{ "aboutHtml": "

Ming Image 0.1 Design Layer — inclusionAI kompaniyasining yassi dizaynni RGBA qatlamlariga ajratuvchi tasvirdan tasvir modeli. POST /v1/images/generations manzilidagi Images usuli bilan aniq inclusionai/ming-image-0.1-design-layer ID qiymatini tanlang. Uning vazifasi mavjud kompozitsiya va yozma qatlam rejasini olib, qatlamlar uchun alohida tasvir natijalarini qaytarishdir.

input_references orqali aynan bitta namuna tasvirini bering va prompt ichida nimani ajratish kerakligini tasvirlang. Hujjatlashtirilgan namuna ko‘rinishi HTTP(S) tasvir URL manzili yoki base64 ma’lumot URL manzilini qabul qiladi. Foydali qatlam rejasi fon, asosiy buyum va oldingi bezakni ajratishi hamda qaysi ko‘rinadigan elementlar birga bo‘lishini tushuntirishi mumkin. Ajratish tahrirlamoqchi bo‘lgan kompozitsiyaga bog‘lanishi uchun namuna sifatida haqiqiy yassi dizayndan foydalaning.

Modelga bag‘ishlangan profil input_references ni bitta namunaga, n ni esa 1 ga belgilaydi. Bu so‘rov sozlamasi bitta so‘ralgan ajratishni bildiradi; hujjatlashtirilgan model xatti-harakati har bir qatlam uchun bitta tasvir qaytaradi. Birinchi data elementini butun natija deb qabul qilish o‘rniga javobdagi har bir tasvirni saqlang. prompt elementlarning ko‘zlangan guruhlanishini yetkazishi kerak, qaytarilgan qatlamlar esa tekshiriladigan haqiqiy chiqish to‘plamini beradi.

Qo‘llab-quvvatlanadigan output_format variantlari png va webp. Chiqish o‘lchamlari kirish tasviriga mos keladi. Ushbu nashrda aniq size va aspect_ratio qiymatlari rad etiladi, shuning uchun namuna tasvirini kompozitsiyaga kerakli o‘lchamda tayyorlang va bu boshqaruvlarni belgilanmagan holda qoldiring. Aniq tanlash qiymati Design Layer nashrini belgilaydi; uning kirishi mavjud dizayn, chiqishi esa tasvir qatlamlaridan iborat.

Yaratishda to‘liq tasvir javobi ishlatiladi va ushbu modelning alohida profili oqimli yetkazishni qo‘llab-quvvatlamaydi. Har bir qaytarilgan b64_json tasvirini dekodlang yoki har bir qaytarilgan tasvir URL manzilidan faylni oling, saqlashda haqiqiy chiqish formatini saqlang. Qatlamlarni manba tasviri va qatlam rejasi bilan birga saqlang. Mahalliy o‘zgartirishlardan oldin qatlamlar bilan ishlaydigan muharrirda shaffof qismlar, qo‘shni elementlarning ajralishi va qayta yig‘ilgan umumiy kompozitsiyani tekshiring.

Natija rastr tasvir qatlamlari to‘plamidir. U muharrirda qayta joylashtirish, ayrim vizual elementlarni almashtirish yoki keyingi kompozitsiyani qo‘llab-quvvatlashi mumkin; saqlangan manba esa solishtirish uchun mavjud bo‘ladi. Tanlangan ajratish ko‘zlangan tuzatishga foydali bo‘lib qolishi uchun qatlam chegaralarini kesib o‘tuvchi har qanday yozuv va buyum qirralarini tekshiring.

