MiniMax-H3 Context-IR mejora de prompt

curl --request POST \
  --url https://api.apimart.ai/v1/videos/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "MiniMax-H3-Context-IR",
    "prompt": "Epic space-opera trailer: a female captain alone before a huge viewport as the last fleet gathers and jumps away.",
    "duration": 5,
    "aspect_ratio": "16:9"
  }'

import requests

url = "https://api.apimart.ai/v1/videos/generations"

payload = {
    "model": "MiniMax-H3-Context-IR",
    "prompt": "Epic space-opera trailer: a female captain alone before a huge viewport as the last fleet gathers and jumps away.",
    "duration": 5,
    "aspect_ratio": "16:9",
}

headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json",
}

response = requests.post(url, json=payload, headers=headers)

print(response.json())

const url = "https://api.apimart.ai/v1/videos/generations";

const payload = {
  model: "MiniMax-H3-Context-IR",
  prompt: "Epic space-opera trailer: a female captain alone before a huge viewport as the last fleet gathers and jumps away.",
  duration: 5,
  aspect_ratio: "16:9",
};

const headers = {
  Authorization: "Bearer <token>",
  "Content-Type": "application/json",
};

fetch(url, {
  method: "POST",
  headers: headers,
  body: JSON.stringify(payload),
})
  .then((response) => response.json())
  .then((data) => console.log(data))
  .catch((error) => console.error("Error:", error));

{
  "code": 200,
  "data": [
    {
      "status": "submitted",
      "task_id": "task_01J9HA7JPQ9A0Z6JZ3V8M9W6PZ"
    }
  ]
}

{
  "error": {
    "code": 400,
    "message": "Invalid request parameters",
    "type": "invalid_request_error"
  }
}

{
  "error": {
    "code": 401,
    "message": "Authentication failed, please check your API key",
    "type": "authentication_error"
  }
}

{
  "error": {
    "code": 402,
    "message": "Insufficient account balance, please top up and try again",
    "type": "payment_required"
  }
}

POST

videos

generations

curl --request POST \
  --url https://api.apimart.ai/v1/videos/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "MiniMax-H3-Context-IR",
    "prompt": "Epic space-opera trailer: a female captain alone before a huge viewport as the last fleet gathers and jumps away.",
    "duration": 5,
    "aspect_ratio": "16:9"
  }'

import requests

url = "https://api.apimart.ai/v1/videos/generations"

payload = {
    "model": "MiniMax-H3-Context-IR",
    "prompt": "Epic space-opera trailer: a female captain alone before a huge viewport as the last fleet gathers and jumps away.",
    "duration": 5,
    "aspect_ratio": "16:9",
}

headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json",
}

response = requests.post(url, json=payload, headers=headers)

print(response.json())

const url = "https://api.apimart.ai/v1/videos/generations";

const payload = {
  model: "MiniMax-H3-Context-IR",
  prompt: "Epic space-opera trailer: a female captain alone before a huge viewport as the last fleet gathers and jumps away.",
  duration: 5,
  aspect_ratio: "16:9",
};

const headers = {
  Authorization: "Bearer <token>",
  "Content-Type": "application/json",
};

fetch(url, {
  method: "POST",
  headers: headers,
  body: JSON.stringify(payload),
})
  .then((response) => response.json())
  .then((data) => console.log(data))
  .catch((error) => console.error("Error:", error));

{
  "code": 200,
  "data": [
    {
      "status": "submitted",
      "task_id": "task_01J9HA7JPQ9A0Z6JZ3V8M9W6PZ"
    }
  ]
}

{
  "error": {
    "code": 400,
    "message": "Invalid request parameters",
    "type": "invalid_request_error"
  }
}

{
  "error": {
    "code": 401,
    "message": "Authentication failed, please check your API key",
    "type": "authentication_error"
  }
}

{
  "error": {
    "code": 402,
    "message": "Insufficient account balance, please top up and try again",
    "type": "payment_required"
  }
}

