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Veo 3.1 Fast

Integrar

Id del modelo veo3.1/fast

# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/veo3.1/fast?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Ultra realistic ASMR video of a fresh ripe pineapple being cut into a glass-shaped cylinder. Close-up macro shot, natural kitchen lighting, high detail pineapple texture, visible juice droplets, slow precise knife slicing.\nSound focus: crisp crunchy cutting sound, juicy wet fiber tearing sound, subtle knife sliding on cutting board, natural room ambience, no music, stereo binaural ASMR audio. \n\nVisual detail: yellow golden pineapple flesh, fresh green crown slightly visible on table, wooden cutting board, stainless steel sharp knife, realistic juice splashing slightly when sliced.\nCamera: slow cinematic movement, macro lens, depth of field, focus on knife entering pineapple flesh.\nStyle: hyper realistic, 4K, natural color grading, food photography realism, satisfying ASMR style.",
    "duration": "4s",
    "resolution": "720p",
    "generate_audio": true
  }'

# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"

const API = "https://api.doitong.ru/v1";
const headers = {
  "Authorization": "Bearer " + process.env.DOITONG_API_KEY,
  "Content-Type": "application/json",
};

// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/veo3.1/fast?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "Ultra realistic ASMR video of a fresh ripe pineapple being cut into a glass-shaped cylinder. Close-up macro shot, natural kitchen lighting, high detail pineapple texture, visible juice droplets, slow precise knife slicing.\nSound focus: crisp crunchy cutting sound, juicy wet fiber tearing sound, subtle knife sliding on cutting board, natural room ambience, no music, stereo binaural ASMR audio. \n\nVisual detail: yellow golden pineapple flesh, fresh green crown slightly visible on table, wooden cutting board, stainless steel sharp knife, realistic juice splashing slightly when sliced.\nCamera: slow cinematic movement, macro lens, depth of field, focus on knife entering pineapple flesh.\nStyle: hyper realistic, 4K, natural color grading, food photography realism, satisfying ASMR style.",
    "duration": "4s",
    "resolution": "720p",
    "generate_audio": true
  }),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);

// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
  res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
  request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");

import os
import requests

API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "prompt": "Ultra realistic ASMR video of a fresh ripe pineapple being cut into a glass-shaped cylinder. Close-up macro shot, natural kitchen lighting, high detail pineapple texture, visible juice droplets, slow precise knife slicing.\nSound focus: crisp crunchy cutting sound, juicy wet fiber tearing sound, subtle knife sliding on cutting board, natural room ambience, no music, stereo binaural ASMR audio. \n\nVisual detail: yellow golden pineapple flesh, fresh green crown slightly visible on table, wooden cutting board, stainless steel sharp knife, realistic juice splashing slightly when sliced.\nCamera: slow cinematic movement, macro lens, depth of field, focus on knife entering pineapple flesh.\nStyle: hyper realistic, 4K, natural color grading, food photography realism, satisfying ASMR style.",
    "duration": "4s",
    "resolution": "720p",
    "generate_audio": True,
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/veo3.1/fast", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
    raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])

# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
    request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
    raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])

# 1. Connect once (Claude Code; Cursor, VS Code, Claude Desktop: https://doitong.com/es/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.ru/v1/mcp \
  --header "Authorization: Bearer $DOITONG_API_KEY"

# 2. Your agent calls the "run" tool with:
{
  "model_id": "veo3.1/fast",
  "input": {
    "prompt": "Ultra realistic ASMR video of a fresh ripe pineapple being cut into a glass-shaped cylinder. Close-up macro shot, natural kitchen lighting, high detail pineapple texture, visible juice droplets, slow precise knife slicing.\nSound focus: crisp crunchy cutting sound, juicy wet fiber tearing sound, subtle knife sliding on cutting board, natural room ambience, no music, stereo binaural ASMR audio. \n\nVisual detail: yellow golden pineapple flesh, fresh green crown slightly visible on table, wooden cutting board, stainless steel sharp knife, realistic juice splashing slightly when sliced.\nCamera: slow cinematic movement, macro lens, depth of field, focus on knife entering pineapple flesh.\nStyle: hyper realistic, 4K, natural color grading, food photography realism, satisfying ASMR style.",
    "duration": "4s",
    "resolution": "720p",
    "generate_audio": true
  }
}

Llama al modelo Veo 3.1 Fast (veo3.1/fast) mediante Doitong API. Documentación para agentes: https://doitong.com/es/developers/models/veo3.1/fast.md

POST https://api.doitong.ru/v1/run/veo3.1/fast?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json

