WaveSpeedAI APIKling V1.6 I2V Pro

Kling V1.6 I2V Pro

Generate 5s videos in 1080p resolution from image

Features

Kling-v1.6-I2V-Pro is an advanced image-to-video generation model developed by the Kuaishou AI Team. Building upon the capabilities of the Kling AI platform, this model transforms static images into dynamic, high-quality videos, enabling users to create compelling visual narratives with ease.

Key Features

  • Kling-V1.6-i2v-pro is an advanced image-to-video generation model designed to transform static images into high-quality, dynamic videos. This model builds on the capabilities of its predecessor, Kling V1.6, with significant improvements in visual quality, motion dynamics, and semantic understanding. Key features include:
  • High-Quality Video Output: Both models generate 5-second videos in 720p and 1080p resolution with vivid details and cinematic quality.
  • Enhanced Motion Rendering: Utilizes advanced dynamic rendering techniques to create smooth and natural movements, making the generated videos more engaging and visually appealing.
  • Improved Semantic Understanding: Excels in interpreting complex user prompts to generate coherent and dynamic scenes that align closely with user expectations.
  • Physical Realism: Simulates realistic physical properties and movements, ensuring the generated videos adhere to natural laws and appear lifelike.
  • Fast Processing: Optimized for efficient generation, allowing users to create high-quality videos quickly.
  • Customizable Parameters: Offers adjustable settings such as duration, quality, and style, providing users with greater control over the final output.

ComfyUI

kwaivgi/kling-v1.6-i2v-pro is also available on ComfyUI, providing local inference capabilities through a node-based workflow, ensuring flexible and efficient image generation on your system.

Limitations

  • Creative Content Focus: Designed primarily for creative video synthesis; not intended for generating factually accurate or reliable content.
  • Input Sensitivity: The quality and consistency of generated videos depend significantly on the quality of the input image; subtle variations may lead to output variability.
  • Resource Requirements: While optimized for performance, generating high-resolution videos with complex simulations may require substantial computational resources.

Out-of-Scope Use

The model and its derivatives may not be used in any way that violates applicable national, federal, state, local, or international law or regulation, including but not limited to:

  • Exploiting, harming, or attempting to exploit or harm minors, including solicitation, creation, acquisition, or dissemination of child exploitative content.
  • Generating or disseminating verifiably false information with the intent to harm others.
  • Creating or distributing personal identifiable information that could be used to harm an individual.
  • Harassing, abusing, threatening, stalking, or bullying individuals or groups.
  • Producing non-consensual nudity or illegal pornographic content.
  • Making fully automated decisions that adversely affect an individual’s legal rights or create binding obligations.
  • Facilitating large-scale disinformation campaigns.

Accelerated Inference

Our accelerated inference approach leverages advanced optimization technology from WavespeedAI. This innovative fusion technique significantly reduces computational overhead and latency, enabling rapid image generation without compromising quality. The entire system is designed to efficiently handle large-scale inference tasks while ensuring that real-time applications achieve an optimal balance between speed and accuracy. For further details, please refer to the blog post.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result


# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/kwaivgi/kling-v1.6-i2v-pro" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "image": "https://d2g64w682n9w0w.cloudfront.net/media/images/1747220408880912820_13ZWSPLJ.jpg",
    "prompt": "A girl falling slowly underwater, calm and serene facial expression, light and shadow dancing on her face. She gently raises both arms, hair flowing softly in water, high-quality visuals, slow motion, cinematic lighting",
    "guidance_scale": 0.5,
    "duration": "5"
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
imagestringYeshttps://d2g64w682n9w0w.cloudfront.net/media/images/1747220408880912820_13ZWSPLJ.jpg-First frame of the video; Supported image formats include.jpg/.jpeg/.png; The image file size cannot exceed 10MB, and the image resolution should not be less than 300*300px, and the aspect ratio of the image should be between 1:2.5 ~ 2.5:1
end_imagestringNo--Tail frame of the video; Supported image formats include.jpg/.jpeg/.png; The image file size cannot exceed 10MB, and the image resolution should not be less than 300*300px.
promptstringNoA girl falling slowly underwater, calm and serene facial expression, light and shadow dancing on her face. She gently raises both arms, hair flowing softly in water, high-quality visuals, slow motion, cinematic lighting-Text prompt for generation; Positive text prompt; Cannot exceed 2500 characters
negative_promptstringNo--Negative text prompt; Cannot exceed 2500 characters
guidance_scalenumberNo0.50.00 ~ 1.00Flexibility in video generation; The higher the value, the lower the model’s degree of flexibility, and the stronger the relevance to the user’s prompt.
durationstringNo55, 10Generate video duration length seconds.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayArray of URLs to the generated content (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.has_nsfw_contentsarrayArray of boolean values indicating NSFW detection for each output
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Query Parameters

Result Request Parameters

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction
data.modelstringModel ID used for the prediction
data.outputsarrayArray of URLs to the generated content (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.has_nsfw_contentsarrayArray of boolean values indicating NSFW detection for each output
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
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