite ovlašćenja alata\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Znajte tačno koje ugrađene funkcije i plug-inovi mogu da menjaju vaš sistem.\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. Tretirajte plug-inove trećih strana kao softver\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Pregledajte njihov izvorni kod, dozvole, mrežni pristup i sačuvane akreditive.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-79\">Zašto plug-inovi zaslužuju isto ispitivanje kao i svaki drugi softver\u003C\u002Fh2>\n\u003Cp>Plug-in može da poveže asistenta sa API-jima, perifernim aplikacijama i onlajn servisima.\u003C\u002Fp>\n\u003Cp>To znači da plug-in može da rukuje konfiguracionim vrednostima, akreditivima ili eksternim zahtevima u zavisnosti od toga za šta je napravljen.\u003C\u002Fp>\n\u003Cp>NVIDIA repozitorijum eksplicitno obezbeđuje lokaciju config.json za podešavanja plug-ina i upozorava programere da ne commit-uju akreditive.\u003C\u002Fp>\n\u003Cp>Ispravno bezbednosno pitanje stoga nije samo „Da li je G-Assist lokalni?“ već i „Na šta se povezuje svaki instalirani plug-in?“\u003C\u002Fp>\n\u003Ch2 id=\"section-84\">G-Assist je bliži agentu nego chatbot-u\u003C\u002Fh2>\n\u003Cp>Chatbot uglavnom proizvodi jezik.\u003C\u002Fp>\n\u003Cp>Agent tumači cilj, posmatra relevantne informacije, bira akciju, poziva alat i procenjuje rezultat.\u003C\u002Fp>\n\u003Cp>G-Assist sada mnogo bliže odgovara tom drugom opisu jer može da koordinira više akcija, pregleda podržano stanje računara i poziva prave alate.\u003C\u002Fp>\n\u003Caside class=\"editorjs-referral my-6\">\u003Ca href=\"https:\u002F\u002Ffigure.rocks\u002Fsr\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 pokazuje zašto AI saigračima trebaju dva mozga: brzi refleksi i sporo rezonovanje\u003C\u002Fstrong>\u003Cp class=\"mt-2 text-sm text-gray-600 dark:text-gray-300\">Primer arhitekture game-agenta koji pokazuje razdvajanje između rezonovanja, stanja uživo, alata i determinističkog izvršavanja.\u003C\u002Fp>\u003Cspan class=\"mt-3 inline-flex text-sm font-medium text-primary-600 dark:text-primary-400\">Pročitajte vodič za PUBG Ally arhitekturu →\u003C\u002Fspan>\u003C\u002Fdiv>\u003C\u002Fa>\u003C\u002Faside>\n\u003Ch2 id=\"section-89\">Šta G-Assist još uvek nije\u003C\u002Fh2>\n\u003Cp>NVIDIA eksplicitno opisuje G-Assist kao specijalizovanog lokalnog asistenta, a ne kao AI opšte namene za razgovor.\u003C\u002Fp>\n\u003Cp>Njegova vrednost proizlazi iz razumevanja fokusiranog skupa PC i gejming zadataka i posedovanja alata povezanih sa tim zadacima.\u003C\u002Fp>\n\u003Cp>Taj fokus je važan jer manji lokalni model može biti koristan kada mu okolni sistem pruža jake alate i jasne granice.\u003C\u002Fp>\n\u003Ch2 id=\"section-93\">Šta se promenilo u trenutnim verzijama?\u003C\u002Fh2>\n\u003Cp>Trenutna javna istorija izdanja pokazuje da G-Assist ravnomerno napreduje ka sposobnijem lokalnom agentu.\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\">Verzija\u003C\u002Fth>\u003Cth class=\"border border-gray-300 px-4 py-2 text-left font-semibold\">Važna promena\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\">Lakši model, sve RTX GPU sa 6 GB+ VRAM, dodaci zajednice\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\">Optimizacija za laptop, kontrole BatteryBoost i 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\">Režim rezonovanja, Flash režim, upiti sa više radnji, nove kontrole uređaja\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\">Poboljšan sistem znanja, bolje preporuke, kontrole RTX funkcija\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\">Elgato Stream Deck integracija putem MCP servera\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003C\u002Fdiv>\n\u003Ch2 id=\"section-96\">Šta bi promenilo ovaj odgovor?\u003C\u002Fh2>\n\u003Cp>G-Assist je još uvek eksperimentalan i njegova arhitektura se razvija.\u003C\u002Fp>\n\u003Cp>Veličina modela, zahtevi za VRAM, skup alata, protokol dodataka i podrška za hardver mogu se promeniti u budućim izdanjima.\u003C\u002Fp>\n\u003Cp>Buduća verzija bi takođe mogla prebaciti deo inferencije na NPU ili uvesti širu MCP integraciju, ali to ne treba pretpostavljati dok NVIDIA to ne dokumentuje.\u003C\u002Fp>\n\u003Ch2 id=\"section-100\">Ograničenja\u003C\u002Fh2>\n\u003Cp>Ovaj članak opisuje NVIDIA-inu javnu dokumentaciju proizvoda G-Assist i javnu arhitekturu dodataka zaključno sa septembrom 2026.\u003C\u002Fp>\n\u003Cp>NVIDIA ne dokumentuje javno svaki interni detalj svog sistema znanja i preporuka, tako da ovaj članak ne tvrdi da svaki odgovor zasnovan na znanju koristi RAG ili bilo koju drugu specifičnu implementaciju pretraživanja.\u003C\u002Fp>\n\u003Cp>Dodaci trećih strana mogu imati ponašanje i mrežni pristup izvan NVIDIA-inih ugrađenih funkcija, tako da svaki dodatak treba posebno proceniti.\u003C\u002Fp>\n\u003Ch2 id=\"section-104\">Zaključak\u003C\u002Fh2>\n\u003Cp>Najlakši način da razumete Project G-Assist je da prestanete da o njemu razmišljate kao o chatbotu.\u003C\u002Fp>\n\u003Cp>Lokalni SLM tumači vaš zahtev. Znanje mu pomaže da razume problem. Informacije o sistemu uživo mu govore šta je istina na vašem računaru. Ugrađena funkcija ili dodatak definiše šta mu je zapravo dozvoljeno da radi. Alat izvršava radnju i vraća rezultat.\u003C\u002Fp>\n\u003Cp>To je arhitektura lokalnog agenta.\u003C\u002Fp>\n\u003Cp>Njegova najjača ideja nije da model sa 8 milijardi parametara može da govori o vašem GPU. Već da relativno mali lokalni model može postati koristan kada je povezan sa dobro definisanim alatima, trenutnim stanjem i kontrolisanom granicom delovanja.\u003C\u002Fp>\n\u003Ch2 id=\"section-109\">Često postavljana pitanja\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 jednostavnim jezikom\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\">Da li je G-Assist cloud chatbot?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Ne. Njegov osnovni jezički model radi lokalno na GeForce RTX GPU i može da radi offline za podržane lokalne funkcije.\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\">Koji model koristi G-Assist?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">NVIDIA ga trenutno opisuje kao lokalni Llama-based instruct model sa 8 milijardi parametara.\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\">Da li AI model direktno menja moja GPU podešavanja?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Ne. Model bira podržanu ugrađenu funkciju ili plug-in, a taj alat obavlja stvarnu promenu.\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\">Da li G-Assist koristi VRAM tokom igranja?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Da. NVIDIA preporučuje dodatni slobodan VRAM za asistenta i upozorava da inferencija može nakratko smanjiti performanse renderovanja igre.\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\">Da li su G-Assist plug-inovi MCP plug-inovi?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Ne direktno. G-Assist sopstveni trenutni plug-in protokol koristi JSON-RPC 2.0, iako plug-in može da se poveže na MCP server.\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\">Može li G-Assist da radi offline?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Njegov lokalni asistent može, ali pojedinačni plug-inovi mogu i dalje zahtevati pristup internetu ako pozivaju online servise.\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\">Da li je G-Assist opšti AI asistent?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">NVIDIA ga opisuje kao specijalizovanog PC i gaming asistenta, a ne kao široki opšti konverzacioni model.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-111\">Pojmovnik\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\">Ključni G-Assist pojmovi\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, kompaktan jezički model dizajniran da radi lokalno sa nižim hardverskim zahtevima od velikih cloud modela.\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\">Pozivanje alata\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Proces u kojem jezički model bira definisanu funkciju i dostavlja strukturisane argumente kako bi druga komponenta mogla da izvrši radnju.\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\">Ekstenzija koja izlaže dodatne funkcije ili integracije G-Assist-u.\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\">Strukturisani protokol poruka koji koristi trenutni G-Assist Protocol V2 plug-in sistem.\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, odvojeni protokol za interoperabilnost alata i konteksta koji neke eksterne integracije mogu da izlože.\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\">Granica između alata i ovlašćenja\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Figure Rocks model koji razdvaja ono što AI model može da razume od onoga što njegovi povezani alati zapravo dozvoljavaju da uradi.\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\">Lokalni agent stack\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Figure Rocks model koji kombinuje korisničku nameru, lokalni SLM, znanje, trenutno stanje, izbor alata, izvršavanje i verifikaciju rezultata.\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 resursa lokalnog asistenta\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Figure Rocks radni tok za procenu VRAM-a, troškova inferencije, dozvola alata i rizika plug-inova pre korišćenja lokalnog gaming asistenta.\u003C\u002Fdd>\u003C\u002Fdiv>\u003C\u002Fdl>\u003C\u002Fsection>\n\u003Ch2 id=\"section-113\">Primarni izvori\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\">Zvanična trenutna stranica proizvoda koja pokriva lokalni model, podržane funkcije, Reasoning i Flash režime, VRAM zahteve, RTX kontrole, plug-inove i verziju 0.2.2 MCP-bazirane Elgato integracije.\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\">Zvanični javni repozitorijum plug-inova koji dokumentuje G-Assist arhitekturu modula, otkrivanje plug-inova i 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 — G-Assist Protocol V2 vodič za migraciju\u003C\u002Fstrong>\u003Cp class=\"text-sm text-gray-600 dark:text-gray-400\">Zvanična dokumentacija protokola koja pokriva JSON-RPC 2.0, inicijalizaciju, provere zdravlja, izvršavanje, streaming, završetak i ponašanje plug-in SDK-a.\u003C\u002Fp>\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fblogs.nvidia.com\u002Fblog\u002Frtx-ai-garage-gamescom-g-assist-rtx-remix\u002F\" target=\"_blank\" rel=\"noopener noreferrer\" class=\"editorjs-link-tool block border border-gray-200 dark:border-gray-700 rounded-lg p-4 transition text-gray-900 dark:text-gray-100 hover:border-primary-500 hover:bg-primary-50 dark:hover:bg-gray-900 hover:text-gray-900 dark:hover:text-gray-100\">\u003Cstrong class=\"block font-semibold\">NVIDIA Blog — Lagani G-Assist model\u003C\u002Fstrong>\u003Cp class=\"text-sm text-gray-600 dark:text-gray-400\">Zvanična pozadina o G-Assist modelu sa manje memorije, podršci za 6 GB RTX GPU-ove i čvorištu plug-inova zajednice.\u003C\u002Fp>\u003C\u002Fa>",{"time":538,"blocks":539,"version":1437},1790407874061,[540,546,554,561,568,574,579,584,589,596,601,627,632,637,642,647,678,683,688,693,698,723,730,739,744,749,754,759,764,769,774,779,784,789,794,799,804,809,815,823,828,833,838,862,867,872,877,882,903,908,913,918,923,951,956,961,966,971,977,982,987,992,997,1002,1029,1034,1039,1044,1049,1054,1059,1086,1091,1096,1101,1106,1111,1116,1140,1145,1150,1155,1160,1165,1170,1175,1180,1185,1193,1198,1203,1208,1213,1218,1223,1247,1252,1257,1262,1267,1272,1277,1282,1287,1292,1297,1302,1307,1312,1317,1352,1357,1395,1400,1410,1419,1428],{"id":541,"data":542,"type":544,"tunes":545},"3cee674645",{"text":543},"NVIDIA Project G-Assist izgleda kao chatbot, ali taj opis promašuje suštinu. To je lokalni AI sistem koji može da razume zahtev, pregleda podržano stanje računara, izabere alat ili dodatak i zatim izvrši stvarnu radnju kao što je promena DLSS podešavanja, provera drajvera, podešavanje profila ventilatora ili upravljanje perifernim uređajem.","paragraph",{},{"id":547,"data":548,"type":552,"tunes":553},"24a1733ca8",{"body":549,"title":550,"variant":551},"\u003Cstrong>G-Assist nije samo chatbot za vašu grafičku karticu.\u003C\u002Fstrong> To je lokalni mali jezički model povezan sa skupom dozvoljenih alata. Model tumači šta želite, bira podržanu funkciju, prosleđuje argumente toj funkciji, a alat na strani računara izvršava radnju.","Direktan odgovor","info","callout",{},{"id":555,"data":556,"type":552,"tunes":560},"1fcbe512dc",{"body":557,"title":558,"variant":559},"\u003Cstrong>SLM = razume zahtev.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Znanje = objašnjava podržane NVIDIA\u002FPC koncepte.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Alati = izvršavaju radnje.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Dodaci = dodaju nove alate.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Vaš računar = okruženje koje se pregleda ili menja.