each::sense is in private beta.
Eachlabs | AI Workflows for app builders

KLING-V1.5

Kling v1.5 Pro Image to Video reliably converts images into videos, emphasizing sharpness and seamless motion.

Avg Run Time: 200.000s

Model Slug: kling-v1-5-pro-image-to-video

Playground

Input

Enter a URL or choose a file from your computer.

Advanced Controls

Output

Example Result

Preview and download your result.

Unsupported conditions - pricing not available for this input format

API & SDK

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.

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.

Readme

Table of Contents
Overview
Technical Specifications
Key Considerations
Tips & Tricks
Capabilities
What Can I Use It For?
Things to Be Aware Of
Limitations

Overview

Kling v1.5 Pro Image to Video is a video generation model designed to convert static images into short, coherent motion clips. By combining image input with a descriptive prompt, Kling v1.5 Pro Image to Video synthesizes dynamic and realistic animations. It supports advanced control through text prompts, transition planning, and tail image sequencing, making it suitable for storytelling and visual content generation where seamless motion and image consistency are important.

Technical Specifications

 Supports bidirectional temporal rendering with improved interpolation between source and tail images.

Tailored for short video generation up to 10 seconds, maintaining coherence across motion and lighting.

Incorporates a fine-tuned motion engine designed to preserve spatial elements of the input image while generating realistic depth shifts.

Optimized rendering pipeline ensures prompt-guided influence remains prominent while honoring source image structure.

Aspect ratio rendering is aligned with final frame cropping to ensure minimal deformation or artifacting.

Key Considerations

Output quality is strongly dependent on the alignment between prompt and image. Misaligned prompts may cause artifacts or hallucinated elements.

Using tail image drastically changes the ending sequence. Ensure tail image matches the visual tone of the main input image.

Avoid cluttered or text-heavy input images as they may result in motion artifacts or frame instability.

Aspect ratio mismatch between image and selected ratio can cause unwanted cropping or stretching.

Longer durations (10s) might lead to subtle blurriness near the end if motion is too intense or unstructured in the prompt.


Legal Information for Kling v1.5 Pro Image to Video

By using this Kling v1.5 Pro Image to Video, you agree to:

Tips & Tricks

prompt: Be specific. Include motion type (e.g., “slow pan forward”, “dynamic camera tilt”), environmental details, and lighting conditions. Example:
"a majestic mountain range under golden sunset, slow cinematic zoom forward"

negative_prompt: Use to exclude unwanted elements like “blur”, “distortion”, “extra limbs”, “low resolution”, or style mismatches.
Example: "blurry, cartoon, abstract, low quality, extra objects"

cfg_scale:

  • Range: 0–1
  • Values between 0.6–0.8 generally offer a balance between creativity and fidelity to the input image.
  • Lower values (e.g., 0.4) reduce prompt influence and preserve image structure more.
  • Higher values (0.9+) may introduce more creative interpretation but can deviate from image details.

aspect_ratio:

  • 16:9: Best for horizontal videos or cinematic presentation.
  • 9:16: Ideal for mobile or vertical social content.
  • 1:1: Square format for symmetrical scenes or specific platform needs.

duration:

  • 5s: Recommended for dynamic, punchy motion.
  • 10s: Suitable for smooth, narrative transitions or sequences with tail image usage.

image_url: Should be a clean, single-subject composition. Avoid cluttered scenes. Backgrounds should support the motion direction suggested in the prompt.

tail_image_url: Helps define the ending visual frame. Ensure it's visually compatible with the main image. Example use: character turning around, scene fading into night, etc.

Capabilities

Generates short animated video clips (5–10 seconds) from a single input image.

Supports visual transitions using both a starting and tail image.

Creates realistic camera motion such as panning, zooming, or dolly shots.

Preserves subject integrity while interpreting motion cues from the prompt.

Aligns prompt context with visual depth, environment, and tone.

What Can I Use It For?

Creating dynamic animated intros for static visual assets.

Generating teaser videos from posters, key visuals, or product shots.

Producing cinematic clips for social media with added movement.

Enhancing still photography with fluid camera motions.

Extending visual narratives using tail-to-tail image sequencing.

Things to Be Aware Of

Try combining a calm scene input with a tail image that introduces lighting change for a day-to-night transition.

Animate artwork or illustrations using rich camera motion prompts.

Use negative prompts to eliminate specific artifacts like “frame tearing” or “double shadows.”

Combine a high cfg_scale (0.9) with strong prompts for stylized artistic movement.

Match aspect ratio with platform destination before generation for better composition alignment.

Limitations

Motion generation may lose consistency in highly abstract or surreal prompts.

Faces and text in the image may become distorted if not supported by the prompt.

Not suitable for videos requiring object-level animation or complex scene changes.

Output may suffer from flickering if background has too much texture variation.

Transitions between main and tail image work best with similar subject positions and angles.

Output Format: MP4

Pricing

Pricing Type: Dynamic

What this rule does

Pricing Rules

DurationPrice
5$0.49
10$0.98