Source: https://ailoot.ai/models/uz/minimax-minimax-m3-1-flash/
Canonical: https://ailoot.ai/models/uz/minimax-minimax-m3-1-flash/
Language: uz

# MiniMax: MiniMax M3.1 Flash

[Markdown](https://ailoot.ai/models/uz/minimax-minimax-m3-1-flash/index.md) · [JSON](https://ailoot.ai/models/uz/minimax-minimax-m3-1-flash/facts.json)

## [MiniMax: MiniMax M3.1 Flash](https://ailoot.ai/models/uz/minimax-minimax-m3-1-flash/)

`minimax/minimax-m3.1-flash`

MiniMaxMatnKirish from 0,00015 US$ / 1KChiqish from 0,0006 US$ / 1K

MiniMax M3.1 Flash hujjat tahlili, kod yozish va ko‘p bosqichli vazifalarni rejalashga yordam beradi; Standardʼda Chat Completions va Responses orqali tasvir ham kiritiladi.

MiniMax M3.1 Flash — MiniMaxʼning 2026-yil 19-oktabrda dasturlash, mulohaza va bir nechta bog‘liq bosqichli vazifalar uchun chiqarilgan modeli. Ishlab chiqaruvchi hujjatlar izchilligi, harakatlarni rejalash va dasturiy ishlab chiqishga eʼtibor beradi. Model multimodal tushunishni ham qo‘llaydi; Ailootʼda mavjud kirish turi tanlangan usulga bog‘liq.

### Nimalarni topshirish mumkin

- Katta texnik topshiriqni o‘qish, bog‘liqliklarni ajratish va amalga oshirish rejasini tayyorlash.
- Kodni tahlil qilib, xatoning mumkin bo‘lgan sababini tushuntirish va tekshirish bilan tuzatish variantini taklif etish.
- Bir nechta hujjatni taqqoslash, umumiy talablarni yig‘ish va asl maʼlumotlardagi tafovutlarni belgilash.
- Yagona tuzilmali yo‘riqnoma, tahliliy yozuv yoki hisobot qoralamasini tayyorlash.

Rasmiy materiallarda uzun ishlab chiqish ketma-ketliklari alohida ko‘rilgan: manba kodini tushunish, o‘zgarishni amalga oshirish, xatolarni tuzatish va test bilan tekshirish. Matnli muloqotda buni bosqichma-bosqich tashkil etish mumkin: avval reja, keyin aniq o‘zgarish, so‘ng izoh va tekshiruv mezonlarini so‘rash.

### Matn va tasvirlar

Standardʼda tasvirlarni matnli savol bilan birga Chat Completions va Responses orqali yuborish mumkin. Masalan, skrinshot mazmunini tahlil qilish, ko‘rinadigan elementni muammo tavsifi bilan bog‘lash yoki tasvirdagi maʼlumotni matnli xulosaga qo‘shishni so‘rash mumkin. Tasvirning qaysi qismi muhim va qanday natija kerakligini belgilang.

Ultraʼda va bu kartochkaning Geminiʼga mos usulida matnli kirish ishlatiladi. Barcha variantlar matn: izoh, harakatlar ro‘yxati, tahlil yoki kod qaytaradi. Hujjatlarni taqqoslash va hisobot tayyorlashda natija tuzilishini oldindan belgilab, materialdagi maʼlumotlarni taklif etilgan xulosalardan ajratishni so‘rash qulay.

### Mulohaza va uzun kontekst

MiniMax M3.1 Flash yakuniy javobdan avval mulohaza yuritadi. Ishlab chiqaruvchi hujjatlarida lowʼdan maxʼgacha chuqurlik darajalari bor; model mulohazani yoqilgan holda saqlaydi. Yakuniy javob shaklini alohida bering: batafsil ichki tahlil va foydalanuvchiga uzun matn yozish turli talablardir.

Standardʼda kontekst oynasi 1 000 000 tokengacha. U tanlangan so‘rov doirasida uzun matnlar, kod va muhokama tarixi bilan ishlash imkonini beradi. Manba nomlari, ularning tartibi va kerakli savollarni bering; katta natija uchun vazifani aniq bosqichlarga bo‘ling va keyingi xabarlarda oraliq qarorlarni saqlang.