", "aboutText": "Ming Image 0.1 Design Layer — inclusionAI kompaniyasining yassi dizaynni RGBA qatlamlariga ajratuvchi tasvirdan tasvir modeli. POST /v1/images/generations manzilidagi Images usuli bilan aniq inclusionai/ming-image-0.1-design-layer ID qiymatini tanlang. Uning vazifasi mavjud kompozitsiya va yozma qatlam rejasini olib, qatlamlar uchun alohida tasvir natijalarini qaytarishdir.\n\ninput_references orqali aynan bitta namuna tasvirini bering va prompt ichida nimani ajratish kerakligini tasvirlang. Hujjatlashtirilgan namuna ko‘rinishi HTTP(S) tasvir URL manzili yoki base64 ma’lumot URL manzilini qabul qiladi. Foydali qatlam rejasi fon, asosiy buyum va oldingi bezakni ajratishi hamda qaysi ko‘rinadigan elementlar birga bo‘lishini tushuntirishi mumkin. Ajratish tahrirlamoqchi bo‘lgan kompozitsiyaga bog‘lanishi uchun namuna sifatida haqiqiy yassi dizayndan foydalaning.\n\nModelga bag‘ishlangan profil input_references ni bitta namunaga, n ni esa 1 ga belgilaydi. Bu so‘rov sozlamasi bitta so‘ralgan ajratishni bildiradi; hujjatlashtirilgan model xatti-harakati har bir qatlam uchun bitta tasvir qaytaradi. Birinchi data elementini butun natija deb qabul qilish o‘rniga javobdagi har bir tasvirni saqlang. prompt elementlarning ko‘zlangan guruhlanishini yetkazishi kerak, qaytarilgan qatlamlar esa tekshiriladigan haqiqiy chiqish to‘plamini beradi.\n\nQo‘llab-quvvatlanadigan output_format variantlari png va webp. Chiqish o‘lchamlari kirish tasviriga mos keladi. Ushbu nashrda aniq size va aspect_ratio qiymatlari rad etiladi, shuning uchun namuna tasvirini kompozitsiyaga kerakli o‘lchamda tayyorlang va bu boshqaruvlarni belgilanmagan holda qoldiring. Aniq tanlash qiymati Design Layer nashrini belgilaydi; uning kirishi mavjud dizayn, chiqishi esa tasvir qatlamlaridan iborat.\n\nYaratishda to‘liq tasvir javobi ishlatiladi va ushbu modelning alohida profili oqimli yetkazishni qo‘llab-quvvatlamaydi. Har bir qaytarilgan b64_json tasvirini dekodlang yoki har bir qaytarilgan tasvir URL manzilidan faylni oling, saqlashda haqiqiy chiqish formatini saqlang. Qatlamlarni manba tasviri va qatlam rejasi bilan birga saqlang. Mahalliy o‘zgartirishlardan oldin qatlamlar bilan ishlaydigan muharrirda shaffof qismlar, qo‘shni elementlarning ajralishi va qayta yig‘ilgan umumiy kompozitsiyani tekshiring.\n\nNatija rastr tasvir qatlamlari to‘plamidir. U muharrirda qayta joylashtirish, ayrim vizual elementlarni almashtirish yoki keyingi kompozitsiyani qo‘llab-quvvatlashi mumkin; saqlangan manba esa solishtirish uchun mavjud bo‘ladi. Tanlangan ajratish ko‘zlangan tuzatishga foydali bo‘lib qolishi uchun qatlam chegaralarini kesib o‘tuvchi har qanday yozuv va buyum qirralarini tekshiring.", "editorialOverlay": { "copy_fields": null, "copy_sha256": null, "copy_source": null, "html_sha256": "0c66bf0bfacf3eabfeb81d09b6228375c4be742dd622d08d2a3e0230c9915f7d", "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06", "raw_model_unchanged": true, "schema": "ailoot-native-model-editorial-v1" }, "locale": "uz", "methods": [ { "html": "
•

inclusionAI: Ming Image 0.1 Design Layer

inclusionAI /inclusionai/ming-image-0.1-design-layer

Boshlash

Ming Image 0.1 Design Layer bitta yassi dizayn tasvirini alohida RGBA tasvir qatlamlariga ajratadi. Aynan bitta namuna va ko‘zlangan qatlam rejasini tasvirlovchi prompt bering. Ushbu nashr keyingi kompozitsiya uchun tasvir qatlamlarini qaytaradi, PNG yoki WebP ni qo‘llab-quvvatlaydi va kirish tasvirining o‘lchamlarini saqlaydi.

Qabul qilinadigan kirish ma’lumotlari
Matn · Rasmlar
Natijalar
Rasmlar
Model haqida

Bu tavsif model imkoniyatlarini yoritadi. Ailoot da tanlangan usul uchun mavjud kirish, chiqish va parametrlar quyida keltirilgan.

Ming Image 0.1 Design Layer — inclusionAI kompaniyasining yassi dizaynni RGBA qatlamlariga ajratuvchi tasvirdan tasvir modeli. POST /v1/images/generations manzilidagi Images usuli bilan aniq inclusionai/ming-image-0.1-design-layer ID qiymatini tanlang. Uning vazifasi mavjud kompozitsiya va yozma qatlam rejasini olib, qatlamlar uchun alohida tasvir natijalarini qaytarishdir.

input_references orqali aynan bitta namuna tasvirini bering va prompt ichida nimani ajratish kerakligini tasvirlang. Hujjatlashtirilgan namuna ko‘rinishi HTTP(S) tasvir URL manzili yoki base64 ma’lumot URL manzilini qabul qiladi. Foydali qatlam rejasi fon, asosiy buyum va oldingi bezakni ajratishi hamda qaysi ko‘rinadigan elementlar birga bo‘lishini tushuntirishi mumkin. Ajratish tahrirlamoqchi bo‘lgan kompozitsiyaga bog‘lanishi uchun namuna sifatida haqiqiy yassi dizayndan foydalaning.

Modelga bag‘ishlangan profil input_references ni bitta namunaga, n ni esa 1 ga belgilaydi. Bu so‘rov sozlamasi bitta so‘ralgan ajratishni bildiradi; hujjatlashtirilgan model xatti-harakati har bir qatlam uchun bitta tasvir qaytaradi. Birinchi data elementini butun natija deb qabul qilish o‘rniga javobdagi har bir tasvirni saqlang. prompt elementlarning ko‘zlangan guruhlanishini yetkazishi kerak, qaytarilgan qatlamlar esa tekshiriladigan haqiqiy chiqish to‘plamini beradi.

Qo‘llab-quvvatlanadigan output_format variantlari png va webp. Chiqish o‘lchamlari kirish tasviriga mos keladi. Ushbu nashrda aniq size va aspect_ratio qiymatlari rad etiladi, shuning uchun namuna tasvirini kompozitsiyaga kerakli o‘lchamda tayyorlang va bu boshqaruvlarni belgilanmagan holda qoldiring. Aniq tanlash qiymati Design Layer nashrini belgilaydi; uning kirishi mavjud dizayn, chiqishi esa tasvir qatlamlaridan iborat.