\u003C\u002Fstrong>","Najlakši mentalni model","note",{},{"id":562,"data":563,"type":566,"tunes":567},"2a609230a5",{"title":564,"maxLevel":565,"minLevel":47},"Sadržaj",3,"tableOfContents",{},{"id":569,"data":570,"type":572,"tunes":573},"a52f97cb62",{"text":571,"level":47},"Prvo: šta AI model zapravo radi?","header",{},{"id":575,"data":576,"type":544,"tunes":578},"1871a0d8e6",{"text":577},"G-Assist koristi lokalni mali jezički model, ili SLM. NVIDIA trenutno opisuje sistem kao korišćenje Llama-baziranog instrukcionog modela sa 8 milijardi parametara.",{},{"id":580,"data":581,"type":544,"tunes":583},"cfbc6473c4",{"text":582},"Glavni zadatak modela nije da renderuje grafiku ili direktno menja hardverske registre. Njegov zadatak je da razume jezik korisnika, odluči koja podržana mogućnost odgovara zahtevu i pripremi poziv toj mogućnosti.",{},{"id":585,"data":586,"type":544,"tunes":588},"53cadaaeb6",{"text":587},"Na primer, ako kažete „postavi DLSS Super Resolution na režim performansi“, jezički model sam ne menja DLSS. On tumači komandu i usmerava je ka podržanoj funkciji koja može da promeni podešavanje.",{},{"id":590,"data":591,"type":552,"tunes":595},"5d8e508019",{"body":592,"title":593,"variant":594},"AI model \u003Cstrong>odlučuje koji alat pozvati\u003C\u002Fstrong>. Alat \u003Cstrong>obavlja pravi posao\u003C\u002Fstrong>.","Važna razlika","success",{},{"id":597,"data":598,"type":572,"tunes":600},"9ce7e91c28",{"text":599,"level":47},"G-Assist tok izvršavanja radnji",{},{"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. Dajete zahtev prirodnim jezikom","Na primer: „Optimizuj ovu igru za performanse.“",{"label":609,"description":610},"2. Lokalni SLM tumači zahtev","Određuje nameru korisnika i identifikuje koja je podržana funkcija ili dodatak relevantan.",{"label":612,"description":613},"3. Sistem bira alat","To može biti ugrađena funkcija za grafička podešavanja, provera drajvera, funkcija nadzora ili dodatak zajednice.",{"label":615,"description":616},"4. Argumenti se izvlače","Model pretvara zahtev u strukturisane vrednosti kao što su naziv igre, režim, profil ventilatora ili DLSS podešavanje.",{"label":618,"description":619},"5. Alat se izvršava","Alat komunicira sa NVIDIA aplikacijom, operativnim sistemom, softverom perifernog uređaja ili drugim servisom.",{"label":621,"description":622},"6. Rezultat se vraća","G-Assist prijavljuje šta se dogodilo ili vraća podatke koje model može da objasni.","Šta se dešava nakon što date G-Assist-u komandu","auto","processFlow",{},{"id":628,"data":629,"type":572,"tunes":631},"aba1e38958",{"text":630,"level":47},"Ovo je pozivanje alata, a ne magična kontrola računara",{},{"id":633,"data":634,"type":544,"tunes":636},"0a7cb6107d",{"text":635},"Jezički model ne može bezbedno da kontroliše proizvoljan računar samo zato što razume engleski.",{},{"id":638,"data":639,"type":544,"tunes":641},"31191a478c",{"text":640},"Potreban mu je definisan interfejs koji kaže koje radnje postoje, koje argumente prihvataju i šta alat vraća.",{},{"id":643,"data":644,"type":544,"tunes":646},"af3d1a846f",{"text":645},"Trenutne ugrađene mogućnosti G-Assist-a uključuju funkcije kao što su optimizacija grafičkih podešavanja, promena podržanih RTX opcija, provera ili preuzimanje drajvera, prikaz informacija o performansama, promena nekih funkcija napajanja na laptopu, upravljanje podržanim funkcijama monitora i korišćenje podržanih dodataka za periferne uređaje.",{},{"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","Razume „uključi DLSS“",[13,13],{"id":656,"label":657,"values":658},"decide","Bira ispravnu funkciju",[13,13],{"id":660,"label":661,"values":662},"change","Zaista menja podešavanje",[13,13],{"id":664,"label":665,"values":666},"explain","Objašnjava rezultat",[13,13],"Jezički model naspram alata","table",[670,673],{"id":671,"label":672},"model","Jezički model",{"id":674,"label":675},"tool","Alat \u002F dodatak","comparison",{},{"id":679,"data":680,"type":572,"tunes":682},"1537be641c",{"text":681,"level":47},"Šta je sloj znanja?",{},{"id":684,"data":685,"type":544,"tunes":687},"1db6e2e4b5",{"text":686},"G-Assist takođe ima sloj znanja za odgovaranje na pitanja i davanje preporuka.",{},{"id":689,"data":690,"type":544,"tunes":692},"616d72b881",{"text":691},"NVIDIA kaže da je verzija 0.2.1 uvela poboljšani sistem znanja koji pomaže G-Assist-u da daje tačnije preporuke za podešavanja.",{},{"id":694,"data":695,"type":544,"tunes":697},"eb987c41e5",{"text":696},"Taj sloj znanja se razlikuje od trenutnog stanja vašeg računara.",{},{"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","Podešavanja igre",[13,13],{"id":711,"label":712,"values":713},"system","Performanse",[13,13],"Znanje naspram trenutnog stanja računara",[716,719],{"id":717,"label":718},"knowledge","Znanje",{"id":720,"label":721},"state","Trenutno stanje",{},{"id":724,"data":725,"type":552,"tunes":729},"2bac13ef99",{"body":726,"title":727,"variant":728},"\u003Cstrong>Znanje\u003C\u002Fstrong> govori asistentu šta neka funkcija znači ili šta je obično važno.\u003Cbr>\u003Cstrong>Stanje\u003C\u002Fstrong> mu govori šta je trenutno tačno na vašoj mašini.","Ne mešajte znanje sa stanjem","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","Šta je RAG? Najjednostavnije objašnjenje kako funkcioniše","Jednostavno objašnjenje na engleskom o pronalaženju znanja, stanju, memoriji, kontekstu i jezičkom modelu.","Pročitajte jednostavan vodič o RAG-u","referralArticle",{},{"id":740,"data":741,"type":572,"tunes":743},"acbb9b7940",{"text":742,"level":47},"Da li G-Assist koristi RAG?",{},{"id":745,"data":746,"type":544,"tunes":748},"ce0371e492",{"text":747},"Najsigurniji odgovor je: G-Assist očigledno ima sistem znanja, ali NVIDIA-ina javna stranica proizvoda ne dokumentuje svaki interni mehanizam pronalaženja dovoljno detaljno da bi se moglo reći da svaki odgovor zasnovan na znanju specifično proizvodi RAG.",{},{"id":750,"data":751,"type":544,"tunes":753},"c2226e5ec5",{"text":752},"Arhitektonska razlika je i dalje važna. Sloj za pronalaženje može da pruži relevantno znanje, dok sistemski alati pružaju trenutno stanje računara i izvršavaju radnje.",{},{"id":755,"data":756,"type":544,"tunes":758},"e5137fc2c8",{"text":757},"To je isto razdvajanje koje se koristi u mnogim modernim agentima: znanje je jedan izvor konteksta, trenutna zapažanja su drugi, a izvršavanje alata je treći.",{},{"id":760,"data":761,"type":572,"tunes":763},"059b89dedb",{"text":762,"level":47},"Zašto G-Assist može da radi van mreže",{},{"id":765,"data":766,"type":544,"tunes":768},"19447df6a4",{"text":767},"NVIDIA pokreće jezički model lokalno na GeForce RTX GPU.",{},{"id":770,"data":771,"type":544,"tunes":773},"55aee6ada7",{"text":772},"To znači da osnovni asistent ne zahteva jezički model hostovan u oblaku za svaki upit.",{},{"id":775,"data":776,"type":544,"tunes":778},"f265d1fd96",{"text":777},"NVIDIA eksplicitno navodi da G-Assist može da radi van mreže za svoje lokalne mogućnosti.",{},{"id":780,"data":781,"type":544,"tunes":783},"1dc8613200",{"text":782},"Dodatak i dalje može da koristi internet ako taj dodatak poziva onlajn servis. Lokalno izvršavanje modela i onlajn pristup dodataka su odvojena pitanja.",{},{"id":785,"data":786,"type":572,"tunes":788},"ee01c97a66",{"text":787,"level":47},"Cena lokalne AI: G-Assist koristi vaš GPU i VRAM",{},{"id":790,"data":791,"type":544,"tunes":793},"1784ad3fcf",{"text":792},"Lokalno pokretanje pruža privatnost i nezavisnost od modela u oblaku, ali rad mora negde da se izvrši.",{},{"id":795,"data":796,"type":544,"tunes":798},"1275ab759f",{"text":797},"Za G-Assist, to negde je isti GeForce RTX GPU koji možda već renderuje vašu igru.",{},{"id":800,"data":801,"type":544,"tunes":803},"cec86f847a",{"text":802},"NVIDIA upozorava da GPU nakratko dodeljuje računarske resurse za AI inferenciju kada G-Assist odgovara. Ako se istovremeno pokreće zahtevna igra, igra može privremeno da izgubi deo performansi renderovanja dok je model aktivan.",{},{"id":805,"data":806,"type":544,"tunes":808},"e6ea700df6",{"text":807},"Trenutni zahtevi takođe navode ciljne vrednosti slobodne VRAM memorije koja prevazilazi memoriju koju igra već koristi: približno 6 GB slobodne VRAM memorije za Reasoning Mode i 4,5 GB za Flash Mode.",{},{"id":810,"data":811,"type":552,"tunes":814},"2126f74de5",{"body":812,"title":813,"variant":728},"Igra, Windows, drajver i druge aplikacije već troše VRAM. G-Assist sopstveni zahtev odnosi se na \u003Cstrong>slobodnu VRAM memoriju pored one koju pokrenuti radni zadatak već koristi\u003C\u002Fstrong>.","8 GB VRAM ne znači da je 8 GB dostupno za G-Assist",{},{"id":816,"data":817,"type":737,"tunes":822},"13c0dcb3f3",{"url":818,"title":819,"excerpt":820,"ctaLabel":821},"https:\u002F\u002Ffigure.rocks\u002Fsr\u002Fblog\u002Fvram-usage-is-not-vram-requirement-why-a-full-memory-meter-does-not-tell-the-whole-story","Korišćenje VRAM nije isto što i zahtev za VRAM: Zašto pun memorni merač ne govori celu priču","Zašto su instalirana VRAM, trenutno korišćenje, budžeti za rezidentnost i stvarni memorni pritisak različite stvari.","Pročitajte vodič za VRAM",{},{"id":824,"data":825,"type":572,"tunes":827},"d684b2c1c8",{"text":826,"level":47},"Reasoning Mode naspram Flash Mode",{},{"id":829,"data":830,"type":544,"tunes":832},"3c1f2379db",{"text":831},"Trenutne verzije G-Assist razdvajaju sposobniji Reasoning Mode od bržeg Flash Mode.",{},{"id":834,"data":835,"type":544,"tunes":837},"86f50ebd33",{"text":836},"Reasoning Mode je dizajniran za odluke višeg kvaliteta i može da koordinira više radnji iz jednog upita. Flash Mode je optimizovan za brže odgovore i manju potrošnju resursa.",{},{"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","Primarni cilj",[13,13],{"id":847,"label":848,"values":849},"vram","Preporučena slobodna VRAM",[13,13],{"id":851,"label":852,"values":853},"use","Najbolje odgovara",[13,13],[855,858],{"id":856,"label":857},"reasoning","Reasoning Mode",{"id":859,"label":860},"flash","Flash Mode",{},{"id":863,"data":864,"type":572,"tunes":866},"cef1bcf553",{"text":865,"level":47},"Šta plug-inovi zapravo dodaju",{},{"id":868,"data":869,"type":544,"tunes":871},"d380d5e28b",{"text":870},"Plug-in ne zamenjuje jezički model. On daje modelu novu radnju koju sme da pozove.",{},{"id":873,"data":874,"type":544,"tunes":876},"434979ebda",{"text":875},"Plug-in definiše funkcije, opise i parametre. G-Assist čita te opise, uparuje korisnički zahtev sa odgovarajućom funkcijom i šalje joj strukturisane argumente.",{},{"id":878,"data":879,"type":544,"tunes":881},"21ebe69c79",{"text":880},"To omogućava asistentu da raste izvan NVIDIA ugrađenih funkcija.",{},{"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. Plug-in deklariše funkciju","Na primer: set_keyboard_color(color).",{"label":890,"description":891},"2. Manifest opisuje funkciju","Manifest govori G-Assist-u šta funkcija radi i koje parametre zahteva.",{"label":893,"description":894},"3. Korisnik pita prirodno","Na primer: „Napravi moju tastaturu zelenom.“",{"label":896,"description":897},"4. SLM bira funkciju","Model mapira zahtev na funkciju plug-ina i izvlači zeleno kao parametar.",{"label":899,"description":900},"5. Plug-in izvršava","Plug-in komunicira sa softverom perifernog uređaja ili eksternim servisom.","Kako funkcioniše G-Assist plug-in",{},{"id":904,"data":905,"type":572,"tunes":907},"1dc857ce2f",{"text":906,"level":47},"G-Assist Protocol V2 je JSON-RPC 2.0",{},{"id":909,"data":910,"type":544,"tunes":912},"02bdb0566d",{"text":911},"NVIDIA trenutni javni repozitorijum plug-inova koristi Protocol V2.",{},{"id":914,"data":915,"type":544,"tunes":917},"f82da294cf",{"text":916},"Protocol V2 koristi JSON-RPC 2.0 sa porukama prefiksiranim dužinom između G-Assist engine-a i plug-inova.",{},{"id":919,"data":920,"type":544,"tunes":922},"530c3cf9b9",{"text":921},"Engine može da inicijalizuje plug-in, proveri njegovo zdravlje, izvrši funkciju, pošalje korisnički unos i isključi ga. Plug-inovi mogu da vrate rezultate, strimuju napredak ili prijave greške.",{},{"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],"Važne Protocol V2 poruke",[944,947],{"id":945,"label":946},"direction","Smer",{"id":948,"label":949},"purpose","Svrha",{},{"id":952,"data":953,"type":572,"tunes":955},"304fbd9944",{"text":954,"level":47},"Gde MCP ulazi u sliku",{},{"id":957,"data":958,"type":544,"tunes":960},"fae73881e4",{"text":959},"G-Assist sopstveni protokol za dodatke nije MCP. Njegov trenutni javni sistem dodataka koristi JSON-RPC 2.0.",{},{"id":962,"data":963,"type":544,"tunes":965},"551d11710a",{"text":964},"Međutim, G-Assist dodatak može da se poveže sa MCP serverom.",{},{"id":967,"data":968,"type":544,"tunes":970},"0537fb222a",{"text":969},"NVIDIA trenutna verzija 0.2.2 uključuje Elgato integraciju koja može da pozove radnje izložene putem Elgato Stream Deck MCP servera.",{},{"id":972,"data":973,"type":552,"tunes":976},"760a86ad19",{"body":974,"title":975,"variant":594},"\u003Cstrong>G-Assist ↔ njegov dodatak:\u003C\u002Fstrong> NVIDIA Protocol V2 \u002F JSON-RPC 2.0.