{
  "prompt": "Ultra realistic ASMR video of a fresh ripe pineapple being cut into a glass-shaped cylinder. Close-up macro shot, natural kitchen lighting, high detail pineapple texture, visible juice droplets, slow precise knife slicing.\nSound focus: crisp crunchy cutting sound, juicy wet fiber tearing sound, subtle knife sliding on cutting board, natural room ambience, no music, stereo binaural ASMR audio. \n\nVisual detail: yellow golden pineapple flesh, fresh green crown slightly visible on table, wooden cutting board, stainless steel sharp knife, realistic juice splashing slightly when sliced.\nCamera: slow cinematic movement, macro lens, depth of field, focus on knife entering pineapple flesh.\nStyle: hyper realistic, 4K, natural color grading, food photography realism, satisfying ASMR style.",
  "duration": "4s",
  "resolution": "720p",
  "generate_audio": true
}

Si el estado de la respuesta es "queued" o "running", consulta GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 hasta que sea "succeeded"; los archivos están en outputs[].url. POST https://api.doitong.ru/v1/quote/veo3.1/fast con el mismo cuerpo devuelve el precio exacto antes de la ejecución.

Esta solicitud: 0,60 $ 600 créditos de API · ≈ 63,28 ₽ Ejecutar en esta página

Obtener clave de API

Google Texto a vídeo Audio nativoSalida 4KRápido4–8 shasta 4k #fast#dialogue

El Veo 3.1 más rápido y económico para clips de 4 a 8 segundos con sonido.

OpenAPI Markdown

Ejemplos

Salida · ~42 s

IndicaciónUltra realistic ASMR video of a fresh ripe pineapple being cut into a glass-shaped cylinder. Close-up macro shot, natural kitchen lighting, high detail pineapple texture, visible juice droplets, slow precise knife slicing. Sound focus: crisp crunchy cutting sound, juicy wet fiber tearing sound, subtle knife sliding on cutting board, natural room ambience, no music, stereo binaural ASMR audio. Visual detail: yellow golden pineapple flesh, fresh green crown slightly visible on table, wooden cutting board, stainless steel sharp knife, realistic juice splashing slightly when sliced. Camera: slow cinematic movement, macro lens, depth of field, focus on knife entering pineapple flesh. Style: hyper realistic, 4K, natural color grading, food photography realism, satisfying ASMR style.

4s720pgenerate_audio: true0,60 $ · 600 créditos de API

Prompt de @Strength04_X en X

Precio

Precio exacto

desde 0,10 $ / segundo

100 créditos de API / segundo · ≈ 10,55 ₽

8 s ≈ 0,80 $

Esta solicitud: 4 segundos × 0,15 $ 0,60 $ 600 créditos de API · ≈ 63,28 ₽

Ejecutar · 0,60 $

Solo se cobra si tiene éxito; si falla, se reembolsa automáticamente.

duration 4 s

resolution

Reglas de precios

Cuando resolution = 4k y generate_audio = true: 0,35 $ / segundo
Cuando resolution = 4k: 0,30 $ / segundo
Cuando generate_audio = true: 0,15 $ / segundo

Se cobra por segundo de salida (duration).

Tiempo habitual: ~42 s
Endpoint de cotización: POST /quote/{id}

Crear una solicitud

Los controles se generan a partir del esquema del modelo. El código y el precio se actualizan al modificarlos.

prompt •obligatorio 789 / 20000

Descripción textual del video deseado para la generación.

duration 4 s

Duración del video de salida.

aspect_ratio predeterminado 16:9

Relación entre el ancho y la altura del video generado.

resolution

Resolución utilizada para el video de salida.

Avanzado negative_prompt · safety_tolerance · seed · auto_fix

negative_prompt

Prompt negativo utilizado para orientar la generación de video.

safety_tolerance predeterminado 4

Establece la tolerancia de moderación de contenido entre el nivel menos restrictivo, 6, y el nivel más estricto, 1, que bloquea la mayoría del contenido.

seed

Valor de semilla que inicializa la generación de números aleatorios.

POST /run/veo3.1/fast?wait=20 cotización → 0,60 $

# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/veo3.1/fast?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Ultra realistic ASMR video of a fresh ripe pineapple being cut into a glass-shaped cylinder. Close-up macro shot, natural kitchen lighting, high detail pineapple texture, visible juice droplets, slow precise knife slicing.\nSound focus: crisp crunchy cutting sound, juicy wet fiber tearing sound, subtle knife sliding on cutting board, natural room ambience, no music, stereo binaural ASMR audio. \n\nVisual detail: yellow golden pineapple flesh, fresh green crown slightly visible on table, wooden cutting board, stainless steel sharp knife, realistic juice splashing slightly when sliced.\nCamera: slow cinematic movement, macro lens, depth of field, focus on knife entering pineapple flesh.\nStyle: hyper realistic, 4K, natural color grading, food photography realism, satisfying ASMR style.",
    "duration": "4s",
    "resolution": "720p",
    "generate_audio": true
  }'

# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"

const API = "https://api.doitong.ru/v1";
const headers = {
  "Authorization": "Bearer " + process.env.DOITONG_API_KEY,
  "Content-Type": "application/json",
};

// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/veo3.1/fast?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "Ultra realistic ASMR video of a fresh ripe pineapple being cut into a glass-shaped cylinder. Close-up macro shot, natural kitchen lighting, high detail pineapple texture, visible juice droplets, slow precise knife slicing.\nSound focus: crisp crunchy cutting sound, juicy wet fiber tearing sound, subtle knife sliding on cutting board, natural room ambience, no music, stereo binaural ASMR audio. \n\nVisual detail: yellow golden pineapple flesh, fresh green crown slightly visible on table, wooden cutting board, stainless steel sharp knife, realistic juice splashing slightly when sliced.\nCamera: slow cinematic movement, macro lens, depth of field, focus on knife entering pineapple flesh.\nStyle: hyper realistic, 4K, natural color grading, food photography realism, satisfying ASMR style.",
    "duration": "4s",
    "resolution": "720p",
    "generate_audio": true
  }),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);

// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
  res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
  request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");

import os
import requests

API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "prompt": "Ultra realistic ASMR video of a fresh ripe pineapple being cut into a glass-shaped cylinder. Close-up macro shot, natural kitchen lighting, high detail pineapple texture, visible juice droplets, slow precise knife slicing.\nSound focus: crisp crunchy cutting sound, juicy wet fiber tearing sound, subtle knife sliding on cutting board, natural room ambience, no music, stereo binaural ASMR audio. \n\nVisual detail: yellow golden pineapple flesh, fresh green crown slightly visible on table, wooden cutting board, stainless steel sharp knife, realistic juice splashing slightly when sliced.\nCamera: slow cinematic movement, macro lens, depth of field, focus on knife entering pineapple flesh.\nStyle: hyper realistic, 4K, natural color grading, food photography realism, satisfying ASMR style.",
    "duration": "4s",
    "resolution": "720p",
    "generate_audio": True,
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/veo3.1/fast", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
    raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])

# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
    request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
    raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "run",
    "arguments": {
      "model_id": "veo3.1/fast",
      "input": {
        "prompt": "Ultra realistic ASMR video of a fresh ripe pineapple being cut into a glass-shaped cylinder. Close-up macro shot, natural kitchen lighting, high detail pineapple texture, visible juice droplets, slow precise knife slicing.\nSound focus: crisp crunchy cutting sound, juicy wet fiber tearing sound, subtle knife sliding on cutting board, natural room ambience, no music, stereo binaural ASMR audio. \n\nVisual detail: yellow golden pineapple flesh, fresh green crown slightly visible on table, wooden cutting board, stainless steel sharp knife, realistic juice splashing slightly when sliced.\nCamera: slow cinematic movement, macro lens, depth of field, focus on knife entering pineapple flesh.\nStyle: hyper realistic, 4K, natural color grading, food photography realism, satisfying ASMR style.",
        "duration": "4s",
        "resolution": "720p",
        "generate_audio": true
      },
      "wait_seconds": 20
    }
  }
}

Ejecutar esta solicitud

Clave de API

Tu clave permanece en este navegador: solo se envía a la Doitong API y se guarda (localStorage) únicamente si marcas Recordar. Recordar en este navegador Obtener una clave de API

Creado en Doitong

Trabajos públicos creados con Veo 3.1 por la comunidad de Doitong. Reutiliza un prompt con un clic.

Trabajos públicos mostrados: 16

Vídeo

Кинематографичная сцена в современном офисном коридоре. Огромная дверь с надписью «Фарм» резко открыта, изнутри виден пиксельный мир в стиле Minecraft: квадратные фермы, зелёные блоки, механизмы, лёгкое зелёное и тёплое свечение. Из двери выходит главный герой — толстый, неприятного вида, немного...

Vídeo

Кинематографичная сцена: главный герой открывает дверь и попадает в бесконечный тёмный мир серверов. Камера медленно движется вперёд, показывая бесконечные серверные стойки, мигающие лампы и холодный неоновый свет. Из темноты появляется глава разработки — абсурдно огромный качок с идеальной...

Vídeo

Главный герой открывает дверь и попадает в розовый сказочный HR-мир. Камера показывает пони, сердечки, блестящие облачка, розовый свет и всё вокруг как будто сделано из милоты. В центре появляется бимбо-глава HR — очень гламурная, в розовом, с идеальной внешностью и ярким макияжем. Она дружелюбно...

Vídeo

Главный герой открывает дверь и оказывается в гигантском мире Minecraft-like. Камера показывает бесконечные фермы, механизмы, падающие ресурсы, мобов, редстоун и автоматизацию. На переднем плане стоит глава отдела фарма — квадратный парень с мотыгой в руках. Он разворачивается к герою и жестом...