Yaratishda to‘liq tasvir javobi ishlatiladi va ushbu modelning alohida profili oqimli yetkazishni qo‘llab-quvvatlamaydi. Har bir qaytarilgan b64_json tasvirini dekodlang yoki har bir qaytarilgan tasvir URL manzilidan faylni oling, saqlashda haqiqiy chiqish formatini saqlang. Qatlamlarni manba tasviri va qatlam rejasi bilan birga saqlang. Mahalliy o‘zgartirishlardan oldin qatlamlar bilan ishlaydigan muharrirda shaffof qismlar, qo‘shni elementlarning ajralishi va qayta yig‘ilgan umumiy kompozitsiyani tekshiring.

Natija rastr tasvir qatlamlari to‘plamidir. U muharrirda qayta joylashtirish, ayrim vizual elementlarni almashtirish yoki keyingi kompozitsiyani qo‘llab-quvvatlashi mumkin; saqlangan manba esa solishtirish uchun mavjud bo‘ladi. Tanlangan ajratish ko‘zlangan tuzatishga foydali bo‘lib qolishi uchun qatlam chegaralarini kesib o‘tuvchi har qanday yozuv va buyum qirralarini tekshiring.

Ailoot da mavjud · kirish ma’lumotlari va usullar

Ailoot Ultra · Images POST /v1/images/generations
Kirish
text, image
Chiqish
image
Chiqish formati
Rasm fayli
MaydonTurTalabQiymatlar va cheklovlarStandart
MaydonmodelTurstringTalabMajburiyQiymatlar va cheklovlar
inclusionai/ming-image-0.1-design-layer
Standart—
MaydonpromptTurstringTalabMajburiyQiymatlar va cheklovlarStandart—
MaydonstreamTurbooleanTalabIxtiyoriyQiymatlar va cheklovlar
false
Standartfalse
Maydoninput_referencesTurarrayTalabMajburiyQiymatlar va cheklovlarStandart—
MaydonnTurintegerTalabIxtiyoriyQiymatlar va cheklovlar
Eng kam: 1
Eng ko‘p: 1
Standart—
Maydonoutput_formatTurstringTalabIxtiyoriyQiymatlar va cheklovlar
png, webp
Standart—
Usul parametrlari va hayot sikli
ParametrParametr talablari
Parametrcontent_typeParametr talablariapplication/json
ParametrrequiredParametr talablarimodel, prompt, input_references
ParametroptionalParametr talablaristream, n, output_format
Parametrmaterial_typesParametr talablaritext, image
ParametrconditionsParametr talablariUse stream:false or omit stream. The complete buffered JSON result contains all generated images.

Hayot sikli: synchronous_result_then_owned_library

GET /v1/media/assets

GET /v1/media/assets/{asset_id}

Tariflar

Yakuniy to‘lov qanday hisoblanadi

Ko‘rsatilgan tariflar xarajatni generatsiyadan oldin taxminiy hisoblash uchun xizmat qiladi. Yakuniy to‘lov dastlabki generatsiya uchun qayd etilgan xarajat asosida hisoblanadi. Natijaning o‘lchangan davomiyligi va oldindan taxmin qilingan miqdorlar haq undiriladigan yakuniy miqdor hisoblanmaydi.

Tarif ma’lumotlari so‘rov imkoniyatlarini qo‘shmaydi. Qo‘llab-quvvatlanadigan parametrlar tanlangan usulda ko‘rsatilgan.

Tezkor rejim
Ko‘rsatilmagan Tezkor rejim tanlanganda
Flex rejimi
Ko‘rsatilmagan flex rejimi tanlanganda
Maksimal fikrlash darajasi
Ko‘rsatilmagan Maksimal fikrlash darajasi uchun standart (default) tuzatish qo‘llanganda

Taqqoslash uchun taxminiy tariflar

Sozlamalar bo‘yicha narxlar

Har bir to‘lovni ko‘rsatilgan shartlarga moslang. Har bir muqobil sozlamalar to‘plami uchun bitta tarifdan foydalaning.

SozlamaTariflar jadvaliPrognoz miqdoriTo‘lov
SozlamaTokenlar uchun bazaviy tariflarTariflar jadvaliAsosiy tarifPrognoz miqdori—To‘lov
Kirish · Kirish tokenlari · Faqat taqqoslash uchun taxmin — / 1K token
Chiqish · Chiqish tokenlari · Faqat taqqoslash uchun taxmin — / 1K token
Kirish · Keshdan o‘qish · Faqat taqqoslash uchun taxmin — / 1K token
Kirish · Keshga yozish · Faqat taqqoslash uchun taxmin — / 1K token
Kirish · Keshga yozish, 1 soat · Faqat taqqoslash uchun taxmin — / 1K token
SozlamaEstimated generation costTariflar jadvali—Prognoz miqdoribir generatsiya uchun taxminTo‘lov
Kirish · Yaratishning taxminiy narxi · Faqat taqqoslash uchun taxmin $0.98304 yaratishdan oldingi taxmin

This estimate is not an additional charge or a fixed rate for the completed generation.

