SJinn
Kling 3.0 Image-to-Video

Kling 3.0 Image-to-Video

Transform static images into dynamic videos using Kling 3.0 model with Standard and Pro modes

Tool Overview

The Kling 3.0 Image-to-Video tool generates high-quality video content from a starting image and text description using Kuaishou's Kling 3.0 model. It supports flexible video duration (3-15 seconds), multi-shot mode, optional tail frame image, and two quality tiers (Standard / Pro).

Tool Identifier

kling3-image-to-video-api

Parameters

Required Parameters

prompt

  • Type: string (required)
  • Description: Text description of the desired motion and video content. Focus on describing the movement rather than the image contents
  • Validation: Must be a non-empty string
  • Example: "The character turns around slowly and smiles at the camera with wind blowing through her hair"

image

  • Type: string (required)
  • Description: Image URL for the video's starting frame
  • Format: Must be a complete HTTP/HTTPS URL (e.g., https://cdn.sjinn.ai/uploads/image.jpg)
  • Validation: Must be a non-empty string

Optional Parameters

duration

  • Type: number (optional)
  • Default: 5
  • Range: 3 - 15 (seconds)
  • Note: Values below 3 are clamped to 3, values above 15 are clamped to 15. String values are automatically parsed to numbers

multi_shot

  • Type: boolean (optional)
  • Default: true
  • Description: Enable multi-shot mode for more dynamic video composition with automatic scene transitions

model_mode

  • Type: string (optional)
  • Default: "standard"
  • Supported Values:
    • "standard" - Standard quality, 200 credits/second
    • "pro" - Enhanced quality with finer detail, 300 credits/second

tail_image_url

  • Type: string (optional)
  • Description: Image URL for the video's ending frame. When provided, the generated video will transition from the starting image to this tail image
  • Format: Must be a complete HTTP/HTTPS URL

Pricing

  • Standard Mode: 200 credits per second (duration × 200)
  • Pro Mode: 300 credits per second (duration × 300)
  • Examples:
    • 5s Standard = 1,000 credits | 5s Pro = 1,500 credits
    • 10s Standard = 2,000 credits | 10s Pro = 3,000 credits
    • 15s Standard = 3,000 credits | 15s Pro = 4,500 credits

Request Examples

Standard Mode (5 seconds)

curl -X POST https://sjinn.ai/api/un-api/create_tool_task \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "tool_type": "kling3-image-to-video-api",
    "input": {
      "prompt": "The character turns around slowly and smiles at the camera",
      "image": "https://cdn.sjinn.ai/uploads/character.jpg",
      "duration": 5
    }
  }'

Pro Mode with Tail Image

curl -X POST https://sjinn.ai/api/un-api/create_tool_task \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "tool_type": "kling3-image-to-video-api",
    "input": {
      "prompt": "The scene gradually transitions from day to night with city lights turning on",
      "image": "https://cdn.sjinn.ai/uploads/city-day.jpg",
      "tail_image_url": "https://cdn.sjinn.ai/uploads/city-night.jpg",
      "duration": 10,
      "model_mode": "pro"
    }
  }'

Using JavaScript

const response = await fetch('https://sjinn.ai/api/un-api/create_tool_task', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    tool_type: 'kling3-image-to-video-api',
    input: {
      prompt: 'The character turns around slowly and smiles at the camera',
      image: 'https://cdn.sjinn.ai/uploads/character.jpg',
      duration: 5,
      model_mode: 'standard',
    },
  }),
});

const result = await response.json();
console.log('Task ID:', result.data.task_id);

Using Python

import requests

url = 'https://sjinn.ai/api/un-api/create_tool_task'
headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json'
}
data = {
    'tool_type': 'kling3-image-to-video-api',
    'input': {
        'prompt': 'The character turns around slowly and smiles at the camera',
        'image': 'https://cdn.sjinn.ai/uploads/character.jpg',
        'duration': 5,
        'model_mode': 'standard'
    }
}

response = requests.post(url, json=data, headers=headers)
result = response.json()
print('Task ID:', result['data']['task_id'])

Response Examples

Success Response

{
  "success": true,
  "errorMsg": "",
  "error_code": 0,
  "data": {
    "task_id": "550e8400-e29b-41d4-a716-446655440000"
  }
}

Error Response

{
  "success": false,
  "errorMsg": "image is required",
  "error_code": 400
}

Best Practices

  1. Image Quality: Use high-quality, clear starting images for better video results
  2. Prompt Focus: Describe the desired motion and movement rather than the image contents. The model already sees the image
  3. Mode Selection: Use standard mode for prototyping, switch to pro for final output when quality matters
  4. Tail Image: Use tail_image_url for controlled transitions between two specific frames. Both images should have similar composition for smooth results
  5. Multi-Shot: Keep multi_shot enabled (default) for more cinematic compositions. Disable it only if you need a single continuous shot
  6. Duration Selection: Start with shorter durations (3-5s) for testing, then increase for final output. Cost scales linearly with duration
  7. Generation Time: Video generation typically takes 2-8 minutes depending on duration and mode

Related Links