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MODEL IDtopazlabs:wonder@4
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Topaz Labs Wonder 4

Topaz Labs
by
Available with Zero Data Retention

Wonder 4 is Topaz Labs' all-purpose generative model for image enhancement and upscaling. It treats each region of an image separately, combining denoising, deblurring, compression artifact removal, face recovery, and upscaling in one pass with no settings to tune. It suits photo restoration, cleanup of degraded or compressed images, and enhancement at the original size or enlarged up to six times, with output up to 256 megapixels.

Topaz Labs Wonder 4

API Options

Platform-level options for task execution and delivery.

taskType

stringrequiredvalue: upscale

Identifier for the type of task being performed.

taskUUID

stringrequiredUUID v4

UUID v4 identifier for tracking tasks and matching async responses. Must be unique per task.

outputType

stringdefault: URL

Image output type.

Allowed values3 values

outputFormat

stringdefault: JPG

Specifies the file format of the generated output. The available values depend on the task type and the specific model's capabilities.

  • `JPG`: Best for photorealistic images with smaller file sizes (no transparency).
  • `PNG`: Lossless compression, supports high quality and transparency (alpha channel).
  • `WEBP`: Modern format providing superior compression and transparency support.
**Transparency**: If you are using features like background removal or LayerDiffuse that require transparency, you must select a format that supports an alpha channel (e.g., `PNG`, `WEBP`, `TIFF`). `JPG` does not support transparency.
Allowed values3 values

outputQuality

integermin: 20max: 99default: 95

Compression quality of the output. Higher values preserve quality but increase file size.

webhookURL

stringuri

Webhook URL that receives JSON responses via HTTP POST when generation tasks complete. For batch requests with multiple results, each completed item triggers a separate webhook call as it becomes available.

Learn more1 resource

deliveryMethod

stringdefault: sync

Determines how the API delivers task results.

Allowed values2 values
Returns results directly in the API response. Over HTTP, a task still running after 120 seconds continues as an async task and comes back with status 'processing'. Poll for its results using getResponse.
Returns an immediate acknowledgment with the task UUID. Poll for results using getResponse.
Learn more1 resource

uploadEndpoint

stringuri

Specifies a URL where the generated content will be automatically uploaded using the HTTP PUT method. The raw binary data of the media file is sent directly as the request body. For secure uploads to cloud storage, use presigned URLs that include temporary authentication credentials.

Common use cases:

  • Cloud storage: Upload directly to S3 buckets, Google Cloud Storage, or Azure Blob Storage using presigned URLs.
  • CDN integration: Upload to content delivery networks for immediate distribution.
// S3 presigned URL for secure upload
https://your-bucket.s3.amazonaws.com/generated/content.mp4?X-Amz-Signature=abc123&X-Amz-Expires=3600

// Google Cloud Storage presigned URL
https://storage.googleapis.com/your-bucket/content.jpg?X-Goog-Signature=xyz789

// Custom storage endpoint
https://storage.example.com/uploads/generated-image.jpg

The content data will be sent as the request body to the specified URL when generation is complete.

ttl

integermin: 60

Time-to-live (TTL) in seconds for generated content. Only applies when outputType is URL.

includeCost

boolean

Include task cost in the response.

routing

object

Model router options. Only read when model is auto, and never sent to the model.

Properties5 properties
routing » allowedModels

allowedModels

array of stringsmin items: 2

Models the router may choose from. Nothing outside this list is considered, so a request none of them can serve is refused.

routing » excludedModels

excludedModels

array of stringsmin items: 1

Models the router may not choose. Every other model stays a candidate.

routing » preferences

preferences

object

Relative importance of each dimension when models are compared. Weights, not thresholds.

Properties3 properties
routing » preferences » quality
quality
integermin: 0max: 5

Importance of one dimension. 0 leaves it out of the decision.

routing » preferences » speed
speed
integermin: 0max: 5

Importance of one dimension. 0 leaves it out of the decision.

routing » preferences » cost
cost
integermin: 0max: 5

Importance of one dimension. 0 leaves it out of the decision.

routing » maxPrice

maxPrice

floatmin: 0

Upper bound on what this request may cost, in USD. A model whose cost cannot be bounded is not chosen.

routing » requirements

requirements

stringmax: 3000

Conditions the result has to meet, in plain words, such as a style or a feature. A model that cannot meet them is not chosen. Output size is set with width and height rather than described here.

Inputs

Input resources for the task (images, audio, etc). These must be nested inside the inputs object.

inputs » image

image

stringrequired2 limits

Image input (UUID, URL, Data URI, or Base64).

Core Parameters

Primary parameters that define the task output.

model

stringrequiredvalue: topazlabs:wonder@4

Send auto instead of an AIR identifier to have the model router choose the model for this task. The rest of the request is unchanged, every value you send is kept, and only the parameters you leave out are filled in. See Model Router.

Learn more3 resources

upscaleFactor

integermin: 1max: 6default: 2

Factor by which to upscale the generated image. A value of 2 doubles width and height. The output must not exceed 256 megapixels or 32000 pixels per side.

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