Qwen Image Edit

Playground

Qwen-Image-Edit is a 20B MMDiT image-to-image model offering precise bilingual (Chinese & English) text edits while preserving style. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Qwen-Image-Edit

A next-gen image editing model built on Qwen-Image 20B MMDiT. Qwen-Image-Edit delivers precise bilingual text editing (Chinese & English), supports both semantic and appearance-level edits, and preserves the original style — making it one of the most capable image editing models available.

Why It Looks Great

Dual-mode editing: Supports both appearance-level edits (add/remove/modify elements while keeping other regions pixel-accurate) and semantic-level edits (IP creation, rotation, style transfer with global coherence).
Precise text editing (CN/EN): Edit on-image text directly — add, delete, or replace while retaining the original font, size, kerning, and style.
Style preservation: Maintains palette, lighting, brushwork, and overall look even under substantial edits.
20B parameter power: Built on the robust Qwen-Image foundation for superior understanding and generation.
State-of-the-art performance: Achieves SOTA results across multiple public image editing benchmarks.
Prompt Enhancer: Built-in tool to refine your editing instructions automatically.

Parameters

Parameter	Required	Description
prompt	Yes	Text instruction describing the edit you want to make.
image	Yes	Source image to edit (upload or public URL).
size	No	Custom output dimensions with width and height controls.
width	No	Output width in pixels (e.g., 256).
height	No	Output height in pixels (e.g., 256).
seed	No	Random seed for reproducibility. Use -1 for random.
output_format	No	Output file format: jpeg or png. Default: jpeg.
enable_base64_output	No	API only: Returns base64 string instead of URL.
enable_sync_mode	No	API only: Waits for result and returns it directly in response.

How to Use

Write your edit instruction — describe what you want to change in the image.
Use Prompt Enhancer (optional) — click to refine your editing instruction.
Upload your image — drag and drop or paste a public URL.
Set dimensions (optional) — adjust width and height for the output size.
Set seed (optional) — use -1 for random, or a specific number to reproduce results.
Choose output format — select jpeg or png.
Run — click the button to apply the edit.
Download — preview and save your edited image.

Pricing

Flat rate per edit.

Output	Cost
Per image	$0.02

Best Use Cases

Text Replacement — Change text on signs, labels, clothing, or any surface in images (supports Chinese & English).
Element Modification — Add, remove, or swap objects while preserving untouched areas pixel-perfectly.
Style Transfer — Apply new artistic styles while maintaining semantic content.
IP Creation — Generate character variations and creative adaptations.
Object Manipulation — Rotate, reposition, or transform objects within scenes.
Product Customization — Create variations of product images with different details or branding.

Example Prompts

“Change the background to daytime”
“Replace the text on the sign to say ‘Welcome’”
“Remove the person on the left side of the image”
“Change the dress color from red to blue”
“Add sunglasses to the person”

Editing Modes Explained

Mode	Description	Use When
Appearance Editing	Modifies specific elements while keeping all other regions pixel-accurate and unchanged	Adding/removing objects, color changes, localized edits
Semantic Editing	Allows global pixel updates while maintaining semantic intent and consistency	Style transfer, pose changes, IP creation, rotation

Pro Tips for Best Results

Be specific about what to change and what the result should be.
For text editing, the model preserves original typography — just specify the new text content.
Reference elements clearly: “the text on the shirt”, “the background”, “the person’s hair”.
For appearance edits, unchanged areas remain pixel-perfect — focus only on what needs editing.
Use Chinese prompts for editing Chinese text in images for best accuracy.
The model understands context — describe the intent, not just the mechanical change.

Notes

If using a URL for the image, ensure it is publicly accessible. A preview thumbnail confirms successful loading.
The enable_base64_output and enable_sync_mode options are only available through the API.
Complex edits may require more specific prompts for accurate results.
For multiple edits to the same image, consider processing sequentially for better control.

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/wavespeed-ai/qwen-image/edit" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "seed": -1,
    "output_format": "jpeg",
    "enable_base64_output": false,
    "enable_sync_mode": false
}'

# 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

Parameter	Type	Required	Default	Range	Description
prompt	string	Yes		-	The positive prompt for the generation.
image	string	Yes		-	The image to generate an image from.
size	string	No	-	256 ~ 1536 per dimension	The size of the generated media in pixels (width*height).
seed	integer	No	-1	-1 ~ 2147483647	The random seed to use for the generation. -1 means a random seed will be used.
output_format	string	No	jpeg	jpeg, png, webp	The format of the output image.
enable_base64_output	boolean	No	false	-	If enabled, the output will be encoded into a BASE64 string instead of a URL. This property is only available through the API.
enable_sync_mode	boolean	No	false	-	If set to true, the function will wait for the result to be generated and uploaded before returning the response. It allows you to get the result directly in the response. This property is only available through the API.

Response Parameters

Parameter	Type	Description
code	integer	HTTP status code (e.g., 200 for success)
message	string	Status message (e.g., “success”)
data.id	string	Unique identifier for the prediction, Task Id
data.model	string	Model ID used for the prediction
data.outputs	array	Array of URLs to the generated content (empty when status is not `completed`)
data.urls	object	Object containing related API endpoints
data.urls.get	string	URL to retrieve the prediction result
data.has_nsfw_contents	array	Array of boolean values indicating NSFW detection for each output
data.status	string	Status of the task: `created`, `processing`, `completed`, or `failed`
data.created_at	string	ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.error	string	Error message (empty if no error occurred)
data.timings	object	Object containing timing details
data.timings.inference	integer	Inference time in milliseconds

Result Request Parameters

Parameter	Type	Required	Default	Description
id	string	Yes	-	Task ID

Result Response Parameters

Parameter	Type	Description
code	integer	HTTP status code (e.g., 200 for success)
message	string	Status message (e.g., “success”)
data	object	The prediction data object containing all details
data.id	string	Unique identifier for the prediction, the ID of the prediction to get
data.model	string	Model ID used for the prediction
data.outputs	string	Array of URLs to the generated content (empty when status is not completed).
data.urls	object	Object containing related API endpoints
data.urls.get	string	URL to retrieve the prediction result
data.status	string	Status of the task: `created`, `processing`, `completed`, or `failed`
data.created_at	string	ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.error	string	Error message (empty if no error occurred)
data.timings	object	Object containing timing details
data.timings.inference	integer	Inference time in milliseconds

Qwen Image 2512 LoRA Trainer Qwen Image Edit 2511