Ailoot so‘rovdan oldin taxminiy summani band qiladi. Natijadan keyin o‘lchangan sarf asosidagi yakuniy to‘lovni yechadi. Oqimli javob bo‘yicha yakuniy hisob-kitob yakuniy sarf yozuviga asoslanadi. Summani band qilish va to‘lovni hisoblash tartibi →

So‘rov namunalari

Ailoot Ultra · Images

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\nexport AILOOT_API_KEY\n: "${AILOOT_IMAGE_URL:?Set an actual customer material or documented value}"\nexport AILOOT_IMAGE_URL\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "inclusionai/ming-image-0.1-design-layer", "prompt": "A calm studio product photograph with a plain background.", "input_references": [{"type": "image_url", "image_url": {"url": "YOUR_ACCESSIBLE_IMAGE_URL"}}]}')\np['input_references'][0]['image_url']['url']=os.environ['AILOOT_IMAGE_URL']\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/images/generations \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\n# Submit once. Retain the complete result, original identifiers and every response header.\n

Natijalarni olish va saqlash

Ailoot Ultra · Images

Har bir qaytarilgan rasmni yuklab oling yoki uning Base64 kontentini saqlang

Barcha tayyor natijalarni saqlash

Har bir tayyor rasmni saqlang; har bir qaytarilgan URL dan kontentni oling yoki uning Base64 kontentini dekodlang.

Retain every returned image and field. Use owned content_url values and actual asset_id records; refresh the same asset when a link expires.

Asl javobni tekshirish kerak bo‘lsa

Preserve the original response, headers and X-Client-Request-ID. An uncertain outcome does not authorize another creation.

Taxalluslar

Model taxalluslari

Ailoot Ultra inclusionai/ming-image-0.1-design-layer

Usul yo‘llari taxalluslari

Yuqorida ko‘rsatilgan usul yo‘llaridan foydalaning.