\u003Cbr>\u003Cstrong>Dodatak ↔ drugi ekosistem alata:\u003C\u002Fstrong> može da koristi MCP kada ta integracija to podržava.","Važna razlika u protokolu",{},{"id":978,"data":979,"type":572,"tunes":981},"bd182f72b0",{"text":980,"level":47},"Zašto je ovo važno van RGB svetala",{},{"id":983,"data":984,"type":544,"tunes":986},"d072506ce2",{"text":985},"Arhitektura dodataka pretvara G-Assist iz fiksnog asistenta u lokalni usmerivač alata.",{},{"id":988,"data":989,"type":544,"tunes":991},"2876e067dc",{"text":990},"Isti obrazac može da poveže SLM sa alatima za nadzor, perifernim uređajima, API-jevima, automatizovanim sistemima, lokalnim aplikacijama ili eksternim servisima.",{},{"id":993,"data":994,"type":544,"tunes":996},"37689640e9",{"text":995},"Važna arhitektonska jedinica stoga nije prozor za ćaskanje. To je granica između namere na prirodnom jeziku i strukturisanog izvršavanja alata.",{},{"id":998,"data":999,"type":572,"tunes":1001},"550fbb42d4",{"text":1000,"level":47},"Lokalni agentski stek",{},{"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. Korisnička namera","Komanda na prirodnom jeziku ili glasovna komanda.",{"label":1010,"description":1011},"2. Lokalni SLM","Razume zahtev i bira sposobnost.",{"label":1013,"description":1014},"3. Znanje \u002F kontekst","Pruža znanje o proizvodu, preporuke ili informacije potrebne za odluku.",{"label":1016,"description":1017},"4. Stanje sistema uživo","Pruža trenutne informacije o hardveru, drajverima, performansama ili konfiguraciji kada je to podržano.",{"label":1019,"description":1020},"5. Izbor alata","Bira se ugrađena funkcija ili dodatak.",{"label":1022,"description":1023},"6. Strukturisano izvršavanje","Funkcija prima argumente i izvršava stvarnu radnju.",{"label":1025,"description":1026},"7. Verifikacija rezultata","Alat vraća status ili podatke, a model objašnjava šta se dogodilo.","Korisna perspektiva za razumevanje G-Assist-a",{},{"id":1030,"data":1031,"type":572,"tunes":1033},"6c976db763",{"text":1032,"level":47},"Zašto su granice alata bezbednosna karakteristika",{},{"id":1035,"data":1036,"type":544,"tunes":1038},"ba65a3b467",{"text":1037},"AI asistent koji bi mogao da izvršava proizvoljne komande operativnog sistema bio bi daleko moćniji, ali i mnogo teže ograničen.",{},{"id":1040,"data":1041,"type":544,"tunes":1043},"a932df9663",{"text":1042},"G-Assist umesto toga izlaže definisane funkcije sa poznatim parametrima.",{},{"id":1045,"data":1046,"type":544,"tunes":1048},"7d1d45c83d",{"text":1047},"To znači da model može da izvrši samo radnje koje omogućava ugrađeni skup funkcija ili instalirani dodaci.",{},{"id":1050,"data":1051,"type":544,"tunes":1053},"10460fda21",{"text":1052},"Ovo ne uklanja sav rizik, posebno kod dodataka trećih strana, ali stvara jasniju granicu dozvola i sposobnosti od neograničenog pristupa ljusci.",{},{"id":1055,"data":1056,"type":572,"tunes":1058},"25049448ea",{"text":1057,"level":47},"Granica ovlašćenja alata",{},{"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},"Podešavanje GPU-a",[13,13],{"id":1067,"label":1068,"values":1069},"files","Datoteke",[13,13],{"id":1071,"label":1072,"values":1073},"web","Internet",[13,13],{"id":1075,"label":1076,"values":1077},"device","Kontrola perifernih uređaja",[13,13],"Šta asistent može da razume naspram onoga što sme da uradi",[1080,1082],{"id":652,"label":1081},"Model može da razume",{"id":1083,"label":1084},"authority","Ovlašćenje alata",{},{"id":1087,"data":1088,"type":572,"tunes":1090},"8fd8e35c51",{"text":1089,"level":47},"Zašto G-Assist može privremeno da smanji performanse igre",{},{"id":1092,"data":1093,"type":544,"tunes":1095},"f75234546f",{"text":1094},"Arhitektura lokalnog modela ima jednostavnu posledicu: AI i igra mogu da se takmiče za isti GPU.",{},{"id":1097,"data":1098,"type":544,"tunes":1100},"28bc054afa",{"text":1099},"NVIDIA eksplicitno upozorava da brzina renderovanja ili brzina inferencije može nakratko da opadne dok G-Assist obrađuje zahtev tokom radnog opterećenja koje intenzivno koristi GPU.",{},{"id":1102,"data":1103,"type":544,"tunes":1105},"0823573513",{"text":1104},"Kada se inferencija završi, ti GPU resursi se vraćaju igri.",{},{"id":1107,"data":1108,"type":544,"tunes":1110},"905eed843d",{"text":1109},"Ovo se razlikuje od cloud asistenta, gde se većina inferencije modela odvija na udaljenom serveru i ne troši gaming GPU.",{},{"id":1112,"data":1113,"type":572,"tunes":1115},"839c0e3988",{"text":1114,"level":47},"Test resursa lokalnog asistenta",{},{"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. Proverite instaliranu VRAM","Trenutni G-Assist baseline je RTX GPU sa najmanje 6 GB VRAM.",{"label":1124,"description":1125},"2. Proverite slobodnu VRAM tokom same igre","Instalirani kapacitet nije isto što i slobodan kapacitet.",{"label":1127,"description":1128},"3. Izaberite Reasoning ili Flash režim na odgovarajući način","Koristite lakši režim kada je pritisak na resurse važniji od dubokog rezonovanja.",{"label":1130,"description":1131},"4. Izmerite padove frejma tokom inferencije","Posmatrajte igru dok tražite od G-Assist da obavlja zadatke.",{"label":1133,"description":1134},"5. Proverite ovlašćenja alata","Znajte tačno koje ugrađene funkcije i plug-inovi mogu da menjaju vaš sistem.",{"label":1136,"description":1137},"6. Tretirajte plug-inove trećih strana kao softver","Pregledajte njihov izvorni kod, dozvole, mrežni pristup i sačuvane akreditive.","Kako proceniti da li lokalni gaming asistent odgovara vašem računaru",{},{"id":1141,"data":1142,"type":572,"tunes":1144},"ca52c48d2e",{"text":1143,"level":47},"Zašto plug-inovi zaslužuju isto ispitivanje kao i svaki drugi softver",{},{"id":1146,"data":1147,"type":544,"tunes":1149},"8e6a760529",{"text":1148},"Plug-in može da poveže asistenta sa API-jima, perifernim aplikacijama i onlajn servisima.",{},{"id":1151,"data":1152,"type":544,"tunes":1154},"be793240e1",{"text":1153},"To znači da plug-in može da rukuje konfiguracionim vrednostima, akreditivima ili eksternim zahtevima u zavisnosti od toga za šta je napravljen.",{},{"id":1156,"data":1157,"type":544,"tunes":1159},"3c6c4c9aaf",{"text":1158},"NVIDIA repozitorijum eksplicitno obezbeđuje lokaciju config.json za podešavanja plug-ina i upozorava programere da ne commit-uju akreditive.",{},{"id":1161,"data":1162,"type":544,"tunes":1164},"03413f935a",{"text":1163},"Ispravno bezbednosno pitanje stoga nije samo „Da li je G-Assist lokalni?“ već i „Na šta se povezuje svaki instalirani plug-in?“",{},{"id":1166,"data":1167,"type":572,"tunes":1169},"f473162e86",{"text":1168,"level":47},"G-Assist je bliži agentu nego chatbot-u",{},{"id":1171,"data":1172,"type":544,"tunes":1174},"59dd3df9c2",{"text":1173},"Chatbot uglavnom proizvodi jezik.",{},{"id":1176,"data":1177,"type":544,"tunes":1179},"188cb4bb40",{"text":1178},"Agent tumači cilj, posmatra relevantne informacije, bira akciju, poziva alat i procenjuje rezultat.",{},{"id":1181,"data":1182,"type":544,"tunes":1184},"117d1032f1",{"text":1183},"G-Assist sada mnogo bliže odgovara tom drugom opisu jer može da koordinira više akcija, pregleda podržano stanje računara i poziva prave alate.",{},{"id":1186,"data":1187,"type":737,"tunes":1192},"ef132fc518",{"url":1188,"title":1189,"excerpt":1190,"ctaLabel":1191},"https:\u002F\u002Ffigure.rocks\u002Fsr\u002Fblog\u002Fpubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning","PUBG Ally pokazuje zašto AI saigračima trebaju dva mozga: brzi refleksi i sporo rezonovanje","Primer arhitekture game-agenta koji pokazuje razdvajanje između rezonovanja, stanja uživo, alata i determinističkog izvršavanja.","Pročitajte vodič za PUBG Ally arhitekturu",{},{"id":1194,"data":1195,"type":572,"tunes":1197},"9f8fa308a5",{"text":1196,"level":47},"Šta G-Assist još uvek nije",{},{"id":1199,"data":1200,"type":544,"tunes":1202},"f5f24e8aa3",{"text":1201},"NVIDIA eksplicitno opisuje G-Assist kao specijalizovanog lokalnog asistenta, a ne kao AI opšte namene za razgovor.",{},{"id":1204,"data":1205,"type":544,"tunes":1207},"e4d187593f",{"text":1206},"Njegova vrednost proizlazi iz razumevanja fokusiranog skupa PC i gejming zadataka i posedovanja alata povezanih sa tim zadacima.",{},{"id":1209,"data":1210,"type":544,"tunes":1212},"0c1b7f8948",{"text":1211},"Taj fokus je važan jer manji lokalni model može biti koristan kada mu okolni sistem pruža jake alate i jasne granice.",{},{"id":1214,"data":1215,"type":572,"tunes":1217},"79a5920e77",{"text":1216,"level":47},"Šta se promenilo u trenutnim verzijama?",{},{"id":1219,"data":1220,"type":544,"tunes":1222},"e78d96ef6c",{"text":1221},"Trenutna javna istorija izdanja pokazuje da G-Assist ravnomerno napreduje ka sposobnijem lokalnom agentu.",{},{"id":1224,"data":1225,"type":668,"tunes":1246},"87dd1d3d3c",{"content":1226,"stretched":1245,"withHeadings":15},[1227,1230,1233,1236,1239,1242],[1228,1229],"Verzija","Važna promena",[1231,1232],"0.1.17","Lakši model, sve RTX GPU sa 6 GB+ VRAM, dodaci zajednice",[1234,1235],"0.1.18","Optimizacija za laptop, kontrole BatteryBoost i WhisperMode",[1237,1238],"0.2","Režim rezonovanja, Flash režim, upiti sa više radnji, nove kontrole uređaja",[1240,1241],"0.2.1","Poboljšan sistem znanja, bolje preporuke, kontrole RTX funkcija",[1243,1244],"0.2.2","Elgato Stream Deck integracija putem MCP servera",false,{},{"id":1248,"data":1249,"type":572,"tunes":1251},"09bde21a8d",{"text":1250,"level":47},"Šta bi promenilo ovaj odgovor?",{},{"id":1253,"data":1254,"type":544,"tunes":1256},"b0e7ca01a4",{"text":1255},"G-Assist je još uvek eksperimentalan i njegova arhitektura se razvija.",{},{"id":1258,"data":1259,"type":544,"tunes":1261},"537568c224",{"text":1260},"Veličina modela, zahtevi za VRAM, skup alata, protokol dodataka i podrška za hardver mogu se promeniti u budućim izdanjima.",{},{"id":1263,"data":1264,"type":544,"tunes":1266},"fe24516c11",{"text":1265},"Buduća verzija bi takođe mogla prebaciti deo inferencije na NPU ili uvesti širu MCP integraciju, ali to ne treba pretpostavljati dok NVIDIA to ne dokumentuje.",{},{"id":1268,"data":1269,"type":572,"tunes":1271},"0e31e2d54d",{"text":1270,"level":47},"Ograničenja",{},{"id":1273,"data":1274,"type":544,"tunes":1276},"a7881e11e1",{"text":1275},"Ovaj članak opisuje NVIDIA-inu javnu dokumentaciju proizvoda G-Assist i javnu arhitekturu dodataka zaključno sa septembrom 2026.",{},{"id":1278,"data":1279,"type":544,"tunes":1281},"71ebc16fda",{"text":1280},"NVIDIA ne dokumentuje javno svaki interni detalj svog sistema znanja i preporuka, tako da ovaj članak ne tvrdi da svaki odgovor zasnovan na znanju koristi RAG ili bilo koju drugu specifičnu implementaciju pretraživanja.",{},{"id":1283,"data":1284,"type":544,"tunes":1286},"add780d6ba",{"text":1285},"Dodaci trećih strana mogu imati ponašanje i mrežni pristup izvan NVIDIA-inih ugrađenih funkcija, tako da svaki dodatak treba posebno proceniti.",{},{"id":1288,"data":1289,"type":572,"tunes":1291},"f7a38af5be",{"text":1290,"level":47},"Zaključak",{},{"id":1293,"data":1294,"type":544,"tunes":1296},"f1308f3e80",{"text":1295},"Najlakši način da razumete Project G-Assist je da prestanete da o njemu razmišljate kao o chatbotu.",{},{"id":1298,"data":1299,"type":544,"tunes":1301},"b102a861bb",{"text":1300},"Lokalni SLM tumači vaš zahtev. Znanje mu pomaže da razume problem. Informacije o sistemu uživo mu govore šta je istina na vašem računaru. Ugrađena funkcija ili dodatak definiše šta mu je zapravo dozvoljeno da radi. Alat izvršava radnju i vraća rezultat.",{},{"id":1303,"data":1304,"type":544,"tunes":1306},"da805fabf0",{"text":1305},"To je arhitektura lokalnog agenta.",{},{"id":1308,"data":1309,"type":544,"tunes":1311},"675aecee06",{"text":1310},"Njegova najjača ideja nije da model sa 8 milijardi parametara može da govori o vašem GPU. Već da relativno mali lokalni model može postati koristan kada je povezan sa dobro definisanim alatima, trenutnim stanjem i kontrolisanom granicom delovanja.",{},{"id":1313,"data":1314,"type":572,"tunes":1316},"0354b8daaf",{"text":1315,"level":47},"Često postavljana pitanja",{},{"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","Ne. Njegov osnovni jezički model radi lokalno na GeForce RTX GPU i može da radi offline za podržane lokalne funkcije.","Da li je G-Assist cloud chatbot?",{"id":1326,"answer":1327,"question":1328},"faq2","NVIDIA ga trenutno opisuje kao lokalni Llama-based instruct model sa 8 milijardi parametara.","Koji model koristi G-Assist?",{"id":1330,"answer":1331,"question":1332},"faq3","Ne. Model bira podržanu ugrađenu funkciju ili plug-in, a taj alat obavlja stvarnu promenu.","Da li AI model direktno menja moja GPU podešavanja?",{"id":1334,"answer":1335,"question":1336},"faq4","Da. NVIDIA preporučuje dodatni slobodan VRAM za asistenta i upozorava da inferencija može nakratko smanjiti performanse renderovanja igre.","Da li G-Assist koristi VRAM tokom igranja?",{"id":1338,"answer":1339,"question":1340},"faq5","Ne direktno. G-Assist sopstveni trenutni plug-in protokol koristi JSON-RPC 2.0, iako plug-in može da se poveže na MCP server.","Da li su G-Assist plug-inovi MCP plug-inovi?",{"id":1342,"answer":1343,"question":1344},"faq6","Njegov lokalni asistent može, ali pojedinačni plug-inovi mogu i dalje zahtevati pristup internetu ako