NVIDIA: Nemotron 3.5 Super VL

{"about":"### Mulohaza, kod va uzun matn bilan ishlash\n\nNemotron 3.5 Super VL — bir nechta mulohaza bosqichini bog‘lash, dastur kodini tushunish yoki katta materialni qayta ishlash kerak bo‘lgan vazifalar uchun NVIDIA modeli. Ailootʼda bu kartochka matnli muloqotni taqdim etadi: ko‘rsatmalar, asl maʼlumotlar va xabarlar tarixini yuborasiz, model esa matnli javob qaytaradi.\n\nUndan texnik hujjatlarni tahlil qilish, talablarni taqqoslash, kodga izohlar tayyorlash va matnli hisobotlarni tahlil qilish uchun foydalanish mumkin. So‘rovda maqsadni berish, kerakli materiallarni qo‘shish va natija shaklini belgilash qulay: masalan, asoslangan xulosalar ro‘yxati, dasturni o‘zgartirish rejasi yoki bir nechta yechimni taqqoslash.\n\n### Tuzilishi va ixtisosligi\n\nAsl Super VL — C-RADIO vizual enkoderiga ega, hujjat va videolarni tushunishga ham mo‘ljallangan NVIDIA vizual-til modeli. Bu Ailoot kartochkasida uning matn bilan ishlashi mavjud; asl materiallar matnli mazmun sifatida yuboriladi.\n\nModel asosi Mamba-2, Transformer va Mixture of Experts arxitekturasini birlashtiradi. Taxminan 120 milliard parametrdan qayta ishlash qadamida 12 milliardga yaqini faollashadi. Bu muayyan so‘rovning haqiqiy tezligidan alohida hisobga olinadigan model tuzilishidir.\n\nO‘qitishda dasturiy repozitoriylar, vazifa va kod o‘zgarishlari juftliklari, yig‘ish jurnallari, ko‘p bosqichli yechim yo‘llari va uzun kontekst materiallari ishlatilgan. Keyingi o‘qitish kod, mulohaza, ko‘rsatma va muloqot bilan ishlashni birlashtirgan. Bunday ixtisoslik asl maʼlumotlarni avval bog‘lab, keyin natijani rasmiylashtirish kerak bo‘lgan tarkibli vazifalarni qo‘yishda foydali.\n\n### Vazifani qanday tayyorlash kerak\n\nHujjat tahlili uchun avval savol va maʼlumot tanlash mezonlarini yozib, keyin bo‘lim sarlavhalari bilan matnni qo‘shing. Manbalarni taqqoslash kerak bo‘lsa, ularga qisqa belgi bering va xulosalarni shu belgilarga bog‘lashni so‘rang. Kod vazifasiga tegishli dastur parchasi, kuzatilgan xatti-harakat va kutilgan natijani qo‘shing; shunda javobni aniq holat bilan solishtirish mumkin.\n\nKatta kontekst oynasi bog‘liq materiallarni bitta so‘rovga joylashga yordam beradi. Kontekst hajmining o‘zi aniq vazifa bayoni o‘rnini bosmaydi: ko‘rsatmalarni asl maʼlumotlardan ajratib, qanday yechim yoki hujjat olmoqchi ekaningizni oldindan ko‘rsatish foydali.\n\n### Kontekst va ulanish usullari\n\nAilootʼda bu variant uchun 262144 tokenli kontekst oynasi ko‘rsatilgan. Suhbat tarixi, ko‘rsatmalar, asl materiallar va javob bu makondan birgalikda foydalanadi; uzun so‘rov tayyorlashda natija uchun joy qoldiring.\n\nModel Chat Completions, Responses, Messages va Gemini formatidagi matnli interfeys orqali mavjud. Bu variantdagi jarayon — kirishda matn, chiqishda matn; hujjatlar matnli mazmun sifatida uzatiladi.","alias_of":null,"aliases":[],"author":"NVIDIA","canonical_model":"nvidia/nemotron-3.5-super-vl","ctx":null,"formats":["chat","gemini","messages","responses"],"id":"nvidia/nemotron-3.5-super-vl","input":["text"],"kind":"text","max_out":null,"methods":[{"cache_read":0.04,"cache_write":null,"cache_write_1h":null,"cache_write_5m":null,"conditional_meter":null,"ctx":null,"family":"anthropic","fast_multiplier":1,"flex_multiplier":1,"fmt":"messages","http":"POST","img_in":null,"img_out":null,"in":0.3,"input":["text"],"label":"Anthropic Messages","max_out":null,"max_tool_calls":null,"out":1.0,"output":["text"],"path":"/v1/messages","request_model_id":"nvidia/nemotron-3.5-super-vl","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.04,"cache_write":null,"cache_write_1h":null,"cache_write_5m":null,"conditional_meter":null,"ctx":null,"family":"openai","fast_multiplier":1,"flex_multiplier":1,"fmt":"responses","http":"POST","img_in":null,"img_out":null,"in":0.3,"input":["text"],"label":"OpenAI Responses","max_out":null,"max_tool_calls":null,"out":1.0,"output":["text"],"path":"/v1/responses","request_model_id":"nvidia/nemotron-3.5-super-vl","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.04,"cache_write":null,"cache_write_1h":null,"cache_write_5m":null,"conditional_meter":null,"ctx":null,"family":"openai","fast_multiplier":1,"flex_multiplier":1,"fmt":"chat","http":"POST","img_in":null,"img_out":null,"in":0.3,"input":["text"],"label":"OpenAI Chat","max_out":null,"max_tool_calls":null,"out":1.0,"output":["text"],"path":"/v1/chat/completions","request_model_id":"nvidia/nemotron-3.5-super-vl","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.04,"cache_write":null,"cache_write_1h":null,"cache_write_5m":null,"conditional_meter":null,"ctx":null,"family":"gemini","fast_multiplier":1,"flex_multiplier":1,"fmt":"gemini","http":"POST","img_in":null,"img_out":null,"in":0.3,"input":["text"],"label":"Gemini generateContent","max_out":null,"max_tool_calls":null,"out":1.0,"output":["text"],"path":"/v1beta/models/nvidia/nemotron-3.5-super-vl:generateContent","request_model_id":"nvidia/nemotron-3.5-super-vl","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]}],"model_aliases":[{"canonical_model_id":"nvidia/nemotron-3.5-super-vl","request_model_id":"nvidia/nemotron-3.5-super-vl","route_label":"Ultra"}],"name":"NVIDIA: Nemotron 3.5 Super VL","price":{"in":0.3,"in_label":null,"out":1.0,"out_label":null,"sort_in":0.3,"sort_out":1.0,"varies":false},"public_id":"nvidia/nemotron-3.5-super-vl","short":"Mulohaza, kod bilan ishlash va katta materiallarni tahlil qilish uchun NVIDIA modeli bilan matnli muloqot."}