Chaqirish uchun tegishli ID lar

inclusionai/ming-image-0.1-design-layer

", "method_identity": { "effective_request_model_id": "inclusionai/ming-image-0.1-design-layer", "fmt": "images", "http": "POST", "path": "/v1/images/generations", "request_model_id": "inclusionai/ming-image-0.1-design-layer", "route_label": "Ultra" }, "method_key": "Ultra|images|/v1/images/generations|inclusionai%2Fming-image-0.1-design-layer", "ordinal": 0, "rawMethod": { "available": null, "billing_basis": { "basis": "original_invoice_usd", "description": "The displayed rates estimate the cost before generation. The final charge is calculated from the cost recorded for the original generation. Measured output duration and forecast quantities are not the final billable quantity.", "forecast_quantity_is_estimate": true, "physical_output_is_billable_quantity": false, "version": "original_invoice_usd_v1" }, "cache_read": null, "cache_write": null, "cache_write_1h": null, "contract": { "data": { "all_results": "Retain the complete response, all actual results, original identifiers, usage and response headers.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "example_body": { "input_references": [ { "image_url": { "url": "YOUR_ACCESSIBLE_IMAGE_URL" }, "type": "image_url" } ], "model": "inclusionai/ming-image-0.1-design-layer", "prompt": "A calm studio product photograph with a plain background." }, "lifecycle": { "assets": [ { "http": "GET", "path": "/v1/media/assets", "query": { "cursor": "actual returned next_cursor, when present", "family": "image" } }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "cancel_endpoint": null, "create": { "http": "POST", "path": "/v1/images/generations" }, "mode": "synchronous_result_then_owned_library", "operation_id_is_not_task_id": true, "owned_content": { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "Use the exact returned content_url. Refresh an expired link by reading the same existing asset." }, "status": [], "unknown": "Preserve the original response, headers and X-Client-Request-ID. An uncertain outcome does not authorize another creation.", "unknown_no_replay": true }, "outputs": { "all_results": "Retain every returned image and field. Use owned content_url values and actual asset_id records; refresh the same asset when a link expires.", "family": "image", "format": "JSON with all URL or base64 outputs" }, "parameters": [ { "default_known": false, "enum": [ "inclusionai/ming-image-0.1-design-layer" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "default_known": false, "enum_known": false, "name": "prompt", "required": true, "type": "string" }, { "default": false, "default_known": true, "enum": [ false ], "enum_known": true, "name": "stream", "required": false, "type": "boolean" }, { "default_known": false, "enum_known": false, "items": { "properties": { "image_url": { "properties": { "url": { "type": "string" } }, "required": [ "url" ], "type": "object" }, "type": { "const": "image_url" } }, "required": [ "type", "image_url" ], "type": "object" }, "maxItems": 1, "minItems": 1, "name": "input_references", "required": true, "type": "array" }, { "default_known": false, "enum_known": false, "maximum": 1, "minimum": 1, "name": "n", "required": false, "type": "integer" }, { "default_known": false, "enum": [ "png", "webp" ], "enum_known": true, "name": "output_format", "required": false, "type": "string" } ], "request_schema": { "additionalProperties": true, "properties": { "input_references": { "items": { "properties": { "image_url": { "properties": { "url": { "type": "string" } }, "required": [ "url" ], "type": "object" }, "type": { "const": "image_url" } }, "required": [ "type", "image_url" ], "type": "object" }, "maxItems": 1, "minItems": 1, "type": "array" }, "model": { "enum": [ "inclusionai/ming-image-0.1-design-layer" ], "type": "string" }, "n": { "maximum": 1, "minimum": 1, "type": "integer" }, "output_format": { "enum": [ "png", "webp" ], "type": "string" }, "prompt": { "type": "string" }, "stream": { "default": false, "enum": [ false ], "type": "boolean" } }, "required": [ "model", "prompt", "input_references" ], "type": "object" }, "schema_template": { "body": { "input_references": [ { "image_url": { "url": "YOUR_ACCESSIBLE_IMAGE_URL" }, "type": "image_url" } ], "model": "inclusionai/ming-image-0.1-design-layer", "prompt": "A calm studio product photograph with a plain background." }, "content_type": "application/json" } }, "input": { "conditions": [ "Use stream:false or omit stream. The complete buffered JSON result contains all generated images." ], "content_type": "application/json", "material_types": [ "text", "image" ], "optional": [ "stream", "n", "output_format" ], "required": [ "model", "prompt", "input_references" ] }, "lifecycle": { "assets": [ { "http": "GET", "path": "/v1/media/assets", "query": { "cursor": "actual returned next_cursor, when present", "family": "image" } }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "cancel_endpoint": null, "create": { "http": "POST", "path": "/v1/images/generations" }, "mode": "synchronous_result_then_owned_library", "operation_id_is_not_task_id": true, "owned_content": { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "Use the exact returned content_url. Refresh an expired link by reading the same existing asset." }, "status": [], "unknown": "Preserve the original response, headers and X-Client-Request-ID. An uncertain outcome does not authorize another creation.", "unknown_no_replay": true }, "method": { "http": "POST", "path": "/v1/images/generations" }, "method_aliases": [], "output": { "all_results": "Retain every returned image and field. Use owned content_url values and actual asset_id records; refresh the same asset when a link expires.", "family": "image", "format": "JSON with all URL or base64 outputs" } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "basis": "This estimate is not an additional charge or a fixed rate for the completed generation.", "dimensions": { "forecast_quantity": "one generation estimate" }, "label": "Estimated generation cost", "units": [ { "amount": "0.98304", "amount_unit": "usd_per_exact_native_unit", "billing_input": false, "estimate_only": true, "key": "forecast_usd", "label": "Estimated generation cost", "native_amount_usd_per_unit": "0.98304", "native_quantity": 1, "public_unit_label": "estimate before generation", "quantity": 1, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "request_estimate" } ] } ], "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nexport AILOOT_API_KEY\n: \"${AILOOT_IMAGE_URL:?Set an actual customer material or documented value}\"\nexport AILOOT_IMAGE_URL\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"inclusionai/ming-image-0.1-design-layer\", \"prompt\": \"A calm studio product photograph with a plain background.