### Ailoot API orqali mavjud

Kirish

`text`, `image`

Chiqish

`text`

Kontekst

1 000 000 *token*

Maks. javob

524 288 *token*

Kirish

0,00015 US$ */ 1K*

Chiqish

0,0006 US$ */ 1K*

Keshdan o‘qish

≈0,000015 US$ */ 1K*

Keshga yozish

0,0003 US$ */ 1K*

Keshga yozish, 5 daqiqa

0,0003 US$ */ 1K tokens*

Kirish

`text`, `image`

Chiqish

`text`

Kontekst

1 000 000 *token*

Maks. javob

524 288 *token*

Kirish

0,00015 US$ */ 1K*

Chiqish

0,0006 US$ */ 1K*

Keshdan o‘qish

≈0,000015 US$ */ 1K*

Keshga yozish

0,0003 US$ */ 1K*

Keshga yozish, 5 daqiqa

0,0003 US$ */ 1K tokens*

Kirish

`text`

Chiqish

`text`

Kontekst

1 000 000 *token*

Maks. javob

524 288 *token*

Kirish

0,00015 US$ */ 1K*

Chiqish

0,0006 US$ */ 1K*

Keshdan o‘qish

≈0,000015 US$ */ 1K*

Keshga yozish

0,0003 US$ */ 1K*

Keshga yozish, 5 daqiqa

0,0003 US$ */ 1K tokens*

Kirish

`text`

Chiqish

`text`

Kontekst

968 576 *token*

Maks. javob

80 000 *token*

Kirish

0,0003 US$ */ 1K*

Chiqish

0,0012 US$ */ 1K*

Keshdan o‘qish

≈0,00003 US$ */ 1K*

Keshga yozish

≈0,000036 US$ */ 1K*

Keshga yozish, 5 daqiqa

≈0,000036 US$ */ 1K tokens*

Kirish

`text`

Chiqish

`text`

Kontekst

968 576 *token*

Maks. javob

80 000 *token*

Kirish

0,0003 US$ */ 1K*

Chiqish

0,0012 US$ */ 1K*

Keshdan o‘qish

≈0,00003 US$ */ 1K*

Keshga yozish

≈0,000036 US$ */ 1K*

Keshga yozish, 5 daqiqa

≈0,000036 US$ */ 1K tokens*

Kirish

`text`

Chiqish

`text`

Kontekst

968 576 *token*

Maks. javob

80 000 *token*

Kirish

0,0003 US$ */ 1K*

Chiqish

0,0012 US$ */ 1K*

Keshdan o‘qish

≈0,00003 US$ */ 1K*

Keshga yozish

≈0,000036 US$ */ 1K*

Keshga yozish, 5 daqiqa

≈0,000036 US$ */ 1K tokens*

Kirish

`text`

Chiqish

`text`

Kontekst

Katalogda ko‘rsatilmagan

Maks. javob

Katalogda ko‘rsatilmagan

Kirish

0,0003 US$ */ 1K*

Chiqish

0,0012 US$ */ 1K*

Keshdan o‘qish

≈0,00003 US$ */ 1K*

Kirish

`text`

Chiqish

`text`

Kontekst

Katalogda ko‘rsatilmagan

Maks. javob

Katalogda ko‘rsatilmagan

Kirish

0,0003 US$ */ 1K*

Chiqish

0,0012 US$ */ 1K*

Keshdan o‘qish

≈0,00003 US$ */ 1K*

Kirish

`text`

Chiqish

`text`

Kontekst

Katalogda ko‘rsatilmagan

Maks. javob

Katalogda ko‘rsatilmagan

Kirish

0,0003 US$ */ 1K*

Chiqish

0,0012 US$ */ 1K*

Keshdan o‘qish

≈0,00003 US$ */ 1K*

Kirish

`text`

Chiqish

`text`

Kontekst

Katalogda ko‘rsatilmagan

Maks. javob

Katalogda ko‘rsatilmagan

Kirish

0,0003 US$ */ 1K*

Chiqish

0,0012 US$ */ 1K*

Keshdan o‘qish

≈0,00003 US$ */ 1K*

`minimax/minimax-m3.1-flash` · JSON

```
{"about":"MiniMax M3.1 Flash — MiniMaxʼning 2026-yil 19-oktabrda dasturlash, mulohaza va bir nechta bog‘liq bosqichli vazifalar uchun chiqarilgan modeli. Ishlab chiqaruvchi hujjatlar izchilligi, harakatlarni rejalash va dasturiy ishlab chiqishga eʼtibor beradi. Model multimodal tushunishni ham qo‘llaydi; Ailootʼda mavjud kirish turi tanlangan usulga bog‘liq.\n\n### Nimalarni topshirish mumkin\n\n- Katta texnik topshiriqni o‘qish, bog‘liqliklarni ajratish va amalga oshirish rejasini tayyorlash.\n- Kodni tahlil qilib, xatoning mumkin bo‘lgan sababini tushuntirish va tekshirish bilan tuzatish variantini taklif etish.\n- Bir nechta hujjatni taqqoslash, umumiy talablarni yig‘ish va asl maʼlumotlardagi tafovutlarni belgilash.\n- Yagona tuzilmali yo‘riqnoma, tahliliy yozuv yoki hisobot qoralamasini tayyorlash.