Full 2K Workflow (opcional): ① Context-IR mejora el prompt → ② MiniMax-H3 con 768P para una vista previa → ③ Regeneration sube a 2K. Los precios unitarios combinados coinciden con el 2K directo, con reintentos más baratos. También puede llamar a este endpoint solo.

curl --request POST \
  --url https://api.apimart.ai/v1/videos/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "MiniMax-H3-Context-IR",
    "prompt": "Epic space-opera trailer: a female captain alone before a huge viewport as the last fleet gathers and jumps away.",
    "duration": 5,
    "aspect_ratio": "16:9"
  }'

import requests

url = "https://api.apimart.ai/v1/videos/generations"

payload = {
    "model": "MiniMax-H3-Context-IR",
    "prompt": "Epic space-opera trailer: a female captain alone before a huge viewport as the last fleet gathers and jumps away.",
    "duration": 5,
    "aspect_ratio": "16:9",
}

headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json",
}

response = requests.post(url, json=payload, headers=headers)

print(response.json())

const url = "https://api.apimart.ai/v1/videos/generations";

const payload = {
  model: "MiniMax-H3-Context-IR",
  prompt: "Epic space-opera trailer: a female captain alone before a huge viewport as the last fleet gathers and jumps away.",
  duration: 5,
  aspect_ratio: "16:9",
};

const headers = {
  Authorization: "Bearer <token>",
  "Content-Type": "application/json",
};

fetch(url, {
  method: "POST",
  headers: headers,
  body: JSON.stringify(payload),
})
  .then((response) => response.json())
  .then((data) => console.log(data))
  .catch((error) => console.error("Error:", error));

{
  "code": 200,
  "data": [
    {
      "status": "submitted",
      "task_id": "task_01J9HA7JPQ9A0Z6JZ3V8M9W6PZ"
    }
  ]
}

{
  "error": {
    "code": 400,
    "message": "Invalid request parameters",
    "type": "invalid_request_error"
  }
}

{
  "error": {
    "code": 401,
    "message": "Authentication failed, please check your API key",
    "type": "authentication_error"
  }
}

{
  "error": {
    "code": 402,
    "message": "Insufficient account balance, please top up and try again",
    "type": "payment_required"
  }
}

Autorización

string

requerido

Autenticación Bearer Token. Obtenga una clave en la página de gestión de API Keys.

Authorization: Bearer YOUR_API_KEY

Resumen

Envíe su idea y medios opcionales para comprensión multimodal; reciba un prompt estructurado y más rico.

No se produce video. El resultado está en result.prompt (no en result.videos)
Los campos de medios usan las mismas reglas de validación que la generación de video (exclusión mutua fotogramas vs referencias; el audio no puede ir solo) para que las mismas entradas puedan pasar a la generación

Ejemplo de consulta de tarea completada:

{
  "code": 200,
  "data": {
    "actual_time": 28,
    "completed": 1700000128,
    "cost": 0.011204,
    "created": 1700000100,
    "credits_cost": 0.11204,
    "estimated_time": 100,
    "id": "task_01J9HA7J*************",
    "progress": 100,
    "result": {
      "prompt": "integrated_multimodal_description: [Shot 1] Cinematic, close-up shot. The camera slowly pushes in on a lone adult astronaut standing in a dimly lit, metallic corridor. The astronaut wears a weathered, white and silver extravehicular spacesuit heavily scuffed with grey dust, featuring a completely opaque, gold-tinted helmet visor. The astronaut slowly pushes open a rusted, thick steel airlock door on the right side of the frame. As the heavy metal door shifts, a sudden, intense beam of vibrant green light spills across the dark frame, illuminating the intricate fabric folds of the suit. The curved golden visor vividly reflects a dense, tangled mass of luminescent green leaves and vines. [Shot 2] At 00:02.500, the camera cuts to a wide shot from directly behind the astronaut from Shot 1, smoothly pedestaling up to reveal the interior of the abandoned orbital station. The vast, hexagonal titanium room is completely overrun by a lush, zero-gravity living garden. Giant, emerald-green vines spiral tightly around cracked, grey ceiling support beams, while thick patches of bioluminescent cyan moss emit a soft glow from the rusted floor grid. Several large, perfectly spherical water droplets float weightlessly in the midground, refracting the ambient green light. The astronaut lowers their heavy, white-gloved hands to their sides, standing perfectly motionless before the massive canopy of overgrown flora.\noverall_soundscape: A loud, grinding metallic creak dominates the foreground as the heavy steel door shifts, instantly followed by a pronounced, high-pitched hiss of escaping pressurized air. A continuous, low-frequency mechanical hum rumbles in the background, establishing the station's deadened room tone. As the space opens, the distinct, crisp rustle of thick foliage is clearly heard, accompanied by soft, resonant liquid plops as unseen water drops collide in the metallic chamber.\nnon_diegetic_music: Ambient electronic score, slow tempo, featuring a deep, sustained synthesizer drone heavily overlaid with delicate, shimmering glockenspiel notes and a solitary, reverberating cello."
    },
    "status": "completed",
    "usage": {
      "input_tokens": 5512,
      "output_tokens": 2388,
      "total_tokens": 7900
    }
  }
}