\", \"input_references\": [{\"type\": \"image_url\", \"image_url\": {\"url\": \"YOUR_ACCESSIBLE_IMAGE_URL\"}}]}')\np['input_references'][0]['image_url']['url']=os.environ['AILOOT_IMAGE_URL']\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/images/generations \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\n# Submit once. Retain the complete result, original identifiers and every response header.\n", "label": "curl · create once and retain the complete result", "language": "bash" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "images", "http": "POST", "img_in": null, "img_out": null, "in": null, "input": [ "text", "image" ], "label": "Images", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "out": null, "output": [ "image" ], "path": "/v1/images/generations", "price_conditions": [ { "label": "Fast mode", "value": "Not specified", "when": "When fast mode is selected" }, { "label": "Flex mode", "value": "Not specified", "when": "When flex mode is selected" }, { "label": "Maximum reasoning effort", "value": "Not specified", "when": "When maximum reasoning effort uses the default adjustment" } ], "pricing": { "billing_mode": "original_invoice_usd", "cache_read_price": null, "cache_write_1h_price": null, "cache_write_price": null, "fast_multiplier": null, "flex_multiplier": null, "image_input_price": null, "image_output_price": null, "input_price": null, "intervals": null, "max_reasoning_effort_multiplier": null, "output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "basis": "This estimate is not an additional charge or a fixed rate for the completed generation.", "dimensions": { "forecast_quantity": "one generation estimate" }, "label": "Estimated generation cost", "units": [ { "amount": "0.98304", "amount_unit": "usd_per_exact_native_unit", "billing_input": false, "estimate_only": true, "key": "forecast_usd", "label": "Estimated generation cost", "native_amount_usd_per_unit": "0.98304", "native_quantity": 1, "public_unit_label": "estimate before generation", "quantity": 1, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "request_estimate" } ] } ], "request_model_id": "inclusionai/ming-image-0.1-design-layer", "route_label": "Ultra", "status_reads": [], "tiers": [], "unit": "image", "units": [ { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" }, { "amount": "0.98304", "amount_unit": "usd_per_exact_native_unit", "billing_input": false, "estimate_only": true, "key": "forecast_usd", "label": "Estimated generation cost", "native_amount_usd_per_unit": "0.98304", "native_quantity": 1, "public_unit_label": "estimate before generation", "quantity": 1, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "request_estimate" } ] } } ], "model_id": "inclusionai/ming-image-0.1-design-layer", "nativeProvenance": { "input_facts_canonical_sha256": "3aa448b6a1962388fd3ea3203219ac4a0188f4ff999b417198b74e02084c6eee", "input_html_sha256": "4ecf1f227fa4a44ba21eb596ba0680178a9b3a6c24bb9bd321551b9d5e9b8ae3", "private_audit_sha256": "d44c11087ac20b865be8858d569482bc8a1af1dff0aa49c868a383d18633b7c2", "role": "historical-normalized-input-audit-hashes", "schema": "ailoot-native-model-provenance-v2" }, "page": { "canonical": "https://ailoot.ai/models/uz/inclusionai-ming-image-0-1-design-layer/", "description": "Ming Image 0.1 Design Layer bitta yassi dizayn tasvirini alohida RGBA tasvir qatlamlariga ajratadi. Aynan bitta namuna va ko‘zlangan qatlam rejasini tasvirlovchi prompt bering. Ushbu nashr keyingi kompozitsiya uchun tasvir qatlamlarini qaytaradi, PNG yoki WebP ni qo‘llab-quvvatlaydi va kirish tasvirining o‘lchamlarini saqlaydi.", "locale": "uz", "md_url": "https://ailoot.ai/models/uz/inclusionai-ming-image-0-1-design-layer/index.md", "title": "inclusionAI: Ming Image 0.1 Design Layer — Ailoot", "url": "https://ailoot.ai/models/uz/inclusionai-ming-image-0-1-design-layer/" }, "rawModel": { "about": "Ming Image 0.1 Design Layer — inclusionAI kompaniyasining yassi dizaynni RGBA qatlamlariga ajratuvchi tasvirdan tasvir modeli. POST /v1/images/generations manzilidagi Images usuli bilan aniq inclusionai/ming-image-0.1-design-layer ID qiymatini tanlang. Uning vazifasi mavjud kompozitsiya va yozma qatlam rejasini olib, qatlamlar uchun alohida tasvir natijalarini qaytarishdir.\n\ninput_references orqali aynan bitta namuna tasvirini bering va prompt ichida nimani ajratish kerakligini tasvirlang. Hujjatlashtirilgan namuna ko‘rinishi HTTP(S) tasvir URL manzili yoki base64 ma’lumot URL manzilini qabul qiladi. Foydali qatlam rejasi fon, asosiy buyum va oldingi bezakni ajratishi hamda qaysi ko‘rinadigan elementlar birga bo‘lishini tushuntirishi mumkin. Ajratish tahrirlamoqchi bo‘lgan kompozitsiyaga bog‘lanishi uchun namuna sifatida haqiqiy yassi dizayndan foydalaning.\n\nModelga bag‘ishlangan profil input_references ni bitta namunaga, n ni esa 1 ga belgilaydi. Bu so‘rov sozlamasi bitta so‘ralgan ajratishni bildiradi; hujjatlashtirilgan model xatti-harakati har bir qatlam uchun bitta tasvir qaytaradi. Birinchi data elementini butun natija deb qabul qilish o‘rniga javobdagi har bir tasvirni saqlang. prompt elementlarning ko‘zlangan guruhlanishini yetkazishi kerak, qaytarilgan qatlamlar esa tekshiriladigan haqiqiy chiqish to‘plamini beradi.\n\nQo‘llab-quvvatlanadigan output_format variantlari png va webp. Chiqish o‘lchamlari kirish tasviriga mos keladi. Ushbu nashrda aniq size va aspect_ratio qiymatlari rad etiladi, shuning uchun namuna tasvirini kompozitsiyaga kerakli o‘lchamda tayyorlang va bu boshqaruvlarni belgilanmagan holda qoldiring. Aniq tanlash qiymati Design Layer nashrini belgilaydi; uning kirishi mavjud dizayn, chiqishi esa tasvir qatlamlaridan iborat.