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Topaz Gigapixel AI Pro

A dedicated image upscaler that enlarges photographs several times over while rebuilding the detail a plain resize would smear, using trained models tuned for faces, landscapes, and low resolution originals.

Version 8.4.4 1.48 GB Windows 10 / 11 (64-bit) Updated 4 days ago

Overview

What this release is

Gigapixel does one thing and does it better than a general editor's resize command: it makes a small image large without turning it to mush. A conventional enlargement simply spreads the existing pixels, so the result is soft. Gigapixel instead uses trained models to infer the detail that a higher resolution capture would have held, rebuilding edges, texture, and structure as it scales.

The gain is most obvious on the hard cases. An old scan, a heavily cropped frame, or a low resolution export can be pushed to several times its original size and come out looking like it was shot larger, with hair, foliage, and fabric reconstructed rather than blurred. For print work from small originals, that is the difference between usable and not.

The model selection is what keeps the results honest. Separate models are tuned for faces, for landscapes and general photography, for compressed low quality sources, and for line art, so the program applies the reconstruction appropriate to the content instead of one blunt filter. Face recovery in particular rebuilds features that a generic upscaler would invent badly.

Batch processing handles a whole folder in one run, and the Pro build enables the full model set and the largest output sizes from first launch without a trial limit.

Feature set

What you get

Detail reconstruction

Rebuilds edges and texture while enlarging rather than spreading existing pixels into softness.

Model selection

Separate models for faces, general photography, low quality sources, and line art.

Face recovery

Reconstructs facial detail on small or soft originals instead of inventing it crudely.

Large output sizes

Push an image to several times its original resolution for print from small sources.

Batch processing

Enlarge a whole folder in one run with a chosen model and output size.

Standalone or plugin

Runs on its own or as a filter called from a host editor.

Changes in this build

What changed

  • Updated the face recovery model for more natural detail
  • Faster processing on machines with a capable graphics card
  • Improved handling of heavily compressed low quality sources
  • Added finer control over the amount of detail added
  • Fixed the batch run stalling on a folder containing unsupported files

Installation

How to install it

  1. Disable real time protection before extracting the archive.
  2. Extract to a short path and run setup as administrator.
  3. Do not open the program before applying the included registration step.
  4. Start the program and confirm the Pro model set shows no trial badge.
  5. Block outbound access for the executable if you want the registered state to hold.

Hardware

System requirements

ProcessorIntel or AMD, 64-bit, multi-core
Memory8 GB minimum, 16 GB for large images
Graphics4 GB VRAM recommended for accelerated processing
Storage4 GB install plus output space
Display1920 x 1080
SystemWindows 10 version 22H2 or Windows 11

Package

Release information

TitleTopaz Gigapixel AI Pro
Version8.4.4
DeveloperTopaz Labs
CategoryPhoto Editing
PlatformWindows 10 / 11 (64-bit)
Package size1.48 GB
Interface languagesEnglish
Release identifierBS-84040001
Listed1 year ago
Last rebuilt4 days ago
Total downloads581,835

Questions

Before you start

How large can an image be enlarged?

Several times the original in each dimension. The practical limit depends on how much real detail the source held.

Does it need a graphics card?

No, but one speeds processing considerably. On the processor alone it works, more slowly.

Can it run inside another editor?

Yes, as a plugin filter from a host that supports external filters, as well as standalone.

Why does a face look slightly off?

Select the face model for portraits. The general model does not reconstruct facial detail as convincingly.

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