\n\nRasmiy materiallarda uzun ishlab chiqish ketma-ketliklari alohida ko‘rilgan: manba kodini tushunish, o‘zgarishni amalga oshirish, xatolarni tuzatish va test bilan tekshirish. Matnli muloqotda buni bosqichma-bosqich tashkil etish mumkin: avval reja, keyin aniq o‘zgarish, so‘ng izoh va tekshiruv mezonlarini so‘rash.\n\n### Matn va tasvirlar\n\nStandardʼda tasvirlarni matnli savol bilan birga Chat Completions va Responses orqali yuborish mumkin. Masalan, skrinshot mazmunini tahlil qilish, ko‘rinadigan elementni muammo tavsifi bilan bog‘lash yoki tasvirdagi maʼlumotni matnli xulosaga qo‘shishni so‘rash mumkin. Tasvirning qaysi qismi muhim va qanday natija kerakligini belgilang.\n\nUltraʼda va bu kartochkaning Geminiʼga mos usulida matnli kirish ishlatiladi. Barcha variantlar matn: izoh, harakatlar ro‘yxati, tahlil yoki kod qaytaradi. Hujjatlarni taqqoslash va hisobot tayyorlashda natija tuzilishini oldindan belgilab, materialdagi maʼlumotlarni taklif etilgan xulosalardan ajratishni so‘rash qulay.\n\n### Mulohaza va uzun kontekst\n\nMiniMax M3.1 Flash yakuniy javobdan avval mulohaza yuritadi. Ishlab chiqaruvchi hujjatlarida lowʼdan maxʼgacha chuqurlik darajalari bor; model mulohazani yoqilgan holda saqlaydi. Yakuniy javob shaklini alohida bering: batafsil ichki tahlil va foydalanuvchiga uzun matn yozish turli talablardir.\n\nStandardʼda kontekst oynasi 1 000 000 tokengacha. U tanlangan so‘rov doirasida uzun matnlar, kod va muhokama tarixi bilan ishlash imkonini beradi. Manba nomlari, ularning tartibi va kerakli savollarni bering; katta natija uchun vazifani aniq bosqichlarga bo‘ling va keyingi xabarlarda oraliq qarorlarni saqlang.","alias_of":null,"aliases":["MiniMax-M3.1-Flash"],"author":"MiniMax","canonical_model":"minimax/minimax-m3.1-flash","ctx":1000000,"formats":["chat","gemini","messages","responses"],"id":"minimax/minimax-m3.1-flash","input":["image","text"],"kind":"text","max_out":524288,"methods":[{"cache_read":0.015,"cache_write":0.3,"cache_write_1h":null,"cache_write_5m":0.3,"conditional_meter":null,"ctx":1000000,"family":"openai","fast_multiplier":null,"flex_multiplier":null,"fmt":"responses","http":"POST","img_in":null,"img_out":null,"in":0.15,"input":["text","image"],"label":"OpenAI Responses","max_out":524288,"max_tool_calls":null,"out":0.6,"output":["text"],"path":"/v1/responses","request_model_id":"MiniMax-M3.1-Flash","route_label":"Core","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.015,"cache_write":0.3,"cache_write_1h":null,"cache_write_5m":0.3,"conditional_meter":null,"ctx":1000000,"family":"openai","fast_multiplier":null,"flex_multiplier":null,"fmt":"chat","http":"POST","img_in":null,"img_out":null,"in":0.15,"input":["text","image"],"label":"OpenAI Chat","max_out":524288,"max_tool_calls":null,"out":0.6,"output":["text"],"path":"/v1/chat/completions","request_model_id":"MiniMax-M3.1-Flash","route_label":"Core","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.015,"cache_write":0.3,"cache_write_1h":null,"cache_write_5m":0.3,"conditional_meter":null,"ctx":1000000,"family":"gemini","fast_multiplier":null,"flex_multiplier":null,"fmt":"gemini","http":"POST","img_in":null,"img_out":null,"in":0.15,"input":["text"],"label":"Gemini