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MoonshotAI: Kimi K3.1 Pro

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MoonshotAI: Kimi K3.1 Pro

moonshotai/kimi-k3.1-pro
MoonshotAIMatnKirish from 0,002 US$ / 1KChiqish from 0,01 US$ / 1K

Kimi K3.1 Pro murakkab materiallarni tahlil qilish, kod yozish va loyiha, modellashtirish hamda tahlil uchun matnli yechimlar tayyorlashga yordam beradi.

Kimi K3.1 Pro — Moonshot AI modeli, K3.1 seriyasidagi birinchi model. U Kimi K3 asosida keyingi o‘qitish va ko‘plab sohalarda birgalikdagi mustahkamlash orqali o‘qitish hajmi sezilarli oshirilgan holda yaratilgan. Rasmiy tavsifda dasturlash, uch o‘lchamli loyihalar, moliyaviy tadqiqotlar va bir nechta bog‘liq bosqichni talab etadigan vazifalar ajratib ko‘rsatilgan.

Dasturlash va texnik loyihalar

Modeldan mavjud kodni tahlil qilish, o‘zgarishlar tayyorlash va ishlab chiqishni rejalash uchun foydalanish mumkin. Maqsad, joriy yechim va cheklovlarni bering: masalan, qaysi interfeyslar saqlanishi va to‘g‘ri natija qanday ko‘rinishi kerak. Javobda izoh, patch matni, sinov ssenariylari yoki joriy etish ketma-ketligini so‘rash mumkin.

O‘yinlar, interaktiv sahnalar va parametrik modellashtirishda skript hamda texnik mantiq tayyorlash vazifalari foydali. Ishlab chiqaruvchi hujjatlarida Blender, CAD va o‘yin dvigatellari bilan ishlash ko‘rib chiqilgan. Ailootʼda bu kartochka natijasi matn bo‘lgani uchun so‘rovni tanlangan vosita kodi, geometriya tavsifi yoki sahna qurish rejasi sifatida berib, keyin o‘z muhitingizda ishga tushirish qulay.

Berilgan maʼlumotlar bo‘yicha tahlil

Hujjatlar bilan ishlashda manbalarni taqqoslash, hisobni tushuntirish, farazlar izchilligini tekshirish yoki tadqiqot yozuvi tayyorlashni so‘rash mumkin. Moliyaviy model uchun boshlang‘ich ko‘rsatkichlar, o‘lchov birliklari va ular orasidagi bog‘lanishlarni bering. Model formulalar matni va tekshiruv tartibini, hisobot uchun esa taqdim etilgan materiallarga bog‘langan tuzilma va dalillarni taklif qilishi mumkin.

Foydali javobni qanday olish mumkin

  1. Vazifa va kutilgan natijani belgilang: izoh, kod, reja yoki tahliliy xulosa.
  2. Kerakli matnlarni qo‘shib, qaysi manbalar ustuvorligini ko‘rsating.
  3. Tekshirish mezonlarini yozing: saqlanadigan shartlar, format, hisob aniqligi va majburiy bo‘limlar.
  4. Muhim qarorlar va boshlang‘ich cheklovlarni saqlab, ishni aniqlashtirishlar orqali davom ettiring.

Ailootʼdagi kirish va natija

Kartochka matn qabul qiladi va matn qaytaradi. Ko‘rsatmalar, hujjat parchalari, manba kodi, matn ko‘rinishidagi jadvallar va muhokama tarixi mos keladi. K3.1 Proʼda mulohaza doim yoqilgan; model hujjatlarida low, high va max darajalari bor. Standardʼda kirish chegarasi 262 144 tokengacha, javob esa 65 536 tokengacha belgilangan. Katta so‘rov tayyorlashda suhbat tarixini hisobga olib, material hajmini aniq savolga mos tanlang.