pozivaju online servise.","Može li G-Assist da radi offline?",{"id":1346,"answer":1347,"question":1348},"faq7","NVIDIA ga opisuje kao specijalizovanog PC i gaming asistenta, a ne kao široki opšti konverzacioni model.","Da li je G-Assist opšti AI asistent?","NVIDIA Project G-Assist jednostavnim jezikom","faq",{},{"id":1353,"data":1354,"type":572,"tunes":1356},"8733f298cd",{"text":1355,"level":47},"Pojmovnik",{},{"id":1358,"data":1359,"type":1393,"tunes":1394},"407257a6d1",{"title":1360,"entries":1361},"Ključni G-Assist pojmovi",[1362,1366,1370,1374,1378,1382,1386,1390],{"term":1363,"anchor":1364,"definition":1365},"SLM","slm","Small Language Model, kompaktan jezički model dizajniran da radi lokalno sa nižim hardverskim zahtevima od velikih cloud modela.",{"term":1367,"anchor":1368,"definition":1369},"Pozivanje alata","tool-calling","Proces u kojem jezički model bira definisanu funkciju i dostavlja strukturisane argumente kako bi druga komponenta mogla da izvrši radnju.",{"term":1371,"anchor":1372,"definition":1373},"Plug-in","plugin","Ekstenzija koja izlaže dodatne funkcije ili integracije G-Assist-u.",{"term":1375,"anchor":1376,"definition":1377},"JSON-RPC 2.0","json-rpc","Strukturisani protokol poruka koji koristi trenutni G-Assist Protocol V2 plug-in sistem.",{"term":1379,"anchor":1380,"definition":1381},"MCP","mcp","Model Context Protocol, odvojeni protokol za interoperabilnost alata i konteksta koji neke eksterne integracije mogu da izlože.",{"term":1383,"anchor":1384,"definition":1385},"Granica između alata i ovlašćenja","tool-authority-boundary","Figure Rocks model koji razdvaja ono što AI model može da razume od onoga što njegovi povezani alati zapravo dozvoljavaju da uradi.",{"term":1387,"anchor":1388,"definition":1389},"Lokalni agent stack","local-agent-stack","Figure Rocks model koji kombinuje korisničku nameru, lokalni SLM, znanje, trenutno stanje, izbor alata, izvršavanje i verifikaciju rezultata.",{"term":1114,"anchor":1391,"definition":1392},"local-assistant-resource-test","Figure Rocks radni tok za procenu VRAM-a, troškova inferencije, dozvola alata i rizika plug-inova pre korišćenja lokalnog gaming asistenta.","glossary",{},{"id":1396,"data":1397,"type":572,"tunes":1399},"3ab856f2b4",{"text":1398,"level":47},"Primarni izvori",{},{"id":1401,"data":1402,"type":1408,"tunes":1409},"367d2e3548",{"link":1403,"meta":1404},"https:\u002F\u002Fwww.nvidia.com\u002Fen-us\u002Fsoftware\u002Fnvidia-app\u002Fg-assist\u002F",{"image":1405,"title":1406,"description":1407},{"url":13},"NVIDIA — Project G-Assist","Zvanična trenutna stranica proizvoda koja pokriva lokalni model, podržane funkcije, Reasoning i Flash režime, VRAM zahteve, RTX kontrole, plug-inove i verziju 0.2.2 MCP-bazirane Elgato integracije.","linkTool",{},{"id":1411,"data":1412,"type":1408,"tunes":1418},"5641b514c0",{"link":1413,"meta":1414},"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FG-Assist",{"image":1415,"title":1416,"description":1417},{"url":13},"NVIDIA — G-Assist GitHub","Zvanični javni repozitorijum plug-inova koji dokumentuje G-Assist arhitekturu modula, otkrivanje plug-inova i Protocol V2.",{},{"id":1420,"data":1421,"type":1408,"tunes":1427},"22a5b77a1b",{"link":1422,"meta":1423},"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FG-Assist\u002Fblob\u002Fmain\u002FPLUGIN_MIGRATION_GUIDE_V2.md",{"image":1424,"title":1425,"description":1426},{"url":13},"NVIDIA — G-Assist Protocol V2 vodič za migraciju","Zvanična dokumentacija protokola koja pokriva JSON-RPC 2.0, inicijalizaciju, provere zdravlja, izvršavanje, streaming, završetak i ponašanje plug-in SDK-a.",{},{"id":1429,"data":1430,"type":1408,"tunes":1436},"cc3301d997",{"link":1431,"meta":1432},"https:\u002F\u002Fblogs.nvidia.com\u002Fblog\u002Frtx-ai-garage-gamescom-g-assist-rtx-remix\u002F",{"image":1433,"title":1434,"description":1435},{"url":13},"NVIDIA Blog — Lagani G-Assist model","Zvanična pozadina o G-Assist modelu sa manje memorije, podršci za 6 GB RTX GPU-ove i čvorištu plug-inova zajednice.",{},"2.31","NVIDIA Project G-Assist izgleda kao chatbot, ali njegova prava arhitektura je bliža lokalnom AI agentu. Mali jezički model tumači vaš zahtev, stanje sistema pruža trenutne informacije o računaru, alati obavljaju stvarne radnje, a dodaci proširuju ono čime asistent sme da upravlja.","\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":1446,"de":1447,"sr":1448,"es":1449,"fr":1450,"it":1451,"ru":1452,"zh":1453},"\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",[1455,1459,1463,1467,1471],{"id":1456,"name":1457,"slug":1458},171,"ГПУ-ови и драјвери","gpus-and-drivers",{"id":1460,"name":1461,"slug":1462},67,"Windows и драјвери","windows-and-drivers",{"id":1464,"name":1465,"slug":1466},68,"Подешавања у игри","in-game-settings",{"id":1468,"name":1469,"slug":1470},69,"Подешавања екрана","display-settings",{"id":1472,"name":1473,"slug":1474},197,"Најбоља подешавања прво","best-settings-first",{"id":283,"login":1476,"email":1477,"displayName":1478},"aleksandar","aleksandar@stajic.de","Aleksandar Stajic",[1480,2189],{"lang":8,"title":1481,"content":1482,"contentJson":1483,"excerpt":2188},"NVIDIA G-Assist Is Not Just a Chatbot: How Its Local SLM, Tools, Plug-ins and MCP Actually Work","{\"time\":1790407740910,\"blocks\":[{\"id\":\"3cee674645\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA Project G-Assist looks like a chatbot, but that description misses the important part. It is a local AI system that can understand a request, inspect supported PC state, choose a tool or plug-in, and then perform a real action such as changing DLSS settings, checking a driver, adjusting a fan profile or controlling a peripheral.\"},\"tunes\":{}},{\"id\":\"24a1733ca8\",\"type\":\"callout\",\"data\":{\"variant\":\"info\",\"title\":\"Direct answer\",\"body\":\"\u003Cstrong>G-Assist is not simply a chatbot for your GPU.\u003C\u002Fstrong> It is a local small language model connected to a set of allowed tools. The model interprets what you want, selects a supported function, passes arguments to that function, and the PC-side tool performs the action.\"},\"tunes\":{}},{\"id\":\"1fcbe512dc\",\"type\":\"callout\",\"data\":{\"variant\":\"note\",\"title\":\"The easiest mental model\",\"body\":\"\u003Cstrong>SLM = understands the request.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Knowledge = explains supported NVIDIA\u002FPC concepts.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Tools = perform actions.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Plug-ins = add new tools.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Your PC = the environment being inspected or changed.\u003C\u002Fstrong>\"},\"tunes\":{}},{\"id\":\"2a609230a5\",\"type\":\"tableOfContents\",\"data\":{\"title\":\"Contents\",\"minLevel\":2,\"maxLevel\":3},\"tunes\":{}},{\"id\":\"a52f97cb62\",\"type\":\"header\",\"data\":{\"text\":\"First: what is the AI model actually doing?\",\"level\":2},\"tunes\":{}},{\"id\":\"1871a0d8e6\",\"type\":\"paragraph\",\"data\":{\"text\":\"G-Assist uses a local small language model, or SLM. NVIDIA currently describes the system as using a Llama-based 8-billion-parameter instruct model.\"},\"tunes\":{}},{\"id\":\"cfbc6473c4\",\"type\":\"paragraph\",\"data\":{\"text\":\"The model's main job is not to render graphics or directly change hardware registers. Its job is to understand the user's language, decide which supported capability matches the request, and prepare the call to that capability.\"},\"tunes\":{}},{\"id\":\"53cadaaeb6\",\"type\":\"paragraph\",\"data\":{\"text\":\"For example, if you say “set DLSS Super Resolution to Performance Mode,” the language model does not itself modify DLSS. It interprets the command and routes it to the supported function that can change the setting.\"},\"tunes\":{}},{\"id\":\"5d8e508019\",\"type\":\"callout\",\"data\":{\"variant\":\"success\",\"title\":\"The important distinction\",\"body\":\"The AI model \u003Cstrong>decides what tool to call\u003C\u002Fstrong>. The tool \u003Cstrong>does the real work\u003C\u002Fstrong>.\"},\"tunes\":{}},{\"id\":\"9ce7e91c28\",\"type\":\"header\",\"data\":{\"text\":\"The G-Assist action pipeline\",\"level\":2},\"tunes\":{}},{\"id\":\"992b5d6667\",\"type\":\"processFlow\",\"data\":{\"title\":\"What happens after you give G-Assist a command\",\"orientation\":\"auto\",\"steps\":[{\"label\":\"1. You give a natural-language request\",\"description\":\"For example: “Optimize this game for performance.”\"},{\"label\":\"2. The local SLM interprets the request\",\"description\":\"It determines the user's intent and identifies which supported function or plug-in is relevant.\"},{\"label\":\"3. The system chooses a tool\",\"description\":\"That could be a built-in graphics-setting function, driver check, monitoring function or community plug-in.\"},{\"label\":\"4. Arguments are extracted\",\"description\":\"The model converts the request into structured values such as game name, mode, fan profile or DLSS setting.\"},{\"label\":\"5. The tool executes\",\"description\":\"The tool talks to the NVIDIA App, operating system, peripheral software or another service.\"},{\"label\":\"6. The result is returned\",\"description\":\"G-Assist reports what happened, or returns data that the model can explain.\"}]},\"tunes\":{}},{\"id\":\"aba1e38958\",\"type\":\"header\",\"data\":{\"text\":\"This is tool calling, not magic PC control\",\"level\":2},\"tunes\":{}},{\"id\":\"0a7cb6107d\",\"type\":\"paragraph\",\"data\":{\"text\":\"A language model cannot safely control an arbitrary computer simply because it understands English.\"},\"tunes\":{}},{\"id\":\"31191a478c\",\"type\":\"paragraph\",\"data\":{\"text\":\"It needs a defined interface that says which actions exist, which arguments they accept and what the tool returns.\"},\"tunes\":{}},{\"id\":\"af3d1a846f\",\"type\":\"paragraph\",\"data\":{\"text\":\"G-Assist's current built-in capabilities include functions such as optimizing graphics settings, changing supported RTX options, checking or downloading drivers, showing performance information, changing some laptop power features, controlling supported monitor functions and using supported peripheral plug-ins.\"},\"tunes\":{}},{\"id\":\"d6fd0eb144\",\"type\":\"comparison\",\"data\":{\"title\":\"Language model vs tool\",\"layout\":\"table\",\"columns\":[{\"id\":\"model\",\"label\":\"Language model\"},{\"id\":\"tool\",\"label\":\"Tool \u002F plug-in\"}],\"rows\":[{\"id\":\"understand\",\"label\":\"Understand “turn on DLSS”\",\"values\":[\"\",\"\"]},{\"id\":\"decide\",\"label\":\"Choose the correct function\",\"values\":[\"\",\"\"]},{\"id\":\"change\",\"label\":\"Actually change the setting\",\"values\":[\"\",\"\"]},{\"id\":\"explain\",\"label\":\"Explain the result\",\"values\":[\"\",\"\"]}]},\"tunes\":{}},{\"id\":\"1537be641c\",\"type\":\"header\",\"data\":{\"text\":\"What is the knowledge layer?\",\"level\":2},\"tunes\":{}},{\"id\":\"1db6e2e4b5\",\"type\":\"paragraph\",\"data\":{\"text\":\"G-Assist also has a knowledge layer for answering questions and making recommendations.\"},\"tunes\":{}},{\"id\":\"616d72b881\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA says version 0.2.1 introduced an improved knowledge system that helps G-Assist make more accurate settings recommendations.\"},\"tunes\":{}},{\"id\":\"eb987c41e5\",\"type\":\"paragraph\",\"data\":{\"text\":\"That knowledge layer is different from the live state of your PC.\"},\"tunes\":{}},{\"id\":\"bf6a4f5502\",\"type\":\"comparison\",\"data\":{\"title\":\"Knowledge vs live PC state\",\"layout\":\"table\",\"columns\":[{\"id\":\"knowledge\",\"label\":\"Knowledge\"},{\"id\":\"state\",\"label\":\"Live state\"}],\"rows\":[{\"id\":\"gpu\",\"label\":\"GPU\",\"values\":[\"\",\"\"]},{\"id\":\"game\",\"label\":\"Game settings\",\"values\":[\"\",\"\"]},{\"id\":\"system\",\"label\":\"Performance\",\"values\":[\"\",\"\"]}]},\"tunes\":{}},{\"id\":\"2bac13ef99\",\"type\":\"callout\",\"data\":{\"variant\":\"warning\",\"title\":\"Do not mix knowledge with state\",\"body\":\"\u003Cstrong>Knowledge\u003C\u002Fstrong> tells the assistant what a feature means or what usually matters.\u003Cbr>\u003Cstrong>State\u003C\u002Fstrong> tells it what is true on your machine right now.\"},\"tunes\":{}},{\"id\":\"73708d5e0d\",\"type\":\"referralArticle\",\"data\":{\"url\":\"https:\u002F\u002Fstajic.de\u002Fblog\u002Fwhat-is-rag-the-simplest-explanation-of-how-it-works\",\"title\":\"What Is RAG? The Simplest Explanation of How It Works\",\"excerpt\":\"A plain-English explanation of knowledge retrieval, state, memory, context and the language model.\",\"ctaLabel\":\"Read the simple RAG guide\"},\"tunes\":{}},{\"id\":\"acbb9b7940\",\"type\":\"header\",\"data\":{\"text\":\"Does G-Assist use RAG?\",\"level\":2},\"tunes\":{}},{\"id\":\"ce0371e492\",\"type\":\"paragraph\",\"data\":{\"text\":\"The safest answer is: G-Assist clearly has a knowledge system, but NVIDIA's public product page does not document every internal retrieval mechanism in enough detail to say that every knowledge answer is specifically produced by RAG.