\n\nYaratishda to‘liq tasvir javobi ishlatiladi va ushbu modelning alohida profili oqimli yetkazishni qo‘llab-quvvatlamaydi. Har bir qaytarilgan b64_json tasvirini dekodlang yoki har bir qaytarilgan tasvir URL manzilidan faylni oling, saqlashda haqiqiy chiqish formatini saqlang. Qatlamlarni manba tasviri va qatlam rejasi bilan birga saqlang. Mahalliy o‘zgartirishlardan oldin qatlamlar bilan ishlaydigan muharrirda shaffof qismlar, qo‘shni elementlarning ajralishi va qayta yig‘ilgan umumiy kompozitsiyani tekshiring.\n\nNatija rastr tasvir qatlamlari to‘plamidir. U muharrirda qayta joylashtirish, ayrim vizual elementlarni almashtirish yoki keyingi kompozitsiyani qo‘llab-quvvatlashi mumkin; saqlangan manba esa solishtirish uchun mavjud bo‘ladi. Tanlangan ajratish ko‘zlangan tuzatishga foydali bo‘lib qolishi uchun qatlam chegaralarini kesib o‘tuvchi har qanday yozuv va buyum qirralarini tekshiring.", "alias_of": null, "aliases": [], "author": "inclusionAI", "ctx": null, "formats": [ "images" ], "id": "inclusionai/ming-image-0.1-design-layer", "input": [ "image", "text" ], "kind": "image", "max_out": null, "methods": [ { "available": null, "billing_basis": { "basis": "original_invoice_usd", "description": "The displayed rates estimate the cost before generation. The final charge is calculated from the cost recorded for the original generation. Measured output duration and forecast quantities are not the final billable quantity.", "forecast_quantity_is_estimate": true, "physical_output_is_billable_quantity": false, "version": "original_invoice_usd_v1" }, "cache_read": null, "cache_write": null, "cache_write_1h": null, "contract": { "data": { "all_results": "Retain the complete response, all actual results, original identifiers, usage and response headers.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "example_body": { "input_references": [ { "image_url": { "url": "YOUR_ACCESSIBLE_IMAGE_URL" }, "type": "image_url" } ], "model": "inclusionai/ming-image-0.1-design-layer", "prompt": "A calm studio product photograph with a plain background." }, "lifecycle": { "assets": [ { "http": "GET", "path": "/v1/media/assets", "query": { "cursor": "actual returned next_cursor, when present", "family": "image" } }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "cancel_endpoint": null, "create": { "http": "POST", "path": "/v1/images/generations" }, "mode": "synchronous_result_then_owned_library", "operation_id_is_not_task_id": true, "owned_content": { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "Use the exact returned content_url. Refresh an expired link by reading the same existing asset." }, "status": [], "unknown": "Preserve the original response, headers and X-Client-Request-ID. An uncertain outcome does not authorize another creation.", "unknown_no_replay": true }, "outputs": { "all_results": "Retain every returned image and field. Use owned content_url values and actual asset_id records; refresh the same asset when a link expires.", "family": "image", "format": "JSON with all URL or base64 outputs" }, "parameters": [ { "default_known": false, "enum": [ "inclusionai/ming-image-0.1-design-layer" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "default_known": false, "enum_known": false, "name": "prompt", "required": true, "type": "string" }, { "default": false, "default_known": true, "enum": [ false ], "enum_known": true, "name": "stream", "required": false, "type": "boolean" }, { "default_known": false, "enum_known": false, "items": { "properties": { "image_url": { "properties": { "url": { "type": "string" } }, "required": [ "url" ], "type": "object" }, "type": { "const": "image_url" } }, "required": [ "type", "image_url" ], "type": "object" }, "maxItems": 1, "minItems": 1, "name": "input_references", "required": true, "type": "array" }, { "default_known": false, "enum_known": false, "maximum": 1, "minimum": 1, "name": "n", "required": false, "type": "integer" }, { "default_known": false, "enum": [ "png", "webp" ], "enum_known": true, "name": "output_format", "required": false, "type": "string" } ], "request_schema": { "additionalProperties": true, "properties": { "input_references": { "items": { "properties": { "image_url": { "properties": { "url": { "type": "string" } }, "required": [ "url" ], "type": "object" }, "type": { "const": "image_url" } }, "required": [ "type", "image_url" ], "type": "object" }, "maxItems": 1, "minItems": 1, "type": "array" }, "model": { "enum": [ "inclusionai/ming-image-0.1-design-layer" ], "type": "string" }, "n": { "maximum": 1, "minimum": 1, "type": "integer" }, "output_format": { "enum": [ "png", "webp" ], "type": "string" }, "prompt": { "type": "string" }, "stream": { "default": false, "enum": [ false ], "type": "boolean" } }, "required": [ "model", "prompt", "input_references" ], "type": "object" }, "schema_template": { "body": { "input_references": [ { "image_url": { "url": "YOUR_ACCESSIBLE_IMAGE_URL" }, "type": "image_url" } ], "model": "inclusionai/ming-image-0.1-design-layer", "prompt": "A calm studio product photograph with a plain background." }, "content_type": "application/json" } }, "input": { "conditions": [ "Use stream:false or omit stream. The complete buffered JSON result contains all generated images." ], "content_type": "application/json", "material_types": [ "text", "image" ], "optional": [ "stream", "n", "output_format" ], "required": [ "model", "prompt", "input_references" ] }, "lifecycle": { "assets": [ { "http": "GET", "path": "/v1/media/assets", "query": { "cursor": "actual returned next_cursor, when present", "family": "image" } }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "cancel_endpoint": null, "create": { "http": "POST", "path": "/v1/images/generations" }, "mode": "synchronous_result_then_owned_library", "operation_id_is_not_task_id": true, "owned_content": { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "Use the exact returned content_url. Refresh an expired link by reading the same existing asset." }, "status": [], "unknown": "Preserve the original response, headers and X-Client-Request-ID. An uncertain outcome does not authorize another creation.", "unknown_no_replay": true }, "method": { "http": "POST", "path": "/v1/images/generations" }, "method_aliases": [], "output": { "all_results": "Retain