Kwaivgi Kling Image V3 Edit

Kwaivgi Kling Image V3 Edit

Playground

Kling V3 Edit is an AI model for editing and transforming images via text prompts, enabling precise modifications with natural-language instructions. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Kling Image V3 Edit is Kuaishou’s image editing model that transforms existing images based on text instructions. Upload a reference image and describe the changes you want — the model applies edits while preserving the original style, structure, and identity. Supports flexible aspect ratios, resolution options, and batch generation.

Why Choose This?

• Text-guided editing Describe changes in natural language — no manual masking or layer editing required.

• Style preservation Maintains the original image’s composition, lighting, and aesthetic while applying your edits.

• Flexible aspect ratios Multiple options including 1:1, 3:4, 4:3, 9:16, 16:9 and more to fit any use case.

• Resolution control Choose output resolution (1k and above) based on your quality and speed requirements.

• Batch generation Generate multiple variations in a single request for rapid iteration and comparison.

• Prompt Enhancer Built-in tool to automatically improve your edit descriptions for better results.

Parameters

How to Use

1. Upload your image — provide the reference image you want to edit.
2. Write your prompt — describe the changes you want (e.g., “Change the jacket to red leather”).
3. Choose aspect ratio — select the output format that fits your use case.
4. Set resolution — choose 1k for speed or higher for more detail.
5. Set num_images — generate multiple variations if needed.
6. Run — submit and download your edited images.

Pricing

Billing Rules

• Rate: $0.028 per image
• Total cost = num_images × $0.028

Best Use Cases

• Fashion & E-commerce — Change clothing colors, styles, or patterns on product images.
• Creative Iteration — Explore variations of a concept without starting from scratch.
• Marketing & Ads — Adapt visuals for different campaigns while maintaining brand consistency.
• Portrait Editing — Adjust styling, backgrounds, or accessories in portrait photos.
• Content Repurposing — Transform existing images for new contexts or platforms.

Pro Tips

• Be specific about what should change and what should stay the same.
• Use the Prompt Enhancer to refine vague instructions into detailed edit commands.
• Generate multiple images (num_images > 1) to explore different interpretations of your edit.
• Higher quality source images yield better editing results.
• Use png format when you need lossless quality output.

Notes

• Both prompt and image are required fields.
• Ensure uploaded image URLs are publicly accessible.
• Higher resolution may slightly increase processing time.

Related Models

• Kling Image V3 Text-to-Image — Generate images from text prompts.
• Kling Image O3 Text-to-Image — Next-generation O3 architecture for text-to-image.
• Kling Video O3 Pro Image-to-Video — Animate edited images into video.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

set -euo pipefail

export WAVESPEED_API_KEY="your-api-key"

REQUEST_BODY=$(cat <<'JSON'
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed",
  "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
  "aspect_ratio": "16:9",
  "resolution": "1k",
  "num_images": 1,
  "output_format": "png",
  "shot_type": "customize"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/kwaivgi/kling-image-v3/edit" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}")

TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "${TASK}" | jq -r '.urls.get // empty')
if [ -z "${RESULT_URL}" ]; then RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"; fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body \
    "${RESULT_URL}" \
    -H "Authorization: Bearer ${WAVESPEED_API_KEY}")
  RESULT=$(printf '%s' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  case "${STATUS}" in
    completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "${STATUS}" >&2; exit 1 ;;
  esac
done

Parameters

Task Submission Parameters

Request Parameters

Response Parameters

Result Request Parameters

Result Response Parameters