# Topaz Gigapixel v1.1.0 — Topaz Gigapixel v1.1.0 - v1.1.1

- Product: Topaz Gigapixel (https://whatsnew.fyi/product/topaz-gigapixel)
- Vendor: Topaz Labs
- Date: 2026-01-23
- Version: v1.1.0
- Original notes: https://community.topazlabs.com/t/topaz-gigapixel-v1-1-0-v1-1-1/100363
- Permalink: https://whatsnew.fyi/product/topaz-gigapixel/releases/v1.1.0
- Labels: Platforms: Windows, macOS

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Hello! Today we’re excited to release Topaz Gigapixel v1.1.0 , an update focused on expanding our generative model lineup , refining the Cloud rendering workflow , and delivering a number of important…

- **added** — Added Wonder 2 model for cloud rendering focused on precision detail, realistic enhancement of faces and skin textures, and minimization of artificial-looking patterns
- **added** — Added Recover 3 model for soft and realistic enhancement, available on Windows for local rendering and on macOS for cloud rendering
- **added** — Added Download All button to Cloud Queue to download all completed renders in the background at once
- **added** — Added Cloud Queue access directly from the Import page
- **changed** — Updated File List to display which generative model was used, associated model settings, and quick hover access to Redefine prompts
- **changed** — Updated Image AI model
- **changed** — Improved error handling and status updates for Cloud rendering
- **changed** — Implemented automatic Lensfun updates
- **fixed** — Fixed HEIC loading issues in some cases
- **fixed** — Fixed plugin dialog not appearing
- **fixed** — Fixed potential crashes in model downloader
- **fixed** — Fixed longest edge preferences not sticking
- **fixed** — Fixed Cloud queue naming and refresh issues
- **fixed** — Fixed cloud thumbnails in most cases
- **fixed** — Fixed cloud filenames being incorrect on upload
- **fixed** — Fixed cloud uploads not being deleted in some cases
- **fixed** — Fixed cloud errors displaying wrong model name
- **fixed** — Fixed TIFF file error handling in Cloud Compare tool
- **fixed** — Fixed cloud uploads sometimes deleting files incorrectly
- **added** — Restored New Features dialog with updated slides

Hello!
Today we’re excited to release Topaz Gigapixel v1.1.0, an update focused on expanding our generative model lineup, refining the Cloud rendering workflow, and delivering a number of important fixes and quality-of-life improvements.
Thanks again for being part of the Topaz Gigapixel community
As always, we’d love to hear your feedback.
Esther H.
Topaz Labs
Topaz Gigapixel v1.1.1
Windows: [[Download]](https://downloads.topazlabs.com/deploy/TopazGigapixel/1.1.1/TopazGigapixel-1.1.1.msi)
Mac: [[Download]](https://downloads.topazlabs.com/deploy/TopazGigapixel/1.1.1/TopazGigapixel-1.1.1.pkg)
Snapdragon: [[Download]](https://downloads.topazlabs.com/deploy/TopazGigapixel/1.1.1/TopazGigapixel-arm64-1.1.1.msi)
Released on January 23, 2026
Topaz Gigapixel v1.1.0
Windows: [[Download]](https://downloads.topazlabs.com/deploy/TopazGigapixel/1.1.0/TopazGigapixel-1.1.0.msi)
Mac: [[Download]](https://downloads.topazlabs.com/deploy/TopazGigapixel/1.1.0/TopazGigapixel-1.1.0.pkg)
Snapdragon: [[Download]](https://downloads.topazlabs.com/deploy/TopazGigapixel/1.1.0/TopazGigapixel-arm64-1.1.0.msi)
Released on January 22, 2026
Wonder 2 — Precision Detail Without the “AI Look” (Cloud Only)
Wonder 2 is an evolution of the original Wonder model, redesigned to focus on precision and realism—especially in faces, skin textures, and fine surface detail.
The goal with Wonder 2 is to aim for:
- Restore fine facial and texture detail
- Recovers text, logos, and signage
- Reduce artificial-looking patterns
- Minimize generative artifacts
- Improve overall quality compared to Wonder 1
Key things to know
- Cloud render only for Topaz Gigapixel
- Single-step model with no preview controls
- Best results when upscaling 4×
- Not recommended for low-light phone images with heavy noise
Wonder 1 vs Wonder 2 results & false resolution
If you’ve experienced getting good results with Wonder 1 but not with Wonder 2, there is a chance your image may have false resolution. This is common with images from scanners, screen captures, or online sources. False resolution happens when an image is upscaled—its pixel dimensions are increased without adding real detail. The image looks large, but the extra pixels are interpolated and don’t contain true information.
You can spot false resolution by viewing the image at 100% (actual size). If you see compression blocks, pixel stepping, or artifacts in areas that should be smooth, the image likely has false resolution.
Workaround:
Try downscaling the image first. Downscaling can be done in a different image editor. Downscaling removes excess fake pixels and condenses the real detail, which often leads to clearer results when processing the image in Topaz Gigapixel with Wonder 2.
Recover 3 — Our Most Natural Enhancement Model Yet
Recover 3 is built for users who want soft, realistic enhancement rather than aggressive detail reconstruction. It shines especially with:
- Fur and feathers
- Natural textures that benefit from subtle recovery
Unlike Wonder 2, Recover 3 is designed to be a general-purpose enhancement model rather than a precision generative tool.
Availability
- Windows: Local + Cloud
- macOS: Cloud only (local support coming later)
How to Use
- Select the Recover model
- Selec the version from the dropdown menu and select “Recover 3”
- Choose a strength mode (Low/Med/High) - the app defaults the Medium option as the best balanced enhancement. The strength mode controls the intensity of the detail enhanced.
Recommended usage
- Optimal input size: 1024 × 1024 or smaller
- Larger images are supported, but renders more slowly
- Not recommended for highly structured or high-grain images
Updated File List
We’ve updated the File List to better reflect generative workflows.
You’ll now see:
- Which generative model was used
- Any associated model settings
- Quick hover access to Redefine prompts
This makes it much easier to review how an image was processed—especially when mixing Core and Generative models.
Cloud Queue — Small Work

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