Alibaba Wan 2.5 Image Edit

Playground

Refine existing visuals with Alibaba WAN 2.5 image-edit using prompt-driven adjustments and stylistic upgrades for photos and graphics. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Alibaba WAN 2.5 Image Edit

Alibaba WAN 2.5 Image Edit enables you to upload an existing visual and specify the desired adjustments. The model preserves layout and subject structure while implementing high-quality updates based on natural language.

Why creators love it

Structure-preserving edits: Make lighting, color, or object changes without breaking composition.
Text-guided styling: Reimagine materials, moods, or art styles with concise prompts.
Prompt expansion on demand: Enable automatic prompt enrichment when you need extra detail.
Flexible output sizes: Pick the resolution that best matches your downstream workflow.

Perfect for

Marketing and design teams refining campaign visuals.
E-commerce sellers upgrading product imagery.
Content creators polishing thumbnails, covers, and posts.
Artists experimenting with variations of their original work.

Pricing

Every edit is just $0.03!!!

Billing rules

Minimum charge: 1 image.
Total cost = number of images × price per resolution.

How to use

Provide the image you want to refine. (Image dimensions must be in (384, 5000))
Describe the desired adjustments in the prompt.
Choose the target resolution and submit.
Review the enhanced output and download the version you like best.

Pro tips

Start with clear instructions about colors, lighting, or objects to adjust.
Pair positive and negative prompts to control what should or should not appear.
Keep source images at or above your target resolution for optimal fidelity.

Note

If you did not upload the image locally, please ensure that the image URL is accessible! A successfully accessible image will display a preview in the interface.

Recommended Resolutions

Aspect Ratio	Exact (W×H)	Exact Pixels	Rounded (W×H, ÷64)	Rounded Pixels
1:1	1448 × 1448	2,096,704	1408 × 1408	1,982,464
3:2	1773 × 1182	2,095,686	1728 × 1152	1,990,656
4:3	1672 × 1254	2,096,688	1664 × 1216	2,023,424
16:9	1936 × 1089	2,108,304	1920 × 1088	2,088,960
21:9	2212 × 948	2,096,976	2176 × 960	2,088,960
1:1	1024 × 1024	1,048,576	1024 × 1024	1,048,576
3:2	1254 × 836	1,048,344	1216 × 832	1,011,712
4:3	1182 × 887	1,048,434	1152 × 896	1,032,192
16:9	1365 × 768	1,048,320	1344 × 768	1,032,192
21:9	1564 × 670	1,047,880	1536 × 640	983,040
1:1	323 × 323	104,329	320 × 320	102,400
3:2	397 × 264	104,808	384 × 256	98,304
4:3	374 × 280	104,720	448 × 320	143,360
16:9	432 × 243	104,976	448 × 256	114,688
21:9	495 × 212	104,940	576 × 256	147,456

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/alibaba/wan-2.5/image-edit" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "seed": -1
}'

# 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.
negative_prompt	string	No		-	The negative prompt for the generation.
images	array	Yes	[]	1 ~ 2 items	List of URLs of input images for editing. The maximum number of images is 2.
seed	integer	No	-1	-1 ~ 2147483647	The random seed to use for the generation. -1 means a random seed will be used.

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	object	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

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