MiniMax-H3 Context-IR Prompt Enhancement

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 (optional): ① Context-IR enhances the prompt → ② MiniMax-H3 with 768P for a preview → ③ Regeneration upscales to 2K. Combined unit prices match direct 2K, with cheaper retries. You can also call this endpoint alone.

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"
  }
}

Authorization

string

required

Bearer Token auth. Get a key from the API Key Management Page.

Authorization: Bearer YOUR_API_KEY

Overview

Send your idea plus optional media for multimodal understanding; receive a structured, richer prompt.

No video is produced. Result is in result.prompt (not result.videos)
Media fields use the same validation rules as video generation (frame vs reference mutual exclusion; audio cannot be alone) so the same inputs can go to generation next

Completed task query example:

{
  "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
    }
  }
}

Pass result.prompt as-is to MiniMax-H3 as prompt.

Request Parameters

string

required

Fixed value: MiniMax-H3-Context-IR

string

required

Original idea text, ≤ 7000 characters

integer

default:"5"

Target video duration (seconds), 4~15, default 5. Affects pacing language in the enhanced prompt.

string

Target aspect ratio. Required for text-only input, and cannot be adaptive.Common values: 16:9, 9:16, 1:1, 4:3, 3:4, 21:9, etc.

string

First-frame image URL

string

Last-frame image URL

string[]

Reference images (always treated as references), ≤ 9

object[]

Role-tagged images: first_frame / last_frame / reference_image

string[]

Reference videos, ≤ 3; each 2~15s, total ≤ 15s

string[]

Reference audio, ≤ 3; cannot be used alone — pair with image or video

Billing

Token-based (only H3-family model billed by tokens):

Item	Price
Input tokens	$0.87 / million
Output tokens	$3.45 / million

A typical call (~5.6k input + ~3.4k output tokens) is about $0.0167. A fixed deposit is pre-charged on submit, then settled against real prompt_tokens / completion_tokens (refund excess / charge shortfall). Multimodal inputs significantly increase input tokens.

Notes

Usually 20~40 seconds; poll task status every 3~5 seconds.
Bad params → sync 400 (no task, no charge); runtime failures go to failed with auto refund.
Full workflow notes are on the Regeneration page.

Response

integer

Status code; 200 on success

array

On submit: status / task_id

Show Array elements

string

Initially submitted

string

Task ID

Overview

Text Series

Image Series

Video Series

Audio Series

Moderation Series

Upload Management

Task Management

Account Management

MiniMax-H3 Context-IR Prompt Enhancement

Authorization

Overview

Request Parameters

Billing

Notes

Response

​Authorization

​Overview

​Request Parameters

​Billing

​Notes

​Response

Authorization

Overview

Request Parameters

Billing

Notes

Response