Ailoot API orqali mavjud

Core Anthropic MessagesPOST /v1/messages
Kirish
text
Chiqish
text
Kontekst
262 144 token
Maks. javob
65 536 token
Kirish
0,002 US$ / 1K
Chiqish
0,01 US$ / 1K
Keshdan o‘qish
0,0002 US$ / 1K
Keshga yozish
0,002 US$ / 1K
Keshga yozish, 5 daqiqa
0,002 US$ / 1K tokens
Core OpenAI ResponsesPOST /v1/responses
Kirish
text
Chiqish
text
Kontekst
262 144 token
Maks. javob
65 536 token
Kirish
0,002 US$ / 1K
Chiqish
0,01 US$ / 1K
Keshdan o‘qish
0,0002 US$ / 1K
Keshga yozish
0,002 US$ / 1K
Keshga yozish, 5 daqiqa
0,002 US$ / 1K tokens
Core OpenAI ChatPOST /v1/chat/completions
Kirish
text
Chiqish
text
Kontekst
262 144 token
Maks. javob
65 536 token
Kirish
0,002 US$ / 1K
Chiqish
0,01 US$ / 1K
Keshdan o‘qish
0,0002 US$ / 1K
Keshga yozish
0,002 US$ / 1K
Keshga yozish, 5 daqiqa
0,002 US$ / 1K tokens
Core Gemini generateContentPOST /v1beta/models/{model}:generateContent
Kirish
text
Chiqish
text
Kontekst
262 144 token
Maks. javob
65 536 token
Kirish
0,002 US$ / 1K
Chiqish
0,01 US$ / 1K
Keshdan o‘qish
0,0002 US$ / 1K
Keshga yozish
0,002 US$ / 1K
Keshga yozish, 5 daqiqa
0,002 US$ / 1K tokens
Ultra OpenAI ChatPOST /v1/chat/completions
Kirish
text
Chiqish
text
Kontekst
Katalogda ko‘rsatilmagan
Maks. javob
Katalogda ko‘rsatilmagan
Kirish
0,004 US$ / 1K
Chiqish
0,02 US$ / 1K
Keshdan o‘qish
0,0004 US$ / 1K
Keshga yozish
0,004 US$ / 1K
Keshga yozish, 5 daqiqa
0,004 US$ / 1K tokens
Ultra OpenAI ResponsesPOST /v1/responses
Kirish
text
Chiqish
text
Kontekst
Katalogda ko‘rsatilmagan
Maks. javob
Katalogda ko‘rsatilmagan
Kirish
0,004 US$ / 1K
Chiqish
0,02 US$ / 1K
Keshdan o‘qish
0,0004 US$ / 1K
Keshga yozish
0,004 US$ / 1K
Keshga yozish, 5 daqiqa
0,004 US$ / 1K tokens
Ultra Gemini generateContentPOST /v1beta/models/kimi-k3.1-pro:generateContent
Kirish
text
Chiqish
text
Kontekst
Katalogda ko‘rsatilmagan
Maks. javob
Katalogda ko‘rsatilmagan
Kirish
0,004 US$ / 1K
Chiqish
0,02 US$ / 1K
Keshdan o‘qish
0,0004 US$ / 1K
Keshga yozish
0,004 US$ / 1K
Keshga yozish, 5 daqiqa
0,004 US$ / 1K tokens
Ultra Anthropic MessagesPOST /v1/messages
Kirish
text
Chiqish
text
Kontekst
Katalogda ko‘rsatilmagan
Maks. javob
Katalogda ko‘rsatilmagan
Kirish
0,004 US$ / 1K
Chiqish
0,02 US$ / 1K
Keshdan o‘qish
0,0004 US$ / 1K
Ultra OpenAI ResponsesPOST /v1/responses
Kirish
text
Chiqish
text
Kontekst
Katalogda ko‘rsatilmagan
Maks. javob
Katalogda ko‘rsatilmagan
Kirish
0,004 US$ / 1K
Chiqish
0,02 US$ / 1K
Keshdan o‘qish
0,0004 US$ / 1K
Ultra OpenAI ChatPOST /v1/chat/completions
Kirish
text
Chiqish
text
Kontekst
Katalogda ko‘rsatilmagan
Maks. javob
Katalogda ko‘rsatilmagan
Kirish
0,004 US$ / 1K
Chiqish
0,02 US$ / 1K
Keshdan o‘qish
0,0004 US$ / 1K
Ultra Gemini generateContentPOST /v1beta/models/moonshotai/kimi-k3.1-pro:generateContent
Kirish
text
Chiqish
text
Kontekst
Katalogda ko‘rsatilmagan
Maks. javob
Katalogda ko‘rsatilmagan
Kirish
0,004 US$ / 1K
Chiqish
0,02 US$ / 1K
Keshdan o‘qish
0,0004 US$ / 1K
moonshotai/kimi-k3.1-pro · JSON
{"about":"Kimi K3.1 Pro — Moonshot AI modeli, K3.1 seriyasidagi birinchi model. U Kimi K3 asosida keyingi o‘qitish va ko‘plab sohalarda birgalikdagi mustahkamlash orqali o‘qitish hajmi sezilarli oshirilgan holda yaratilgan. Rasmiy tavsifda dasturlash, uch o‘lchamli loyihalar, moliyaviy tadqiqotlar va bir nechta bog‘liq bosqichni talab etadigan vazifalar ajratib ko‘rsatilgan.\n\n### Dasturlash va texnik loyihalar\n\nModeldan mavjud kodni tahlil qilish, o‘zgarishlar tayyorlash va ishlab chiqishni rejalash uchun foydalanish mumkin. Maqsad, joriy yechim va cheklovlarni bering: masalan, qaysi interfeyslar saqlanishi va to‘g‘ri natija qanday ko‘rinishi kerak. Javobda izoh, patch matni, sinov ssenariylari yoki joriy etish ketma-ketligini so‘rash mumkin.\n\nO‘yinlar, interaktiv sahnalar va parametrik modellashtirishda skript hamda texnik mantiq tayyorlash vazifalari foydali. Ishlab chiqaruvchi hujjatlarida Blender, CAD va o‘yin dvigatellari bilan ishlash ko‘rib chiqilgan. Ailootʼda bu kartochka natijasi matn bo‘lgani uchun so‘rovni tanlangan vosita kodi, geometriya tavsifi yoki sahna qurish rejasi sifatida berib, keyin o‘z muhitingizda ishga tushirish qulay.