every returned image and field. Use owned content_url values and actual asset_id records; refresh the same asset when a link expires.", "family": "image", "format": "JSON with all URL or base64 outputs" } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "basis": "This estimate is not an additional charge or a fixed rate for the completed generation.", "dimensions": { "forecast_quantity": "one generation estimate" }, "label": "Estimated generation cost", "units": [ { "amount": "0.98304", "amount_unit": "usd_per_exact_native_unit", "billing_input": false, "estimate_only": true, "key": "forecast_usd", "label": "Estimated generation cost", "native_amount_usd_per_unit": "0.98304", "native_quantity": 1, "public_unit_label": "estimate before generation", "quantity": 1, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "request_estimate" } ] } ], "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nexport AILOOT_API_KEY\n: \"${AILOOT_IMAGE_URL:?Set an actual customer material or documented value}\"\nexport AILOOT_IMAGE_URL\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"inclusionai/ming-image-0.1-design-layer\", \"prompt\": \"A calm studio product photograph with a plain background.\", \"input_references\": [{\"type\": \"image_url\", \"image_url\": {\"url\": \"YOUR_ACCESSIBLE_IMAGE_URL\"}}]}')\np['input_references'][0]['image_url']['url']=os.environ['AILOOT_IMAGE_URL']\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/images/generations \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\n# Submit once. Retain the complete result, original identifiers and every response header.\n", "label": "curl · create once and retain the complete result", "language": "bash" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "images", "http": "POST", "img_in": null, "img_out": null, "in": null, "input": [ "text", "image" ], "label": "Images", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "out": null, "output": [ "image" ], "path": "/v1/images/generations", "price_conditions": [ { "label": "Fast mode", "value": "Not specified", "when": "When fast mode is selected" }, { "label": "Flex mode", "value": "Not specified", "when": "When flex mode is selected" }, { "label": "Maximum reasoning effort", "value": "Not specified", "when": "When maximum reasoning effort uses the default adjustment" } ], "pricing": { "billing_mode": "original_invoice_usd", "cache_read_price": null, "cache_write_1h_price": null, "cache_write_price": null, "fast_multiplier": null, "flex_multiplier": null, "image_input_price": null, "image_output_price": null, "input_price": null, "intervals": null, "max_reasoning_effort_multiplier": null, "output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "basis": "This estimate is not an additional charge or a fixed rate for the completed generation.", "dimensions": { "forecast_quantity": "one generation estimate" }, "label": "Estimated generation cost", "units": [ { "amount": "0.98304", "amount_unit": "usd_per_exact_native_unit", "billing_input": false, "estimate_only": true, "key": "forecast_usd", "label": "Estimated generation cost", "native_amount_usd_per_unit": "0.98304", "native_quantity": 1, "public_unit_label": "estimate before generation", "quantity": 1, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "request_estimate" } ] } ], "request_model_id": "inclusionai/ming-image-0.1-design-layer", "route_label": "Ultra", "status_reads": [], "tiers": [], "unit": "image", "units": [ { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" }, { "amount": "0.98304", "amount_unit": "usd_per_exact_native_unit", "billing_input": false, "estimate_only": true, "key": "forecast_usd", "label": "Estimated generation cost", "native_amount_usd_per_unit": "0.98304", "native_quantity": 1, "public_unit_label": "estimate before generation", "quantity": 1, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "request_estimate" } ] } ], "model_aliases": [ { "canonical_model_id": "inclusionai/ming-image-0.1-design-layer", "request_model_id": "inclusionai/ming-image-0.1-design-layer", "route_label": "Ultra" } ], "name": "inclusionAI: Ming Image 0.1 Design Layer", "price": { "in": null, "in_label": null, "out": null, "out_label": null, "sort_in": null, "sort_out": null, "varies": true }, "short": "Ming Image 0.1 Design Layer bitta yassi dizayn tasvirini alohida RGBA tasvir qatlamlariga ajratadi. Aynan bitta namuna va ko‘zlangan qatlam rejasini tasvirlovchi prompt bering. Ushbu nashr keyingi kompozitsiya uchun tasvir qatlamlarini qaytaradi, PNG yoki WebP ni qo‘llab-quvvatlaydi va kirish tasvirining o‘lchamlarini saqlaydi." }, "renderer_schema": { "method_order": "Original DTO methods order; every exact route/format/path/caller survives.", "prices": "Original public DTO fields and original native display HTML; no flattened or normalized offers." }, "representation": "exact-public-dto-and-native-renderer-html", "representationNotes": { "current_reference": { "about_json_pointer": "/aboutHtml", "methods": [ { "contract_json_pointer": "/methods/0/rawMethod/contract", "html_json_pointer": "/methods/0/html", "method_ordinal": 0 } ], "role": "current-semantic-reference" }, "raw_input": { "examples_role": "historical-input-not-current-ready-examples", "json_pointers": [ "/rawModel", "/methods/0/rawMethod" ], "role": "historical-owner-input" }, "schema": "ailoot-native-model-representations-v1" }, "schema": "ailoot-static-model-facts-v1", "schema_version": 1, "shortText": "Ming Image 0.1 Design Layer bitta yassi dizayn tasvirini alohida RGBA tasvir qatlamlariga ajratadi. Aynan bitta namuna va ko‘zlangan qatlam rejasini tasvirlovchi prompt bering. Ushbu nashr keyingi kompozitsiya uchun tasvir qatlamlarini qaytaradi, PNG yoki WebP ni qo‘llab-quvvatlaydi va kirish tasvirining o‘lchamlarini saqlaydi.", "source": { "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1", "bridge_map_sha256": "1125275768b9636fc8461bc7da5061239a81ddfe508e2557843ca42c58ab0036", "raw_model_json_sha256": "2e08db75a9781d148e9a6a1bfd182362275d1b4170f9dcf2a507b4ed35a3b39a", "renderer_sha256": "aa8a0fca1bd770c042b64987512b6187fca2067aea3ddc877f68b163d80e7df6" }, "sourceRevision": "8bdd0f933abf3f5023a81e07ba8a2227b79448dfb214c3fe25736ea857444565" }