Kling v1.6 Pro Elements

kling-v1-6-pro-elements

Static images turn into clean and reliable videos with Kling v1.6 Pro Elements, designed for consistent and clear video generation.

Fast Inference

REST API

Try in Console API Docs Examples

Model Information

Response Time~380 sec

StatusActive

Version

0.0.1

Updated9 days ago

Live Demo

Average runtime: ~380 seconds

Input

Configure model parameters

Prompt

Element 4 is the background. Element 3 has fallen on the ground. Element 1 and element 2 are helping element 3 stand up.

Reference Image

File upload is currently disabled

Reference Image 2

File upload is currently disabled

Duration

Output

View generated results

Result

Preview, share or download your results with a single click.

Each execution costs $0.49 With $1 you can run this model about 2 times.

API Reference

View Full Documentation

Prerequisites

Create an API Key from the Eachlabs Console
Install the required dependencies for your chosen language (e.g., requests for Python)

API Integration Steps

1. Create a Prediction

Send a POST request to create a new prediction. This will return a prediction ID that you'll use to check the result. The request should include your model inputs and API key.

import requests
import time

API_KEY = "YOUR_API_KEY"  # Replace with your API key
HEADERS = {
    "X-API-Key": API_KEY,
    "Content-Type": "application/json"
}

def create_prediction():
    response = requests.post(
        "https://api.eachlabs.ai/v1/prediction/",
        headers=HEADERS,
        json={
            "model": "kling-v1-6-pro-elements",
            "version": "0.0.1",
            "input": {
  "negative_prompt": "your negative prompt here",
  "aspect_ratio": "16:9",
  "duration": 5,
  "prompt": "your prompt here",
  "image_url_4": "your reference image 4 here",
  "image_url_3": "your reference image 3 here",
  "image_url_2": "your reference image 2 here",
  "image_url_1": "your reference image here"
},
            "webhook_url": ""
        }
    )
    prediction = response.json()
    
    if prediction["status"] != "success":
        raise Exception(f"Prediction failed: {prediction}")
    
    return prediction["predictionID"]

2. Get Prediction Result

Poll the prediction endpoint with the prediction ID until the result is ready. The API uses long-polling, so you'll need to repeatedly check until you receive a success status.

def get_prediction(prediction_id):
    while True:
        result = requests.get(
            f"https://api.eachlabs.ai/v1/prediction/{prediction_id}",
            headers=HEADERS
        ).json()
        
        if result["status"] == "success":
            return result
        elif result["status"] == "error":
            raise Exception(f"Prediction failed: {result}")
        
        time.sleep(1)  # Wait before polling again

3. Complete Example

Here's a complete example that puts it all together, including error handling and result processing. This shows how to create a prediction and wait for the result in a production environment.

try:
    # Create prediction
    prediction_id = create_prediction()
    print(f"Prediction created: {prediction_id}")
    
    # Get result
    result = get_prediction(prediction_id)
    print(f"Output URL: {result['output']}")
    print(f"Processing time: {result['metrics']['predict_time']}s")
except Exception as e:
    print(f"Error: {e}")

Additional Information

The API uses a two-step process: create prediction and poll for results
Response time: ~380 seconds
Rate limit: 60 requests/minute
Concurrent requests: 10 maximum
Use long-polling to check prediction status until completion

Overview

Kling v1.6 Pro Elements is designed to transform multiple input images into a dynamic and cohesive short video. By blending visual references and textual prompts, Kling v1.6 Pro Elements enables the generation of fluid visual sequences where character consistency and stylistic control can be maintained. Kling v1.6 Pro Elements is well-suited for scenarios where multiple reference images are needed to define a subject or concept across frames.

Technical Specifications

Kling v1.6 Pro Elements operates as a multi-image-driven video generation model.

It is optimized for generating short animated clips using 2 to 4 visual references.

Supports motion sequences up to 10 seconds in length.

Ensures coherence in character features, clothing, and motion trajectory.

Integrates text prompt conditioning to guide scene style, context, and visual elements.

Uses diffusion-based architecture to interpolate and animate static visuals into moving scenes.

Key Considerations

Reference images should be high resolution, front-facing, and centered for optimal output.

Significant differences in lighting or angles across reference images may lead to jitter or visual artifacts.

Negative prompts are useful for avoiding unwanted objects, colors, or visual effects.

Kling v1.6 Pro Elements is not intended for real-time processing and has an average rendering latency depending on image size and duration.

Legal Information for Kling v1.6 Pro Elements

By using this Kling v1.6 Pro Elements, you agree to:

Kling Privacy
Kling SERVICE AGREEMENT

Tips & Tricks

prompt: Use descriptive, scene-based text like “a person walking through a foggy forest” to shape the video setting. Stick to one style or theme.

negative_prompt: Exclude visual noise such as “low quality, distorted face, extra limbs” for cleaner outputs.

aspect_ratio:

Use 16:9 for cinematic wide shots.
Use 9:16 for vertical formats (e.g. mobile content).
Use 1:1 for square visuals suitable for avatars or profile formats.

duration:

Choose 5 for quick loops or subtle movement.
Use 10 to show fuller motion arcs or longer transitions.

image_url_1 to image_url_4:

Always fill image_url_1.
Optionally include image_url_2, image_url_3 and mage_url_4 to add diversity and refine motion between perspectives.
Avoid mixing drastically different styles or subjects between inputs.

Capabilities

Generates motion videos from up to four static reference images.

Captures consistent facial and body identity across frames.

Enables text-driven stylistic customization of motion and environment.

Provides control over output format and length.

What can I use for?

Creating animated profile sequences or character reveals.

Producing stylized social media videos based on a set of static portraits.

Building consistent moving visualizations from concept art or reference photography.

Enhancing static character sheets into short animated loops.

Things to be aware of

Try combining images of the same subject in different outfits to visualize smooth outfit transitions.

Blend fantasy prompts like “cyberpunk street at night” with high-quality portraits to generate immersive character scenes.

Use 1:1 aspect ratio and 5 second duration for animated profile avatars.

Limitations

Kling v1.6 Pro Elements does not support audio or lip sync.

Limited to a maximum duration of 10 seconds.

Unbalanced or mismatched reference images can result in flickering or motion inconsistency.

May not preserve intricate background details unless clearly stated in the prompt.

Output Format: MP4

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