\n\n### Berilgan maʼlumotlar bo‘yicha tahlil\n\nHujjatlar bilan ishlashda manbalarni taqqoslash, hisobni tushuntirish, farazlar izchilligini tekshirish yoki tadqiqot yozuvi tayyorlashni so‘rash mumkin. Moliyaviy model uchun boshlang‘ich ko‘rsatkichlar, o‘lchov birliklari va ular orasidagi bog‘lanishlarni bering. Model formulalar matni va tekshiruv tartibini, hisobot uchun esa taqdim etilgan materiallarga bog‘langan tuzilma va dalillarni taklif qilishi mumkin.\n\n### Foydali javobni qanday olish mumkin\n\n1. Vazifa va kutilgan natijani belgilang: izoh, kod, reja yoki tahliliy xulosa.\n2. Kerakli matnlarni qo‘shib, qaysi manbalar ustuvorligini ko‘rsating.\n3. Tekshirish mezonlarini yozing: saqlanadigan shartlar, format, hisob aniqligi va majburiy bo‘limlar.\n4. Muhim qarorlar va boshlang‘ich cheklovlarni saqlab, ishni aniqlashtirishlar orqali davom ettiring.\n\n### Ailootʼdagi kirish va natija\n\nKartochka matn qabul qiladi va matn qaytaradi. Ko‘rsatmalar, hujjat parchalari, manba kodi, matn ko‘rinishidagi jadvallar va muhokama tarixi mos keladi. K3.1 Proʼda mulohaza doim yoqilgan; model hujjatlarida low, high va max darajalari bor. Standardʼda kirish chegarasi 262 144 tokengacha, javob esa 65 536 tokengacha belgilangan. Katta so‘rov tayyorlashda suhbat tarixini hisobga olib, material hajmini aniq savolga mos tanlang.","alias_of":null,"aliases":["k3.1-pro","kimi-k3.1-pro"],"author":"MoonshotAI","canonical_model":"moonshotai/kimi-k3.1-pro","ctx":262144,"formats":["chat","gemini","messages","responses"],"id":"moonshotai/kimi-k3.1-pro","input":["text"],"kind":"text","max_out":65536,"methods":[{"cache_read":0.2,"cache_write":2.0,"cache_write_1h":null,"cache_write_5m":2.0,"conditional_meter":null,"ctx":262144,"family":"anthropic","fast_multiplier":null,"flex_multiplier":null,"fmt":"messages","http":"POST","img_in":null,"img_out":null,"in":2.0,"input":["text"],"label":"Anthropic 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Responses","max_out":null,"max_tool_calls":null,"out":20.0,"output":["text"],"path":"/v1/responses","request_model_id":"kimi-k3.1-pro","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.4,"cache_write":4.0,"cache_write_1h":null,"cache_write_5m":4.0,"conditional_meter":null,"ctx":null,"family":"gemini","fast_multiplier":1,"flex_multiplier":1,"fmt":"gemini","http":"POST","img_in":null,"img_out":null,"in":4.0,"input":["text"],"label":"Gemini generateContent","max_out":null,"max_tool_calls":null,"out":20.0,"output":["text"],"path":"/v1beta/models/kimi-k3.1-pro:generateContent","request_model_id":"kimi-k3.1-pro","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.4,"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":4.0,"input":["text"],"label":"Anthropic 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generateContent","max_out":null,"max_tool_calls":null,"out":20.0,"output":["text"],"path":"/v1beta/models/moonshotai/kimi-k3.1-pro:generateContent","request_model_id":"moonshotai/kimi-k3.1-pro","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]}],"model_aliases":[{"canonical_model_id":"moonshotai/kimi-k3.1-pro","request_model_id":"k3.1-pro","route_label":"Core"},{"canonical_model_id":"moonshotai/kimi-k3.1-pro","request_model_id":"kimi-k3.1-pro","route_label":"Ultra"},{"canonical_model_id":"moonshotai/kimi-k3.1-pro","request_model_id":"moonshotai/kimi-k3.1-pro","route_label":"Ultra"}],"name":"MoonshotAI: Kimi K3.1 Pro","price":{"in":2.0,"in_label":null,"out":10.0,"out_label":null,"sort_in":2.0,"sort_out":10.0,"varies":true},"public_id":"moonshotai/kimi-k3.1-pro","short":"Kimi K3.1 Pro murakkab materiallarni tahlil qilish, kod yozish va loyiha, modellashtirish hamda tahlil uchun matnli yechimlar tayyorlashga yordam beradi."}