generateContent","max_out":524288,"max_tool_calls":null,"out":0.6,"output":["text"],"path":"/v1beta/models/{model}:generateContent","request_model_id":"MiniMax-M3.1-Flash","route_label":"Core","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.03,"cache_write":0.036,"cache_write_1h":null,"cache_write_5m":0.036,"conditional_meter":null,"ctx":968576,"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":80000,"max_tool_calls":null,"out":1.2,"output":["text"],"path":"/v1/chat/completions","request_model_id":"MiniMax-M3.1-Flash","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.03,"cache_write":0.036,"cache_write_1h":null,"cache_write_5m":0.036,"conditional_meter":null,"ctx":968576,"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":80000,"max_tool_calls":null,"out":1.2,"output":["text"],"path":"/v1/responses","request_model_id":"MiniMax-M3.1-Flash","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.03,"cache_write":0.036,"cache_write_1h":null,"cache_write_5m":0.036,"conditional_meter":null,"ctx":968576,"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":80000,"max_tool_calls":null,"out":1.2,"output":["text"],"path":"/v1beta/models/MiniMax-M3.1-Flash:generateContent","request_model_id":"MiniMax-M3.1-Flash","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.03,"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":1.2,"output":["text"],"path":"/v1/messages","request_model_id":"minimax/minimax-m3.1-flash","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.03,"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":1.2,"output":["text"],"path":"/v1/responses","request_model_id":"minimax/minimax-m3.1-flash","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.03,"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":1.2,"output":["text"],"path":"/v1/chat/completions","request_model_id":"minimax/minimax-m3.1-flash","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.03,"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":1.2,"output":["text"],"path":"/v1beta/models/minimax/minimax-m3.1-flash:generateContent","request_model_id":"minimax/minimax-m3.1-flash","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]}],"model_aliases":[{"canonical_model_id":"minimax/minimax-m3.1-flash","request_model_id":"MiniMax-M3.1-Flash","route_label":"Core"},{"canonical_model_id":"minimax/minimax-m3.1-flash","request_model_id":"MiniMax-M3.1-Flash","route_label":"Ultra"},{"canonical_model_id":"minimax/minimax-m3.1-flash","request_model_id":"minimax/minimax-m3.1-flash","route_label":"Ultra"}],"name":"MiniMax: MiniMax M3.1 Flash","price":{"in":0.15,"in_label":null,"out":0.6,"out_label":null,"sort_in":0.15,"sort_out":0.6,"varies":true},"public_id":"minimax/minimax-m3.1-flash","short":"MiniMax M3.1 Flash hujjat tahlili, kod yozish va ko‘p bosqichli vazifalarni rejalashga yordam beradi; Standardʼda Chat Completions va Responses orqali tasvir ham kiritiladi."}
```

## 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.

## Ailoot · Kompaniya va uning loyihalar portfeli





Ailoot to‘plangan faoliyat tajribasi, keng mijozlar bazasi, barqaror xizmat va doimiy KPI nazoratiga tayanadi.





Kompaniya va uning loyihalar portfeli: millionlab mijozlar; oylik sotuvlar hajmi milliardlarda.





Ailoot bu faoliyat tajribasini mijozlar mahsulotlari, agentlar, ilovalar va avtomatlashtirishlarda AI imkoniyatlariga API orqali kirishni ta’minlashda qo‘llaydi.