\"},\"tunes\":{}},{\"id\":\"c2226e5ec5\",\"type\":\"paragraph\",\"data\":{\"text\":\"The architectural distinction still matters. A retrieval layer can provide relevant knowledge, while system tools provide current PC state and perform actions.\"},\"tunes\":{}},{\"id\":\"e5137fc2c8\",\"type\":\"paragraph\",\"data\":{\"text\":\"That is the same separation used in many modern agents: knowledge is one source of context, live observations are another, and tool execution is a third.\"},\"tunes\":{}},{\"id\":\"059b89dedb\",\"type\":\"header\",\"data\":{\"text\":\"Why G-Assist can work offline\",\"level\":2},\"tunes\":{}},{\"id\":\"19447df6a4\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA runs the language model locally on the GeForce RTX GPU.\"},\"tunes\":{}},{\"id\":\"55aee6ada7\",\"type\":\"paragraph\",\"data\":{\"text\":\"That means the core assistant does not require a cloud-hosted language model for every prompt.\"},\"tunes\":{}},{\"id\":\"f265d1fd96\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA explicitly says G-Assist can run offline for its local capabilities.\"},\"tunes\":{}},{\"id\":\"1dc8613200\",\"type\":\"paragraph\",\"data\":{\"text\":\"A plug-in can still use the internet if that plug-in calls an online service. Local model execution and online plug-in access are separate questions.\"},\"tunes\":{}},{\"id\":\"ee01c97a66\",\"type\":\"header\",\"data\":{\"text\":\"The local-AI cost: G-Assist uses your GPU and VRAM\",\"level\":2},\"tunes\":{}},{\"id\":\"1784ad3fcf\",\"type\":\"paragraph\",\"data\":{\"text\":\"Running locally gives privacy and independence from a cloud model, but the work has to execute somewhere.\"},\"tunes\":{}},{\"id\":\"1275ab759f\",\"type\":\"paragraph\",\"data\":{\"text\":\"For G-Assist, that somewhere is the same GeForce RTX GPU that may already be rendering your game.\"},\"tunes\":{}},{\"id\":\"cec86f847a\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA warns that the GPU briefly allocates compute resources to AI inference when G-Assist responds. If a demanding game is running at the same time, the game can temporarily lose some rendering performance while the model is active.\"},\"tunes\":{}},{\"id\":\"e6ea700df6\",\"type\":\"paragraph\",\"data\":{\"text\":\"The current requirements also specify free-VRAM targets beyond the memory already used by the game: approximately 6 GB of free VRAM for Reasoning Mode and 4.5 GB for Flash Mode.\"},\"tunes\":{}},{\"id\":\"2126f74de5\",\"type\":\"callout\",\"data\":{\"variant\":\"warning\",\"title\":\"8 GB VRAM does not mean 8 GB is available to G-Assist\",\"body\":\"The game, Windows, the driver and other applications already consume VRAM. G-Assist's own requirement is about \u003Cstrong>free VRAM in addition to what the running workload already uses\u003C\u002Fstrong>.\"},\"tunes\":{}},{\"id\":\"13c0dcb3f3\",\"type\":\"referralArticle\",\"data\":{\"url\":\"https:\u002F\u002Ffigure.rocks\u002Fblog\u002Fvram-usage-is-not-vram-requirement-why-a-full-memory-meter-does-not-tell-the-whole-story\",\"title\":\"VRAM Usage Is Not VRAM Requirement: Why a Full Memory Meter Does Not Tell the Whole Story\",\"excerpt\":\"Why installed VRAM, current usage, residency budgets and real memory pressure are different things.\",\"ctaLabel\":\"Read the VRAM guide\"},\"tunes\":{}},{\"id\":\"d684b2c1c8\",\"type\":\"header\",\"data\":{\"text\":\"Reasoning Mode vs Flash Mode\",\"level\":2},\"tunes\":{}},{\"id\":\"3c1f2379db\",\"type\":\"paragraph\",\"data\":{\"text\":\"Current G-Assist versions separate a more capable Reasoning Mode from a faster Flash Mode.\"},\"tunes\":{}},{\"id\":\"86f50ebd33\",\"type\":\"paragraph\",\"data\":{\"text\":\"Reasoning Mode is designed for higher-quality decisions and can coordinate multiple actions from one prompt. Flash Mode is optimized for faster responses and lower resource demand.\"},\"tunes\":{}},{\"id\":\"e7be4789db\",\"type\":\"comparison\",\"data\":{\"title\":\"Reasoning Mode vs Flash Mode\",\"layout\":\"table\",\"columns\":[{\"id\":\"reasoning\",\"label\":\"Reasoning Mode\"},{\"id\":\"flash\",\"label\":\"Flash Mode\"}],\"rows\":[{\"id\":\"goal\",\"label\":\"Primary goal\",\"values\":[\"\",\"\"]},{\"id\":\"vram\",\"label\":\"Recommended free VRAM\",\"values\":[\"\",\"\"]},{\"id\":\"use\",\"label\":\"Best fit\",\"values\":[\"\",\"\"]}]},\"tunes\":{}},{\"id\":\"cef1bcf553\",\"type\":\"header\",\"data\":{\"text\":\"What plug-ins actually add\",\"level\":2},\"tunes\":{}},{\"id\":\"d380d5e28b\",\"type\":\"paragraph\",\"data\":{\"text\":\"A plug-in does not replace the language model. It gives the model a new action it is allowed to call.\"},\"tunes\":{}},{\"id\":\"434979ebda\",\"type\":\"paragraph\",\"data\":{\"text\":\"The plug-in defines functions, descriptions and parameters. G-Assist reads those descriptions, matches a user request to the appropriate function and sends structured arguments to it.\"},\"tunes\":{}},{\"id\":\"21ebe69c79\",\"type\":\"paragraph\",\"data\":{\"text\":\"That lets the assistant grow beyond NVIDIA's built-in functions.\"},\"tunes\":{}},{\"id\":\"d0ba7ef284\",\"type\":\"processFlow\",\"data\":{\"title\":\"How a G-Assist plug-in works\",\"orientation\":\"auto\",\"steps\":[{\"label\":\"1. Plug-in declares a function\",\"description\":\"For example: set_keyboard_color(color).\"},{\"label\":\"2. Manifest describes the function\",\"description\":\"The manifest tells G-Assist what the function does and what parameters it needs.\"},{\"label\":\"3. User asks naturally\",\"description\":\"For example: “Make my keyboard green.”\"},{\"label\":\"4. SLM selects the function\",\"description\":\"The model maps the request to the plug-in function and extracts green as the parameter.\"},{\"label\":\"5. Plug-in executes\",\"description\":\"The plug-in talks to the peripheral software or external service.\"}]},\"tunes\":{}},{\"id\":\"1dc857ce2f\",\"type\":\"header\",\"data\":{\"text\":\"G-Assist Protocol V2 is JSON-RPC 2.0\",\"level\":2},\"tunes\":{}},{\"id\":\"02bdb0566d\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA's current public plug-in repository uses Protocol V2.\"},\"tunes\":{}},{\"id\":\"f82da294cf\",\"type\":\"paragraph\",\"data\":{\"text\":\"Protocol V2 uses JSON-RPC 2.0 with length-prefixed messages between the G-Assist engine and plug-ins.\"},\"tunes\":{}},{\"id\":\"530c3cf9b9\",\"type\":\"paragraph\",\"data\":{\"text\":\"The engine can initialize a plug-in, check its health, execute a function, send user input and shut it down. Plug-ins can return results, stream progress or report errors.\"},\"tunes\":{}},{\"id\":\"2ce3fa5d75\",\"type\":\"comparison\",\"data\":{\"title\":\"The important Protocol V2 messages\",\"layout\":\"table\",\"columns\":[{\"id\":\"direction\",\"label\":\"Direction\"},{\"id\":\"purpose\",\"label\":\"Purpose\"}],\"rows\":[{\"id\":\"initialize\",\"label\":\"initialize\",\"values\":[\"\",\"\"]},{\"id\":\"ping\",\"label\":\"ping\",\"values\":[\"\",\"\"]},{\"id\":\"execute\",\"label\":\"execute\",\"values\":[\"\",\"\"]},{\"id\":\"stream\",\"label\":\"stream\",\"values\":[\"\",\"\"]},{\"id\":\"complete\",\"label\":\"complete\",\"values\":[\"\",\"\"]}]},\"tunes\":{}},{\"id\":\"304fbd9944\",\"type\":\"header\",\"data\":{\"text\":\"Where MCP enters the picture\",\"level\":2},\"tunes\":{}},{\"id\":\"fae73881e4\",\"type\":\"paragraph\",\"data\":{\"text\":\"G-Assist's own plug-in protocol is not MCP. Its current public plug-in system uses JSON-RPC 2.0.\"},\"tunes\":{}},{\"id\":\"551d11710a\",\"type\":\"paragraph\",\"data\":{\"text\":\"However, a G-Assist plug-in can connect to an MCP server.\"},\"tunes\":{}},{\"id\":\"0537fb222a\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA's current version 0.2.2 includes an Elgato integration that can invoke actions exposed through the Elgato Stream Deck MCP server.\"},\"tunes\":{}},{\"id\":\"760a86ad19\",\"type\":\"callout\",\"data\":{\"variant\":\"success\",\"title\":\"Important protocol distinction\",\"body\":\"\u003Cstrong>G-Assist ↔ its plug-in:\u003C\u002Fstrong> NVIDIA Protocol V2 \u002F JSON-RPC 2.0.\u003Cbr>\u003Cstrong>Plug-in ↔ another tool ecosystem:\u003C\u002Fstrong> can use MCP when that integration supports it.\"},\"tunes\":{}},{\"id\":\"bd182f72b0\",\"type\":\"header\",\"data\":{\"text\":\"Why this matters beyond RGB lights\",\"level\":2},\"tunes\":{}},{\"id\":\"d072506ce2\",\"type\":\"paragraph\",\"data\":{\"text\":\"The plug-in architecture turns G-Assist from a fixed assistant into a local tool router.\"},\"tunes\":{}},{\"id\":\"2876e067dc\",\"type\":\"paragraph\",\"data\":{\"text\":\"The same pattern can connect an SLM to monitoring tools, peripherals, APIs, automation systems, local applications or external services.\"},\"tunes\":{}},{\"id\":\"37689640e9\",\"type\":\"paragraph\",\"data\":{\"text\":\"The important architectural unit is therefore not the chat window. It is the boundary between natural-language intent and structured tool execution.\"},\"tunes\":{}},{\"id\":\"550fbb42d4\",\"type\":\"header\",\"data\":{\"text\":\"The Local Agent Stack\",\"level\":2},\"tunes\":{}},{\"id\":\"8518dbf820\",\"type\":\"processFlow\",\"data\":{\"title\":\"A useful way to think about G-Assist\",\"orientation\":\"auto\",\"steps\":[{\"label\":\"1. User intent\",\"description\":\"Natural language or voice command.\"},{\"label\":\"2. Local SLM\",\"description\":\"Understands the request and chooses a capability.\"},{\"label\":\"3. Knowledge \u002F context\",\"description\":\"Provides product knowledge, recommendations or information needed for the decision.\"},{\"label\":\"4. Live system state\",\"description\":\"Provides current hardware, driver, performance or configuration information when supported.\"},{\"label\":\"5. Tool selection\",\"description\":\"Built-in function or plug-in is chosen.\"},{\"label\":\"6. Structured execution\",\"description\":\"The function receives arguments and performs the real action.\"},{\"label\":\"7. Result verification\",\"description\":\"The tool returns status or data and the model explains what happened.\"}]},\"tunes\":{}},{\"id\":\"6c976db763\",\"type\":\"header\",\"data\":{\"text\":\"Why tool boundaries are a safety feature\",\"level\":2},\"tunes\":{}},{\"id\":\"ba65a3b467\",\"type\":\"paragraph\",\"data\":{\"text\":\"An AI assistant that could execute arbitrary operating-system commands would be far more powerful, but also much harder to constrain.\"},\"tunes\":{}},{\"id\":\"a932df9663\",\"type\":\"paragraph\",\"data\":{\"text\":\"G-Assist instead exposes defined functions with known parameters.\"},\"tunes\":{}},{\"id\":\"7d1d45c83d\",\"type\":\"paragraph\",\"data\":{\"text\":\"That means the model can only perform actions that the built-in function set or installed plug-ins make available.\"},\"tunes\":{}},{\"id\":\"10460fda21\",\"type\":\"paragraph\",\"data\":{\"text\":\"This does not remove all risk, especially with third-party plug-ins, but it creates a clearer permission and capability boundary than unrestricted shell access.\"},\"tunes\":{}},{\"id\":\"25049448ea\",\"type\":\"header\",\"data\":{\"text\":\"The Tool-Authority Boundary\",\"level\":2},\"tunes\":{}},{\"id\":\"d3ff568795\",\"type\":\"comparison\",\"data\":{\"title\":\"What the assistant can understand vs what it is allowed to do\",\"layout\":\"table\",\"columns\":[{\"id\":\"understand\",\"label\":\"Model may understand\"},{\"id\":\"authority\",\"label\":\"Tool authority\"}],\"rows\":[{\"id\":\"gpu\",\"label\":\"GPU tuning\",\"values\":[\"\",\"\"]},{\"id\":\"files\",\"label\":\"Files\",\"values\":[\"\",\"\"]},{\"id\":\"web\",\"label\":\"Internet\",\"values\":[\"\",\"\"]},{\"id\":\"device\",\"label\":\"Peripheral control\",\"values\":[\"\",\"\"]}]},\"tunes\":{}},{\"id\":\"8fd8e35c51\",\"type\":\"header\",\"data\":{\"text\":\"Why G-Assist can temporarily reduce game performance\",\"level\":2},\"tunes\":{}},{\"id\":\"f75234546f\",\"type\":\"paragraph\",\"data\":{\"text\":\"The local-model architecture has a straightforward consequence: the AI and the game can compete for the same GPU.\"},\"tunes\":{}},{\"id\":\"28bc054afa\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA explicitly warns that render rate or inference speed can briefly dip while G-Assist is processing a request during a GPU-heavy workload.\"},\"tunes\":{}},{\"id\":\"0823573513\",\"type\":\"paragraph\",\"data\":{\"text\":\"Once inference finishes, those GPU resources return to the game.\"},\"tunes\":{}},{\"id\":\"905eed843d\",\"type\":\"paragraph\",\"data\":{\"text\":\"This is different from a cloud assistant, where most model inference happens on a remote server and does not consume the gaming GPU.\"},\"tunes\":{}},{\"id\":\"839c0e3988\",\"type\":\"header\",\"data\":{\"text\":\"The Local Assistant Resource Test\",\"level\":2},\"tunes\":{}},{\"id\":\"affa0ee1b3\",\"type\":\"processFlow\",\"data\":{\"title\":\"How to judge whether a local gaming assistant fits your PC\",\"orientation\":\"auto\",\"steps\":[{\"label\":\"1. Check installed VRAM\",\"description\":\"The current G-Assist baseline is an RTX GPU with at least 6 GB VRAM.