Pase result.prompt tal cual a MiniMax-H3 como prompt.

Parámetros de la solicitud

string

requerido

Valor fijo: MiniMax-H3-Context-IR

boolean

predeterminado:"false"

Indica si se debe moderar el contenido antes de enviar la tarea Context-IR.

true: revisar los prompts y las imágenes de entrada con omni-moderation-latest
false u omitido: no enviar una solicitud de moderación, sin coste ni latencia de moderación adicionales (predeterminado)

string

requerido

Texto de la idea original, ≤ 7000 caracteres

integer

predeterminado:"5"

Duración objetivo del video (segundos), 4~15, valor predeterminado 5. Afecta el lenguaje de ritmo en el prompt mejorado.

string

Relación de aspecto objetivo. Obligatorio para entrada solo de texto, y no puede ser adaptive.Valores comunes: 16:9, 9:16, 1:1, 4:3, 3:4, 21:9, etc.

string

URL de la imagen del primer fotograma

string

URL de la imagen del último fotograma

string[]

Imágenes de referencia (siempre tratadas como referencias), ≤ 9

object[]

Imágenes con roles: first_frame / last_frame / reference_image

string[]

Videos de referencia, ≤ 3; cada uno 2~15 s, total ≤ 15 s

string[]

Audio de referencia, ≤ 3; no se puede usar solo — combínelo con imagen o video

Facturación

Basada en tokens (único modelo de la familia H3 facturado por tokens):

Concepto	Precio
Tokens de entrada	$0.87 / millón
Tokens de salida	$3.45 / millón

Una llamada típica (~5,6k entrada + ~3,4k salida tokens) cuesta unos $0.0167. Se preautoriza un depósito fijo al enviar y luego se liquida con los prompt_tokens / completion_tokens reales (reembolso del exceso / cargo del déficit). Las entradas multimodales aumentan mucho los tokens de entrada.

Notas

Suele tardar 20~40 segundos; consulte el estado de la tarea cada 3~5 segundos.
Parámetros incorrectos → 400 síncrono (sin tarea, sin cargo); fallos en runtime pasan a failed con reembolso automático.
Las notas del workflow completo están en la página Regeneration.

Response

integer

Código de estado; 200 en caso de éxito

array

Al enviar: status / task_id

Mostrar Elementos del array

string

Inicialmente submitted

string

ID de la tarea

Visión general

Modelos

Serie de texto

Serie de imágenes

Serie de video

Serie de audio

Serie de Moderación

Gestión de subidas

Gestión de tareas

Gestión de cuenta

MiniMax-H3 Context-IR mejora de prompt

Autorización

Resumen

Parámetros de la solicitud

Facturación

Notas

Response

​Autorización

​Resumen

​Parámetros de la solicitud

​Facturación

​Notas

​Response

Autorización

Resumen

Parámetros de la solicitud

Facturación

Notas

Response