Pareto 26.10

{"about":"### Pareto 26.10 qanday tuzilgan\n\nPareto 26.10 — Unbiased tarkibli modelining barqaror nashri. Uning asosida har bir so‘rov uchun bir nechta ilg‘or va ochiq model tanlanib, natijalari bitta javobga birlashtiriladigan yondashuv yotadi. Bu savolni bitta tanlangan modelga oddiy uzatishdan farq qiladi: foydalanuvchi bitta Pareto bilan muloqot qilib, umumiy natija oladi. Qatnashuvchi modellar tarkibi o‘zgarishi mumkin, shuning uchun nashr nomi asosiy modellarning qatʼiy ro‘yxatini belgilamaydi.\n\n### Ailootʼda matn bilan ishlash\n\nAilootʼda Pareto 26.10 matn qabul qilib, matn qaytaradi. Ulanish kontekst oynasi — 1 048 576 token. Unga ko‘rsatmalar, suhbat tarixi, berilgan materiallar va yaratilayotgan javob joylashadi. Model metamaʼlumotlarida javob hajmi 131 072 tokengacha deb ko‘rsatilgan; bu har bir generatsiyaning majburiy uzunligi emas, yuqori chegaradir. Mazmunli ish uchun natija hajmi va bo‘limlar tartibini oldindan belgilash foydali.\n\nUzun kontekst bitta so‘rovda bir nechta matn materialini taqqoslashga imkon beradi: texnik topshiriq va yechim, talablar va muhokama bayonnomasi, hujjatning bir nechta varianti. Dastlabki parchalarni tushunarli nomlar bilan yuboring va xulosalarni ularga bog‘lashni so‘rang. Masalan, farqlar jadvalini tuzish, talablar ziddiyatini ajratish yoki butun to‘plam asosida o‘zgarish rejasini tayyorlash mumkin. Bular matnli vazifa qo‘yish usullari; fayllaringiz yoki tashqi tizimlarga kirishni ilova belgilaydi.\n\n### Ishchi so‘rovni qanday tuzish kerak\n\nKod tahlili uchun tegishli funksiyalar, kutilgan xatti-harakat va kuzatilgan xatoni kiriting. Avval ular orasidagi bog‘liqlikni tushuntirish, keyin mahalliy o‘zgarish va tekshirish usullarini taklif qilishni so‘rang. Berilgan matnlar bo‘yicha tadqiqotda savol qo‘ying, manbalarni so‘rov ichida sanang va qaysi fikrlar tegishli parchaga havola bilan kelishi kerakligini belgilang. Hujjat tayyorlash uchun auditoriya, maqsad, majburiy bo‘limlar va qabul mezonlarini bering.\n\nMatnli ulanish Messages, Responses, Chat Completions usullari va matnli generateContent interfeysi bilan berilgan. Format tanlash modelni mavjud mijozga qo‘shishga yordam beradi. Uning o‘zi tasvir o‘qish, veb-qidiruv yoki buyruq bajarishni qo‘shmaydi. Olingan kod, reja va tavsiyalar ilovangiz keyingi harakatlarni bajarmaguncha matn yaratish natijasi bo‘lib qoladi.\n\n### Versiyani aniq tanlash\n\n`unbiased/pareto-26.10` identifikatori aynan 26.10 nashrini tanlaydi. Bu modelni ilova sozlamalarida aniq belgilash yoki bir versiya natijalarini o‘z vazifalaringiz to‘plamida taqqoslash uchun qulay. 26.9 nashri alohida mavjud va o‘z kontekst oynasiga ega.","alias_of":null,"aliases":[],"author":"Unbiased","canonical_model":"unbiased/pareto-26.10","ctx":null,"formats":["chat","gemini","messages","responses"],"id":"unbiased/pareto-26.10","input":["text"],"kind":"text","max_out":null,"methods":[{"cache_read":0.06,"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":1.6,"input":["text"],"label":"Anthropic Messages","max_out":null,"max_tool_calls":null,"out":6.4,"output":["text"],"path":"/v1/messages","request_model_id":"unbiased/pareto-26.10","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.06,"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":1.6,"input":["text"],"label":"OpenAI Responses","max_out":null,"max_tool_calls":null,"out":6.4,"output":["text"],"path":"/v1/responses","request_model_id":"unbiased/pareto-26.10","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.06,"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":1.6,"input":["text"],"label":"OpenAI Chat","max_out":null,"max_tool_calls":null,"out":6.4,"output":["text"],"path":"/v1/chat/completions","request_model_id":"unbiased/pareto-26.10","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.06,"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":1.6,"input":["text"],"label":"Gemini generateContent","max_out":null,"max_tool_calls":null,"out":6.4,"output":["text"],"path":"/v1beta/models/unbiased/pareto-26.10:generateContent","request_model_id":"unbiased/pareto-26.10","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]}],"model_aliases":[{"canonical_model_id":"unbiased/pareto-26.10","request_model_id":"unbiased/pareto-26.10","route_label":"Ultra"}],"name":"Pareto 26.10","price":{"in":1.6,"in_label":null,"out":6.4,"out_label":null,"sort_in":1.6,"sort_out":6.4,"varies":false},"public_id":"unbiased/pareto-26.10","short":"Katta materiallar to‘plamini tahlil qilish va batafsil javob tayyorlash uchun 1 048 576 tokenli kontekstga ega Unbiased tarkibli matn modeli."}