\"},{\"label\":\"2. Check free VRAM during the actual game\",\"description\":\"Installed capacity is not the same as free capacity.\"},{\"label\":\"3. Choose Reasoning or Flash Mode appropriately\",\"description\":\"Use the lighter mode when resource pressure matters more than deep reasoning.\"},{\"label\":\"4. Measure inference-time frame-rate dips\",\"description\":\"Watch the game while asking G-Assist to perform tasks.\"},{\"label\":\"5. Inspect tool authority\",\"description\":\"Know exactly which built-in functions and plug-ins can change your system.\"},{\"label\":\"6. Treat third-party plug-ins as software\",\"description\":\"Review their source, permissions, network access and stored credentials.\"}]},\"tunes\":{}},{\"id\":\"ca52c48d2e\",\"type\":\"header\",\"data\":{\"text\":\"Why plug-ins deserve the same scrutiny as any other software\",\"level\":2},\"tunes\":{}},{\"id\":\"8e6a760529\",\"type\":\"paragraph\",\"data\":{\"text\":\"A plug-in can connect the assistant to APIs, peripheral applications and online services.\"},\"tunes\":{}},{\"id\":\"be793240e1\",\"type\":\"paragraph\",\"data\":{\"text\":\"That means a plug-in may handle configuration values, credentials or external requests depending on what it was built to do.\"},\"tunes\":{}},{\"id\":\"3c6c4c9aaf\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA's repository explicitly provides a config.json location for plug-in settings and warns developers not to commit credentials.\"},\"tunes\":{}},{\"id\":\"03413f935a\",\"type\":\"paragraph\",\"data\":{\"text\":\"The correct security question is therefore not only “Is G-Assist local?” but also “What does each installed plug-in connect to?”\"},\"tunes\":{}},{\"id\":\"f473162e86\",\"type\":\"header\",\"data\":{\"text\":\"G-Assist is closer to an agent than a chatbot\",\"level\":2},\"tunes\":{}},{\"id\":\"59dd3df9c2\",\"type\":\"paragraph\",\"data\":{\"text\":\"A chatbot mainly produces language.\"},\"tunes\":{}},{\"id\":\"188cb4bb40\",\"type\":\"paragraph\",\"data\":{\"text\":\"An agent interprets a goal, observes relevant information, chooses an action, calls a tool and evaluates the result.\"},\"tunes\":{}},{\"id\":\"117d1032f1\",\"type\":\"paragraph\",\"data\":{\"text\":\"G-Assist now fits that second description much more closely because it can coordinate multiple actions, inspect supported PC state and invoke real tools.\"},\"tunes\":{}},{\"id\":\"ef132fc518\",\"type\":\"referralArticle\",\"data\":{\"url\":\"https:\u002F\u002Ffigure.rocks\u002Fblog\u002Fpubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning\",\"title\":\"PUBG Ally Shows Why AI Teammates Need Two Brains: Fast Reflexes and Slow Reasoning\",\"excerpt\":\"A game-agent architecture example showing the separation between reasoning, live state, tools and deterministic execution.\",\"ctaLabel\":\"Read the PUBG Ally architecture guide\"},\"tunes\":{}},{\"id\":\"9f8fa308a5\",\"type\":\"header\",\"data\":{\"text\":\"What G-Assist still is not\",\"level\":2},\"tunes\":{}},{\"id\":\"f5f24e8aa3\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA explicitly describes G-Assist as a specialized local assistant, not a general-purpose conversational AI.\"},\"tunes\":{}},{\"id\":\"e4d187593f\",\"type\":\"paragraph\",\"data\":{\"text\":\"Its value comes from understanding a focused set of PC and gaming tasks and having tools connected to those tasks.\"},\"tunes\":{}},{\"id\":\"0c1b7f8948\",\"type\":\"paragraph\",\"data\":{\"text\":\"That focus is important because a smaller local model can be useful when the surrounding system gives it strong tools and clear boundaries.\"},\"tunes\":{}},{\"id\":\"79a5920e77\",\"type\":\"header\",\"data\":{\"text\":\"What changed in the current versions?\",\"level\":2},\"tunes\":{}},{\"id\":\"e78d96ef6c\",\"type\":\"paragraph\",\"data\":{\"text\":\"The current public release history shows G-Assist moving steadily toward a more capable local agent.\"},\"tunes\":{}},{\"id\":\"87dd1d3d3c\",\"type\":\"table\",\"data\":{\"withHeadings\":true,\"stretched\":false,\"content\":[[\"Version\",\"Important change\"],[\"0.1.17\",\"Lighter model, all RTX GPUs with 6 GB+ VRAM, community plug-ins\"],[\"0.1.18\",\"Laptop optimization, BatteryBoost and WhisperMode controls\"],[\"0.2\",\"Reasoning Mode, Flash Mode, multi-action prompts, new device controls\"],[\"0.2.1\",\"Improved knowledge system, better recommendations, RTX feature controls\"],[\"0.2.2\",\"Elgato Stream Deck integration through an MCP server\"]]},\"tunes\":{}},{\"id\":\"09bde21a8d\",\"type\":\"header\",\"data\":{\"text\":\"What would change this answer?\",\"level\":2},\"tunes\":{}},{\"id\":\"b0e7ca01a4\",\"type\":\"paragraph\",\"data\":{\"text\":\"G-Assist is still experimental and its architecture is evolving.\"},\"tunes\":{}},{\"id\":\"537568c224\",\"type\":\"paragraph\",\"data\":{\"text\":\"The model size, VRAM requirements, tool set, plug-in protocol and hardware support can all change in future releases.\"},\"tunes\":{}},{\"id\":\"fe24516c11\",\"type\":\"paragraph\",\"data\":{\"text\":\"A future version could also move some inference to an NPU or introduce broader MCP integration, but that should not be assumed until NVIDIA documents it.\"},\"tunes\":{}},{\"id\":\"0e31e2d54d\",\"type\":\"header\",\"data\":{\"text\":\"Limitations\",\"level\":2},\"tunes\":{}},{\"id\":\"a7881e11e1\",\"type\":\"paragraph\",\"data\":{\"text\":\"This article describes NVIDIA's public G-Assist product documentation and public plug-in architecture as of September 2026.\"},\"tunes\":{}},{\"id\":\"71ebc16fda\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA does not publicly document every internal detail of its knowledge and recommendation pipeline, so this article does not claim that every knowledge answer uses RAG or any other specific retrieval implementation.\"},\"tunes\":{}},{\"id\":\"add780d6ba\",\"type\":\"paragraph\",\"data\":{\"text\":\"Third-party plug-ins can have behavior and network access beyond NVIDIA's built-in functions, so each plug-in should be evaluated separately.\"},\"tunes\":{}},{\"id\":\"f7a38af5be\",\"type\":\"header\",\"data\":{\"text\":\"Conclusion\",\"level\":2},\"tunes\":{}},{\"id\":\"f1308f3e80\",\"type\":\"paragraph\",\"data\":{\"text\":\"The easiest way to understand Project G-Assist is to stop thinking of it as a chatbot.\"},\"tunes\":{}},{\"id\":\"b102a861bb\",\"type\":\"paragraph\",\"data\":{\"text\":\"The local SLM interprets your request. Knowledge helps it understand the problem. Live system information tells it what is true on your PC. A built-in function or plug-in defines what it is actually allowed to do. The tool performs the action and returns the result.\"},\"tunes\":{}},{\"id\":\"da805fabf0\",\"type\":\"paragraph\",\"data\":{\"text\":\"That is a local agent architecture.\"},\"tunes\":{}},{\"id\":\"675aecee06\",\"type\":\"paragraph\",\"data\":{\"text\":\"Its strongest idea is not that an 8-billion-parameter model can talk about your GPU. It is that a relatively small local model can become useful when it is connected to well-defined tools, current state and a controlled action boundary.\"},\"tunes\":{}},{\"id\":\"0354b8daaf\",\"type\":\"header\",\"data\":{\"text\":\"FAQ\",\"level\":2},\"tunes\":{}},{\"id\":\"e75bc04532\",\"type\":\"faq\",\"data\":{\"title\":\"NVIDIA Project G-Assist in plain English\",\"items\":[{\"id\":\"faq1\",\"question\":\"Is G-Assist a cloud chatbot?\",\"answer\":\"No. Its core language model runs locally on the GeForce RTX GPU and can work offline for supported local functions.\"},{\"id\":\"faq2\",\"question\":\"What model does G-Assist use?\",\"answer\":\"NVIDIA currently describes it as a local Llama-based instruct model with 8 billion parameters.\"},{\"id\":\"faq3\",\"question\":\"Does the AI model directly change my GPU settings?\",\"answer\":\"No. The model selects a supported built-in function or plug-in, and that tool performs the actual change.\"},{\"id\":\"faq4\",\"question\":\"Does G-Assist use VRAM while gaming?\",\"answer\":\"Yes. NVIDIA recommends additional free VRAM for the assistant and warns that inference can briefly reduce game render performance.\"},{\"id\":\"faq5\",\"question\":\"Are G-Assist plug-ins MCP plug-ins?\",\"answer\":\"Not directly. G-Assist's own current plug-in protocol uses JSON-RPC 2.0, although a plug-in can connect to an MCP server.\"},{\"id\":\"faq6\",\"question\":\"Can G-Assist work offline?\",\"answer\":\"Its local assistant can, but individual plug-ins may still require internet access if they call online services.\"},{\"id\":\"faq7\",\"question\":\"Is G-Assist a general AI assistant?\",\"answer\":\"NVIDIA describes it as a specialized PC and gaming assistant rather than a broad general-purpose conversational model.\"}]},\"tunes\":{}},{\"id\":\"8733f298cd\",\"type\":\"header\",\"data\":{\"text\":\"Glossary\",\"level\":2},\"tunes\":{}},{\"id\":\"407257a6d1\",\"type\":\"glossary\",\"data\":{\"title\":\"Key G-Assist terms\",\"entries\":[{\"term\":\"SLM\",\"definition\":\"Small Language Model, a compact language model designed to run locally with lower hardware requirements than large cloud models.\",\"anchor\":\"slm\"},{\"term\":\"Tool calling\",\"definition\":\"The process where a language model chooses a defined function and supplies structured arguments so another component can perform an action.\",\"anchor\":\"tool-calling\"},{\"term\":\"Plug-in\",\"definition\":\"An extension that exposes additional functions or integrations to G-Assist.\",\"anchor\":\"plugin\"},{\"term\":\"JSON-RPC 2.0\",\"definition\":\"The structured message protocol used by the current G-Assist Protocol V2 plug-in system.\",\"anchor\":\"json-rpc\"},{\"term\":\"MCP\",\"definition\":\"Model Context Protocol, a separate tool and context interoperability protocol that some external integrations can expose.\",\"anchor\":\"mcp\"},{\"term\":\"Tool-Authority Boundary\",\"definition\":\"A Figure Rocks model separating what an AI model can understand from what its connected tools actually allow it to do.\",\"anchor\":\"tool-authority-boundary\"},{\"term\":\"Local Agent Stack\",\"definition\":\"A Figure Rocks model combining user intent, local SLM, knowledge, live state, tool selection, execution and result verification.\",\"anchor\":\"local-agent-stack\"},{\"term\":\"Local Assistant Resource Test\",\"definition\":\"A Figure Rocks workflow for evaluating VRAM, inference cost, tool permissions and plug-in risk before using a local gaming assistant.\",\"anchor\":\"local-assistant-resource-test\"}]},\"tunes\":{}},{\"id\":\"3ab856f2b4\",\"type\":\"header\",\"data\":{\"text\":\"Primary sources\",\"level\":2},\"tunes\":{}},{\"id\":\"367d2e3548\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fwww.nvidia.com\u002Fen-us\u002Fsoftware\u002Fnvidia-app\u002Fg-assist\u002F\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"NVIDIA — Project G-Assist\",\"description\":\"Official current product page covering the local model, supported functions, Reasoning and Flash modes, VRAM requirements, RTX controls, plug-ins and version 0.2.2 MCP-based Elgato integration.\"}},\"tunes\":{}},{\"id\":\"5641b514c0\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FG-Assist\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"NVIDIA — G-Assist GitHub\",\"description\":\"Official public plug-in repository documenting G-Assist's module architecture, plug-in discovery and Protocol V2.\"}},\"tunes\":{}},{\"id\":\"22a5b77a1b\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FG-Assist\u002Fblob\u002Fmain\u002FPLUGIN_MIGRATION_GUIDE_V2.md\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"NVIDIA — G-Assist Protocol V2 Migration Guide\",\"description\":\"Official protocol documentation covering JSON-RPC 2.0, initialization, health checks, execution, streaming, completion and plug-in SDK behavior.\"}},\"tunes\":{}},{\"id\":\"cc3301d997\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fblogs.nvidia.com\u002Fblog\u002Frtx-ai-garage-gamescom-g-assist-rtx-remix\u002F\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"NVIDIA Blog — Lightweight G-Assist Model\",\"description\":\"Official background on the lower-memory G-Assist model, support for 6 GB RTX GPUs and the community plug-in hub.\"}},\"tunes\":{}}],\"version\":\"2.31.6\"}",{"time":1484,"blocks":1485,"version":2187},1790407740910,[1486,1490,1495,1500,1504,1508,1512,1516,1520,1525,1529,1552,1556,1560,1564,1568,1590,1594,1598,1602,1606,1624,1629,1635,1639,1643,1647,1651,1655,1659,1663,1667,1671,1675,1679,1683,1687,1691,1696,1703,1707,1711,1715,1731,1735,1739,1743,1747,1767,1771,1775,1779,1783,1803,1807,1811,1815,1819,1824,1828,1832,1836,1840,1844,1870,1874,1878,1882,1886,1890,1894,1915,1919,1923,1927,1931,1935,1939,1962,1966,1970,1974,1978,1982,1986,1990,1994,1998,2005,2009,2013,2017,2021,2025,2029,2046,2050,2054,2058,2062,2066,2070,2074,2078,2082,2086,2090,2094,2098,2102,2128,2132,2157,2161,2167,2173,2180],{"id":541,"data":1487,"type":544,"tunes":1489},{"text":1488},"NVIDIA Project G-Assist looks like a chatbot, but that description misses the important part. It is a local AI system that can understand a request, inspect supported PC state, choose a tool or plug-in, and then perform a real action such as changing DLSS settings, checking a driver, adjusting a fan profile or controlling a peripheral.",{},{"id":547,"data":1491,"type":552,"tunes":1494},{"body":1492,"title":1493,"variant":551},"\u003Cstrong>G-Assist is not simply a chatbot for your GPU.