> For the complete documentation index, see [llms.txt](https://developer.topazlabs.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://developer.topazlabs.com/image-models/upscaling-and-enhancement/generative/wonder-4.md). # Wonder 4 Our most advanced all-purpose image model for automatic enhancement, restoring focus and faces, denoising, restoration, and upscaling at any resolution.
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### Model Overview **Wonder 4** is our most advanced all-in-one model for enhancement and upscaling, designed to automatically improve image quality in one step without manual adjustments. From low-resolution photos to high-resolution images, Wonder 4 intelligently identifies and corrects noise, blur, compression artifacts, image damage, and facial details, while preserving natural textures. Wonder 4 uses a new mixture-of-experts architecture trained to intelligently identify and correct multiple image problems at once. Unlike traditional models that apply the same corrections across an entire image, Wonder 4 analyzes each region independently and applies the enhancements it needs. This intelligent approach delivers superior results in a single pass, without chaining multiple models. ### Best Use Cases * **All-in-one enhancement:** Automatically combines upscaling, denoising, deblurring, compression artifact removal, and face recovery in a single pass, with no parameters or manual adjustments. * **Intelligent region-based processing:** Uses a mixture-of-experts architecture to identify and apply the appropriate corrections to different areas of an image. * **Superior image quality:** Delivers higher-quality results than Wonder 3.5 and more cohesive enhancement than chaining multiple specialized models together, while preserving natural textures and detail. * **Low- and high-resolution support:** Enhances a wide range of images, from low-quality photos and damaged scans to high-resolution sources. ### Endpoint `https://api.topazlabs.com/image/v1/enhance-gen/async` ### Model Parameters | Parameter | Type | Required / Default | Accepted values | Description | | --------- | -------- | ------------------ | --------------- | ----------- | | `model` | `string` | Required | `"Wonder 4"` | — | For request parameters shared by every image endpoint, see [Request Parameters](/getting-started/request-parameters/image.md). The full schema is also available in our [API Reference](https://app.gitbook.com/o/HctdcUHRfIWXBVA1egPp/s/dQjJSfrAUC693PLetlIA/) page. ### Model Pricing **Wonder 4** costs 1 credit per every 8 MP of generated output. The below table includes a list of common output resolutions with associated credit costs. | Resolution | Typical Source | Output MP | Credits | | ---------- | -------------------- | --------- | ------- | | 640×480 | VGA | 0.31 | 1 | | 1280×720 | 720p | 0.92 | 1 | | 1920×1080 | 1080p | 2.07 | 1 | | 2560×1440 | 1440p | 3.69 | 1 | | 3840×2160 | 4K UHD | 8.29 | 2 | | 4000×3000 | 12 MP phone | 12.00 | 2 | | 5472×3648 | 20 MP camera | 19.96 | 3 | | 6000×4000 | 24 MP camera | 24.00 | 3 | | 7680×4320 | 8K UHD | 33.18 | 5 | | 7952×5304 | 42 MP camera | 42.18 | 6 | | 8192×5464 | 45 MP camera | 44.76 | 6 | | 9504×6336 | 61 MP camera | 60.22 | 8 | | 11648×8736 | 100 MP medium format | 101.76 | 13 | | Output MP | 1 | 4 | 8 | 16 | 24 | 32 | 40 | | --------- | - | - | - | -- | -- | -- | -- | | Credits | 1 | 1 | 1 | 2 | 3 | 4 | 5 | {% hint style="info" %} For more accurate credit cost estimates, we recommend using our [Credit Calculator](https://developer.topazlabs.com/credit-calculator). {% endhint %} ### Example Request {% tabs %} {% tab title="cURL" %} ```bash curl -X POST "https://api.topazlabs.com/image/v1/enhance-gen/async" \ -H "X-API-Key: $TOPAZ_API_KEY" \ -F "image=@photo.jpg" \ -F "model=Wonder 4" ``` {% endtab %} {% tab title="JavaScript" %} ```javascript import fs from 'fs'; import FormData from 'form-data'; const form = new FormData(); form.append("image", fs.createReadStream("photo.jpg")); form.append("model", "Wonder 4"); const response = await fetch("https://api.topazlabs.com/image/v1/enhance-gen/async", { method: 'POST', headers: { 'X-API-Key': process.env.TOPAZ_API_KEY, ...form.getHeaders(), }, body: form, }); if (!response.ok) { throw new Error(`Request failed: ${response.status} ${await response.text()}`); } console.log(await response.json()); ``` {% endtab %} {% tab title="Python" %} ```python import os import requests with open("photo.jpg", "rb") as image: response = requests.post( "https://api.topazlabs.com/image/v1/enhance-gen/async", headers={"X-API-Key": os.environ["TOPAZ_API_KEY"]}, files={"image": image}, data={ "model": "Wonder 4" }, ) response.raise_for_status() print(response.json()) ``` {% endtab %} {% endtabs %} ### Limitations This model accepts up to 256 MP input and output. ### Helpful Resources
:play:

Image Quickstart

Quickly get started with our Image API.
:codepen:

Model Playground

Test and create with our models.https://playground.topazlabs.com/
:square-root-variable:

Credit Calculator

Pricing for specific outputs, batches, and more.
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