Vídeo

Кинематографичная сцена: главный герой открывает дверь и попадает в бесконечный тёмный мир серверов. Камера медленно движется вперёд, показывая бесконечные серверные стойки, мигающие лампы и холодный неоновый свет. Из темноты появляется глава разработки — абсурдно огромный качок с идеальной...

Vídeo

Камера показывает рабочую жизнь HR-отдела: одна сотрудница катается на кресле, кто-то берёт подушку Кати, несколько человек сидят и увлечённо болтают, другие пьют чай и кушают, и всё это происходит так, будто это стратегическая работа мирового уровня. Глава HR стоит посреди этого хаоса и с милой...

Vídeo

Кинематографичная сцена в современном офисном коридоре. Главный герой стоит напротив четырёх огромных дверей, каждая из которых выглядит как вход в отдельную вселенную. Над дверями большими буквами написано: Разработка, Маркетинг, HR, Фарм. Сначала камера показывает героя со спины или в...

Vídeo

Глава фарма ведёт главного героя по своему миру и показывает, как устроены фермы и процессы. Затем он указывает на отдельную часть системы, где визуально показана новая схема выдачи аккаунтов по новым гео. Вокруг двигаются механизмы, работают фермы, падает дроп, всё автоматизировано и работает...

Acerca de Veo 3.1 Fast

Veo 3.1 Fast conserva el realismo, el diálogo y la generación de sonido de Veo, con tiempos de renderizado más cortos y un precio mucho menor, lo que lo convierte en una buena opción predeterminada para iterar. 4, 6 u 8 segundos, 16:9 o 9:16, a 720p, 1080p o 4K; el audio se puede desactivar.

Parámetros

NombreTipo PredeterminadoPermitido Descripción

promptobligatorio

Tipostring

≤ 20.000 caracteres

Descripción textual del video deseado para la generación.

aspect_ratioopcional

Tipoenum

Predeterminado16:9

16:99:16

Relación entre el ancho y la altura del video generado.

durationopcional

Tipoenum

Predeterminado8s

4s6s8s

Duración del video de salida.

negative_promptopcional

Tipostring | null

Prompt negativo utilizado para orientar la generación de video.

resolutionopcional

Tipoenum

Predeterminado720p

720p1080p4k

Resolución utilizada para el video de salida.

generate_audioopcional

Tipoboolean

Predeterminadotrue

Controla si el video incluye audio generado.

seedopcional

Tipointeger | null

Valor de semilla que inicializa la generación de números aleatorios.

auto_fixopcional

Tipoboolean

Predeterminadotrue

Reescritura automática de prompts para intentar resolver fallos en las comprobaciones de la política de contenido u otras validaciones.

safety_toleranceopcional

Tipoenum

Predeterminado4

123456

Establece la tolerancia de moderación de contenido entre el nivel menos restrictivo, 6, y el nivel más estricto, 1, que bloquea la mayoría del contenido.

obligatorio

Salida

GET /requests/req_8k2m4q7x1z9c3v5b6n0p2r4t

{
  "id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
  "object": "request",
  "model": "veo3.1/fast",
  "status": "succeeded",
  "created_at": "2026-10-20T12:00:00Z",
  "started_at": "2026-10-20T12:00:02Z",
  "completed_at": "2026-10-20T12:00:09Z",
  "queue_position": null,
  "cost": {
    "credits": 600,
    "usd": "0.60",
    "charged": 600,
    "refunded": 0
  },
  "input": {
    "prompt": "A golden retriever runs along a beach at sunset, waves splashing, slow motion, warm backlight",
    "duration": 6,
    "resolution": "720p"
  },
  "output": {
    "video": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_name": "0-output.mp4",
      "file_size": 1843200
    }
  },
  "outputs": [
    {
      "type": "video",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_size": 1843200,
      "width": 1280,
      "height": 720,
      "duration": 5,
      "stored": true
    }
  ],
  "error": null,
  "metrics": {
    "inference_seconds": 6.8
  },
  "urls": {
    "self": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}

Tus archivos, tú eligesCada outputs[].url es una copia en nuestro almacenamiento: conservada para siempre (se cobra por GB-mes) o 7 días gratis, según la configuración de tu cuenta o ?storage=.

La misma estructura en todos los modelostype, url, content_type, width, height y duration, tanto para imágenes como para vídeo y audio. output es el objeto de resultado propio del modelo.

Campos de salida

video: object {url, content_type, file_name, file_size}Video producido por el modelo.

Más modelos: Texto a vídeo

Para agentes de IA: esta página en Markdown está en https://doitong.com/es/developers/models/veo3.1/fast.md. Todos los modelos y guías: https://doitong.com/developers/llms.txt