\u003C\u002Fstrong> It is a local small language model connected to a set of allowed tools. The model interprets what you want, selects a supported function, passes arguments to that function, and the PC-side tool performs the action.","Direct answer",{},{"id":555,"data":1496,"type":552,"tunes":1499},{"body":1497,"title":1498,"variant":559},"\u003Cstrong>SLM = understands the request.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Knowledge = explains supported NVIDIA\u002FPC concepts.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Tools = perform actions.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Plug-ins = add new tools.\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>Your PC = the environment being inspected or changed.\u003C\u002Fstrong>","The easiest mental model",{},{"id":562,"data":1501,"type":566,"tunes":1503},{"title":1502,"maxLevel":565,"minLevel":47},"Contents",{},{"id":569,"data":1505,"type":572,"tunes":1507},{"text":1506,"level":47},"First: what is the AI model actually doing?",{},{"id":575,"data":1509,"type":544,"tunes":1511},{"text":1510},"G-Assist uses a local small language model, or SLM. NVIDIA currently describes the system as using a Llama-based 8-billion-parameter instruct model.",{},{"id":580,"data":1513,"type":544,"tunes":1515},{"text":1514},"The model's main job is not to render graphics or directly change hardware registers. Its job is to understand the user's language, decide which supported capability matches the request, and prepare the call to that capability.",{},{"id":585,"data":1517,"type":544,"tunes":1519},{"text":1518},"For example, if you say “set DLSS Super Resolution to Performance Mode,” the language model does not itself modify DLSS. It interprets the command and routes it to the supported function that can change the setting.",{},{"id":590,"data":1521,"type":552,"tunes":1524},{"body":1522,"title":1523,"variant":594},"The AI model \u003Cstrong>decides what tool to call\u003C\u002Fstrong>. The tool \u003Cstrong>does the real work\u003C\u002Fstrong>.","The important distinction",{},{"id":597,"data":1526,"type":572,"tunes":1528},{"text":1527,"level":47},"The G-Assist action pipeline",{},{"id":602,"data":1530,"type":625,"tunes":1551},{"steps":1531,"title":1550,"orientation":624},[1532,1535,1538,1541,1544,1547],{"label":1533,"description":1534},"1. You give a natural-language request","For example: “Optimize this game for performance.”",{"label":1536,"description":1537},"2. The local SLM interprets the request","It determines the user's intent and identifies which supported function or plug-in is relevant.",{"label":1539,"description":1540},"3. The system chooses a tool","That could be a built-in graphics-setting function, driver check, monitoring function or community plug-in.",{"label":1542,"description":1543},"4. Arguments are extracted","The model converts the request into structured values such as game name, mode, fan profile or DLSS setting.",{"label":1545,"description":1546},"5. The tool executes","The tool talks to the NVIDIA App, operating system, peripheral software or another service.",{"label":1548,"description":1549},"6. The result is returned","G-Assist reports what happened, or returns data that the model can explain.","What happens after you give G-Assist a command",{},{"id":628,"data":1553,"type":572,"tunes":1555},{"text":1554,"level":47},"This is tool calling, not magic PC control",{},{"id":633,"data":1557,"type":544,"tunes":1559},{"text":1558},"A language model cannot safely control an arbitrary computer simply because it understands English.",{},{"id":638,"data":1561,"type":544,"tunes":1563},{"text":1562},"It needs a defined interface that says which actions exist, which arguments they accept and what the tool returns.",{},{"id":643,"data":1565,"type":544,"tunes":1567},{"text":1566},"G-Assist's current built-in capabilities include functions such as optimizing graphics settings, changing supported RTX options, checking or downloading drivers, showing performance information, changing some laptop power features, controlling supported monitor functions and using supported peripheral plug-ins.",{},{"id":648,"data":1569,"type":676,"tunes":1589},{"rows":1570,"title":1583,"layout":668,"columns":1584},[1571,1574,1577,1580],{"id":652,"label":1572,"values":1573},"Understand “turn on DLSS”",[13,13],{"id":656,"label":1575,"values":1576},"Choose the correct function",[13,13],{"id":660,"label":1578,"values":1579},"Actually change the setting",[13,13],{"id":664,"label":1581,"values":1582},"Explain the result",[13,13],"Language model vs tool",[1585,1587],{"id":671,"label":1586},"Language model",{"id":674,"label":1588},"Tool \u002F plug-in",{},{"id":679,"data":1591,"type":572,"tunes":1593},{"text":1592,"level":47},"What is the knowledge layer?",{},{"id":684,"data":1595,"type":544,"tunes":1597},{"text":1596},"G-Assist also has a knowledge layer for answering questions and making recommendations.",{},{"id":689,"data":1599,"type":544,"tunes":1601},{"text":1600},"NVIDIA says version 0.2.1 introduced an improved knowledge system that helps G-Assist make more accurate settings recommendations.",{},{"id":694,"data":1603,"type":544,"tunes":1605},{"text":1604},"That knowledge layer is different from the live state of your PC.",{},{"id":699,"data":1607,"type":676,"tunes":1623},{"rows":1608,"title":1617,"layout":668,"columns":1618},[1609,1611,1614],{"id":703,"label":704,"values":1610},[13,13],{"id":707,"label":1612,"values":1613},"Game settings",[13,13],{"id":711,"label":1615,"values":1616},"Performance",[13,13],"Knowledge vs live PC state",[1619,1621],{"id":717,"label":1620},"Knowledge",{"id":720,"label":1622},"Live state",{},{"id":724,"data":1625,"type":552,"tunes":1628},{"body":1626,"title":1627,"variant":728},"\u003Cstrong>Knowledge\u003C\u002Fstrong> tells the assistant what a feature means or what usually matters.\u003Cbr>\u003Cstrong>State\u003C\u002Fstrong> tells it what is true on your machine right now.","Do not mix knowledge with state",{},{"id":731,"data":1630,"type":737,"tunes":1634},{"url":733,"title":1631,"excerpt":1632,"ctaLabel":1633},"What Is RAG? The Simplest Explanation of How It Works","A plain-English explanation of knowledge retrieval, state, memory, context and the language model.","Read the simple RAG guide",{},{"id":740,"data":1636,"type":572,"tunes":1638},{"text":1637,"level":47},"Does G-Assist use RAG?",{},{"id":745,"data":1640,"type":544,"tunes":1642},{"text":1641},"The safest answer is: G-Assist clearly has a knowledge system, but NVIDIA's public product page does not document every internal retrieval mechanism in enough detail to say that every knowledge answer is specifically produced by RAG.",{},{"id":750,"data":1644,"type":544,"tunes":1646},{"text":1645},"The architectural distinction still matters. A retrieval layer can provide relevant knowledge, while system tools provide current PC state and perform actions.",{},{"id":755,"data":1648,"type":544,"tunes":1650},{"text":1649},"That is the same separation used in many modern agents: knowledge is one source of context, live observations are another, and tool execution is a third.",{},{"id":760,"data":1652,"type":572,"tunes":1654},{"text":1653,"level":47},"Why G-Assist can work offline",{},{"id":765,"data":1656,"type":544,"tunes":1658},{"text":1657},"NVIDIA runs the language model locally on the GeForce RTX GPU.",{},{"id":770,"data":1660,"type":544,"tunes":1662},{"text":1661},"That means the core assistant does not require a cloud-hosted language model for every prompt.",{},{"id":775,"data":1664,"type":544,"tunes":1666},{"text":1665},"NVIDIA explicitly says G-Assist can run offline for its local capabilities.",{},{"id":780,"data":1668,"type":544,"tunes":1670},{"text":1669},"A plug-in can still use the internet if that plug-in calls an online service. Local model execution and online plug-in access are separate questions.",{},{"id":785,"data":1672,"type":572,"tunes":1674},{"text":1673,"level":47},"The local-AI cost: G-Assist uses your GPU and VRAM",{},{"id":790,"data":1676,"type":544,"tunes":1678},{"text":1677},"Running locally gives privacy and independence from a cloud model, but the work has to execute somewhere.",{},{"id":795,"data":1680,"type":544,"tunes":1682},{"text":1681},"For G-Assist, that somewhere is the same GeForce RTX GPU that may already be rendering your game.",{},{"id":800,"data":1684,"type":544,"tunes":1686},{"text":1685},"NVIDIA warns that the GPU briefly allocates compute resources to AI inference when G-Assist responds. If a demanding game is running at the same time, the game can temporarily lose some rendering performance while the model is active.",{},{"id":805,"data":1688,"type":544,"tunes":1690},{"text":1689},"The current requirements also specify free-VRAM targets beyond the memory already used by the game: approximately 6 GB of free VRAM for Reasoning Mode and 4.5 GB for Flash Mode.",{},{"id":810,"data":1692,"type":552,"tunes":1695},{"body":1693,"title":1694,"variant":728},"The game, Windows, the driver and other applications already consume VRAM. G-Assist's own requirement is about \u003Cstrong>free VRAM in addition to what the running workload already uses\u003C\u002Fstrong>.","8 GB VRAM does not mean 8 GB is available to G-Assist",{},{"id":816,"data":1697,"type":737,"tunes":1702},{"url":1698,"title":1699,"excerpt":1700,"ctaLabel":1701},"https:\u002F\u002Ffigure.rocks\u002Fblog\u002Fvram-usage-is-not-vram-requirement-why-a-full-memory-meter-does-not-tell-the-whole-story","VRAM Usage Is Not VRAM Requirement: Why a Full Memory Meter Does Not Tell the Whole Story","Why installed VRAM, current usage, residency budgets and real memory pressure are different things.","Read the VRAM guide",{},{"id":824,"data":1704,"type":572,"tunes":1706},{"text":1705,"level":47},"Reasoning Mode vs Flash Mode",{},{"id":829,"data":1708,"type":544,"tunes":1710},{"text":1709},"Current G-Assist versions separate a more capable Reasoning Mode from a faster Flash Mode.",{},{"id":834,"data":1712,"type":544,"tunes":1714},{"text":1713},"Reasoning Mode is designed for higher-quality decisions and can coordinate multiple actions from one prompt. Flash Mode is optimized for faster responses and lower resource demand.",{},{"id":839,"data":1716,"type":676,"tunes":1730},{"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],[1728,1729],{"id":856,"label":857},{"id":859,"label":860},{},{"id":863,"data":1732,"type":572,"tunes":1734},{"text":1733,"level":47},"What plug-ins actually add",{},{"id":868,"data":1736,"type":544,"tunes":1738},{"text":1737},"A plug-in does not replace the language model. It gives the model a new action it is allowed to call.",{},{"id":873,"data":1740,"type":544,"tunes":1742},{"text":1741},"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":1744,"type":544,"tunes":1746},{"text":1745},"That lets the assistant grow beyond NVIDIA's built-in functions.",{},{"id":883,"data":1748,"type":625,"tunes":1766},{"steps":1749,"title":1765,"orientation":624},[1750,1753,1756,1759,1762],{"label":1751,"description":1752},"1. Plug-in declares a function","For example: set_keyboard_color(color).",{"label":1754,"description":1755},"2. Manifest describes the function","The manifest tells G-Assist what the function does and what parameters it needs.",{"label":1757,"description":1758},"3. User asks naturally","For example: “Make my keyboard green.”",{"label":1760,"description":1761},"4. SLM selects the function","The model maps the request to the plug-in function and extracts green as the parameter.",{"label":1763,"description":1764},"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":1768,"type":572,"tunes":1770},{"text":1769,"level":47},"G-Assist Protocol V2 is JSON-RPC 2.0",{},{"id":909,"data":1772,"type":544,"tunes":1774},{"text":1773},"NVIDIA's current public plug-in repository uses Protocol V2.",{},{"id":914,"data":1776,"type":544,"tunes":1778},{"text":1777},"Protocol V2 uses JSON-RPC 2.0 with length-prefixed messages between the G-Assist engine and plug-ins.",{},{"id":919,"data":1780,"type":544,"tunes":1782},{"text":1781},"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":1784,"type":676,"tunes":1802},{"rows":1785,"title":1796,"layout":668,"columns":1797},[1786,1788,1790,1792,1794],{"id":928,"label":928,"values":1787},[13,13],{"id":931,"label":931,"values":1789},[13,13],{"id":934,"label":934,"values":1791},[13,13],{"id":937,"label":937,"values":1793},[13,13],{"id":940,"label":940,"values":1795},[13,13],"The important Protocol V2 messages",[1798,1800],{"id":945,"label":1799},"Direction",{"id":948,"label":1801},"Purpose",{},{"id":952,"data":1804,"type":572,"tunes":1806},{"text":1805,"level":47},"Where