Savollar

Vazifam uchun modelni qanday tanlayman?

Avval kerakli kirish va chiqishni aniqlang: matn, rasm, audio yoki video. Keyin mos API usullari, modelning aniq ID qiymati yoki alias hozir yo‘naltiradigan model, narx va hisoblash birligini solishtiring. Bepul GET /v1/models kalitingizga ochiq modellarni ko‘rsatadi.

Har bir model barcha API usullari va media turlarini qo‘llaydimi?

Model kartasida ko‘rsatilgan API usullari hamda kirish va chiqish turlaridan foydalaning. Matn, rasm, audio yoki video qo‘llanishi tanlangan model va usulga bog‘liq; ma’lumot yuborishdan oldin ularning so‘rov misolini tekshiring.

Model ID qiymati bilan alias o‘rtasidagi farq nima?

Aniq ID muayyan modelni bildiradi. Alias modelga yo‘naltiradi va uning maqsad modeli o‘zgarishi mumkin. Katalogda alias hozir qaysi modelga yo‘naltirishini tekshiring; integratsiyaga muayyan model kerak bo‘lsa, aniq ID dan foydalaning.

So‘rov yuborishdan oldin narxlarni qanday solishtiraman?

Model kartasida tanlangan API usulining narxi va hisoblash birligini tekshiring. Bir xil birlik hamda kirish va chiqish turlarini solishtiring; so‘rovlar tarixi haqiqiy foydalanish va yechilgan summani ko‘rsatadi.

Obuna nima beradi?

Muntazam ishga token xaridi chegirmasini. So‘rov hajmingizga mos tarif tanlang; obuna sharti va narxi rasmiylashtirishda ko‘rsatiladi.

50% gacha promokod chegirmasini qanday qo‘llayman?

Token xaridida promokod kiriting. Yakuniy summa aksiya shartlari bo‘yicha qayta hisoblanadi; chegirma to‘lovdan oldin ko‘rinadi.