MCP enters the picture",{},{"id":957,"data":1808,"type":544,"tunes":1810},{"text":1809},"G-Assist's own plug-in protocol is not MCP. Its current public plug-in system uses JSON-RPC 2.0.",{},{"id":962,"data":1812,"type":544,"tunes":1814},{"text":1813},"However, a G-Assist plug-in can connect to an MCP server.",{},{"id":967,"data":1816,"type":544,"tunes":1818},{"text":1817},"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":1820,"type":552,"tunes":1823},{"body":1821,"title":1822,"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":1825,"type":572,"tunes":1827},{"text":1826,"level":47},"Why this matters beyond RGB lights",{},{"id":983,"data":1829,"type":544,"tunes":1831},{"text":1830},"The plug-in architecture turns G-Assist from a fixed assistant into a local tool router.",{},{"id":988,"data":1833,"type":544,"tunes":1835},{"text":1834},"The same pattern can connect an SLM to monitoring tools, peripherals, APIs, automation systems, local applications or external services.",{},{"id":993,"data":1837,"type":544,"tunes":1839},{"text":1838},"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":1841,"type":572,"tunes":1843},{"text":1842,"level":47},"The Local Agent Stack",{},{"id":1003,"data":1845,"type":625,"tunes":1869},{"steps":1846,"title":1868,"orientation":624},[1847,1850,1853,1856,1859,1862,1865],{"label":1848,"description":1849},"1. User intent","Natural language or voice command.",{"label":1851,"description":1852},"2. Local SLM","Understands the request and chooses a capability.",{"label":1854,"description":1855},"3. Knowledge \u002F context","Provides product knowledge, recommendations or information needed for the decision.",{"label":1857,"description":1858},"4. Live system state","Provides current hardware, driver, performance or configuration information when supported.",{"label":1860,"description":1861},"5. Tool selection","Built-in function or plug-in is chosen.",{"label":1863,"description":1864},"6. Structured execution","The function receives arguments and performs the real action.",{"label":1866,"description":1867},"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":1871,"type":572,"tunes":1873},{"text":1872,"level":47},"Why tool boundaries are a safety feature",{},{"id":1035,"data":1875,"type":544,"tunes":1877},{"text":1876},"An AI assistant that could execute arbitrary operating-system commands would be far more powerful, but also much harder to constrain.",{},{"id":1040,"data":1879,"type":544,"tunes":1881},{"text":1880},"G-Assist instead exposes defined functions with known parameters.",{},{"id":1045,"data":1883,"type":544,"tunes":1885},{"text":1884},"That means the model can only perform actions that the built-in function set or installed plug-ins make available.",{},{"id":1050,"data":1887,"type":544,"tunes":1889},{"text":1888},"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":1891,"type":572,"tunes":1893},{"text":1892,"level":47},"The Tool-Authority Boundary",{},{"id":1060,"data":1895,"type":676,"tunes":1914},{"rows":1896,"title":1908,"layout":668,"columns":1909},[1897,1900,1903,1905],{"id":703,"label":1898,"values":1899},"GPU tuning",[13,13],{"id":1067,"label":1901,"values":1902},"Files",[13,13],{"id":1071,"label":1072,"values":1904},[13,13],{"id":1075,"label":1906,"values":1907},"Peripheral control",[13,13],"What the assistant can understand vs what it is allowed to do",[1910,1912],{"id":652,"label":1911},"Model may understand",{"id":1083,"label":1913},"Tool authority",{},{"id":1087,"data":1916,"type":572,"tunes":1918},{"text":1917,"level":47},"Why G-Assist can temporarily reduce game performance",{},{"id":1092,"data":1920,"type":544,"tunes":1922},{"text":1921},"The local-model architecture has a straightforward consequence: the AI and the game can compete for the same GPU.",{},{"id":1097,"data":1924,"type":544,"tunes":1926},{"text":1925},"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":1928,"type":544,"tunes":1930},{"text":1929},"Once inference finishes, those GPU resources return to the game.",{},{"id":1107,"data":1932,"type":544,"tunes":1934},{"text":1933},"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":1936,"type":572,"tunes":1938},{"text":1937,"level":47},"The Local Assistant Resource Test",{},{"id":1117,"data":1940,"type":625,"tunes":1961},{"steps":1941,"title":1960,"orientation":624},[1942,1945,1948,1951,1954,1957],{"label":1943,"description":1944},"1. Check installed VRAM","The current G-Assist baseline is an RTX GPU with at least 6 GB VRAM.",{"label":1946,"description":1947},"2. Check free VRAM during the actual game","Installed capacity is not the same as free capacity.",{"label":1949,"description":1950},"3. Choose Reasoning or Flash Mode appropriately","Use the lighter mode when resource pressure matters more than deep reasoning.",{"label":1952,"description":1953},"4. Measure inference-time frame-rate dips","Watch the game while asking G-Assist to perform tasks.",{"label":1955,"description":1956},"5. Inspect tool authority","Know exactly which built-in functions and plug-ins can change your system.",{"label":1958,"description":1959},"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":1963,"type":572,"tunes":1965},{"text":1964,"level":47},"Why plug-ins deserve the same scrutiny as any other software",{},{"id":1146,"data":1967,"type":544,"tunes":1969},{"text":1968},"A plug-in can connect the assistant to APIs, peripheral applications and online services.",{},{"id":1151,"data":1971,"type":544,"tunes":1973},{"text":1972},"That means a plug-in may handle configuration values, credentials or external requests depending on what it was built to do.",{},{"id":1156,"data":1975,"type":544,"tunes":1977},{"text":1976},"NVIDIA's repository explicitly provides a config.json location for plug-in settings and warns developers not to commit credentials.",{},{"id":1161,"data":1979,"type":544,"tunes":1981},{"text":1980},"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":1983,"type":572,"tunes":1985},{"text":1984,"level":47},"G-Assist is closer to an agent than a chatbot",{},{"id":1171,"data":1987,"type":544,"tunes":1989},{"text":1988},"A chatbot mainly produces language.",{},{"id":1176,"data":1991,"type":544,"tunes":1993},{"text":1992},"An agent interprets a goal, observes relevant information, chooses an action, calls a tool and evaluates the result.",{},{"id":1181,"data":1995,"type":544,"tunes":1997},{"text":1996},"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":1999,"type":737,"tunes":2004},{"url":2000,"title":2001,"excerpt":2002,"ctaLabel":2003},"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":2006,"type":572,"tunes":2008},{"text":2007,"level":47},"What G-Assist still is not",{},{"id":1199,"data":2010,"type":544,"tunes":2012},{"text":2011},"NVIDIA explicitly describes G-Assist as a specialized local assistant, not a general-purpose conversational AI.",{},{"id":1204,"data":2014,"type":544,"tunes":2016},{"text":2015},"Its value comes from understanding a focused set of PC and gaming tasks and having tools connected to those tasks.",{},{"id":1209,"data":2018,"type":544,"tunes":2020},{"text":2019},"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":2022,"type":572,"tunes":2024},{"text":2023,"level":47},"What changed in the current versions?",{},{"id":1219,"data":2026,"type":544,"tunes":2028},{"text":2027},"The current public release history shows G-Assist moving steadily toward a more capable local agent.",{},{"id":1224,"data":2030,"type":668,"tunes":2045},{"content":2031,"stretched":1245,"withHeadings":15},[2032,2035,2037,2039,2041,2043],[2033,2034],"Version","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":2081},{"text":2080,"level":47},"Conclusion",{},{"id":1293,"data":2083,"type":544,"tunes":2085},{"text":2084},"The easiest way to understand Project G-Assist is to stop thinking of it as a chatbot.",{},{"id":1298,"data":2087,"type":544,"tunes":2089},{"text":2088},"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":2091,"type":544,"tunes":2093},{"text":2092},"That is a local agent architecture.",{},{"id":1308,"data":2095,"type":544,"tunes":2097},{"text":2096},"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":2099,"type":572,"tunes":2101},{"text":2100,"level":47},"FAQ",{},{"id":1318,"data":2103,"type":1350,"tunes":2127},{"items":2104,"title":2126},[2105,2108,2111,2114,2117,2120,2123],{"id":1322,"answer":2106,"question":2107},"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":2109,"question":2110},"NVIDIA currently describes it as a local Llama-based instruct model with 8 billion parameters.","What model does G-Assist use?",{"id":1330,"answer":2112,"question":2113},"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":2115,"question":2116},"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":2118,"question":2119},"Not directly. 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Koristite ovaj rečnik da biste izabrali pravi režim za jasnoću i osećaj u igrama.","2026-02-20T14:00:00.000Z",{"id":2683,"slug":2684,"title":2685,"excerpt":2686,"featuredImage":14,"publishedAt":2687},"142","display-cable-and-port-basics-fixing-120hz-vrr-and-hdr-handshake-issues","Osnove kabela i portova za displej: Popravka problema sa usklađivanjem 120Hz, VRR i HDR","Mnogi ‘problemi sa funkcijama’ su problemi sa uspostavljanjem veze: pogrešan port, pogreban kabl, pogrešan režim ulaza. Koristite ovu osnovu da vratite 120Hz, VRR i HDR.","2026-02-20T11:30:00.000Z",{"id":2689,"slug":2690,"title":2691,"excerpt":2692,"featuredImage":14,"publishedAt":2693},"206","display-processing-traps-the-settings-that-secretly-ruin-clarity-and-feel","Zamke obrade slike na ekranu: Podešavanja koja tajno kvare jasnoću i osećaj","Mnogi ekrani se isporučuju sa procesiranjem koje izgleda „lepo“ u filmovima, ali kvari gejming: dodatno kašnjenje, artefakti i nestabilnost. Evo kratke liste onoga što treba onemogućiti i zašto.","2026-02-21T00:22:00.000Z",{"id":2695,"slug":2696,"title":2697,"excerpt":2698,"featuredImage":14,"publishedAt":2699},"209","windows-audio-mixer-traps-why-pc-audio-feels-inconsistent-in-games","Zamke Windows audio miksera: Zašto PC zvuk deluje nedosledno u igrama","PC zvuk deluje nasumično kada se rutiranje menja neprimetno. Saznajte zamke miksera (promena podrazumevanog uređaja, poboljšanja, rutiranje aplikacija) i kako da zaključate jednu stabilnu putanju.","2026-02-20T23:40:00.000Z",{"id":2701,"slug":2702,"title":2703,"excerpt":2704,"featuredImage":14,"publishedAt":2705},"174","windows-game-mode-myths-what-it-does-and-what-actually-matters","Mitovi o Windows Game Mode-u: Šta on radi (i šta je zapravo važno)","Windows Game Mode nije magični prekidač za latenciju. Najveći dobici i dalje dolaze od stabilnog ujednačavanja frejmova i kontrole pozadinskog opterećenja. Koristite ga, ali ga nemojte obožavati.","2026-02-20T15:00:00.000Z",{"id":2707,"slug":2708,"title":2709,"excerpt":2710,"featuredImage":14,"publishedAt":2711},"96","game-mode-on-tvs-and-monitors-the-one-setting-that-changes-everything","Režim igre na televizorima i monitorima: Jedna postavka koja menja sve","Ako igra deluje tromo, prvo proverite režim igre. Saznajte šta režim igre onemogućava, zašto smanjuje kašnjenje i kako da potvrdite da on zaista radi.","2026-02-19T11:00:00.000Z",{"id":2713,"slug":2714,"title":2715,"excerpt":2716,"featuredImage":14,"publishedAt":2717},"180","router-checklist-v2-the-12-settings-that-prevent-lag-spikes","Kontrolna lista za ruter v2: 12 podešavanja koja sprečavaju skokove laga","Većina skokova laga potiče od opterećenja i nestabilnosti, a ne od ‘lošeg pinga’. Koristite ovu kontrolnu listu za ruter da biste stabilizovali latenciju pod opterećenjem pre kupovine nove opreme.","2026-02-20T16:00:00.000Z",{"id":2719,"slug":2720,"title":2721,"excerpt":2722,"featuredImage":14,"publishedAt":2723},"246","router-checklist-for-gaming-the-settings-that-actually-matter","Kontrolna lista za ruter za gejming: Podešavanja koja su zaista bitna","Većina podešavanja rutera ne pomaže. Ova podešavanja pomažu: upravljanje redovima čekanja pod opterećenjem, stabilno Wi-Fi ponašanje i izbegavanje funkcija koje dodaju kašnjenje ili nestabilnost.","2026-02-21T01:30:00.000Z",{"id":2725,"slug":2726,"title":2727,"excerpt":2728,"featuredImage":14,"publishedAt":2729},"159","ethernet-vs-wi-fi-for-gaming-the-real-reasons-ethernet-wins","Ethernet vs Wi-Fi za gejming: Pravi razlozi zašto Ethernet pobeđuje","Ethernet nije stvar brzine. Reč je o stabilnosti: manje skokova, manje smetnji i predvidljiv tajming. Iskoristite ovo da odlučite kada je Wi-Fi ‘dovoljno dobar’.","2026-02-20T13:00:00.000Z",{"id":2731,"slug":2732,"title":2733,"excerpt":2734,"featuredImage":14,"publishedAt":2735},"199","wi-fi-bands-decision-2-4-vs-5-vs-6e-gaming-stability-first","Odluka o Wi-Fi opsezima: 2.4 vs 5 vs 6E (Stabilnost gejminga na prvom mestu)","Birajte Wi-Fi opsege prema stabilnosti, a ne na osnovu pompe. Koristite ovaj vodič za odlučivanje da odaberete 2.4, 5 ili 6E na osnovu udaljenosti, zagušenja i stvarnog ponašanja džitera.","2026-02-20T18:00:00.000Z","fallback",[],[]]