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Topaz Gigapixel AI

Topaz Gigapixel AI Review: Image Upscaling & Portrait Enhancement Tested (2026)

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Tested Hands-OnAI Image UpscalingPortrait EnhancementProfessional EditorialLast verified April 2026

Our take

Topaz Gigapixel AI is the industry-standard tool for professional editorial upscaling, referenced directly in photography workflows and publishing use cases. The Preserve face toggle and adjustable Sharpen/Denoise sliders give editors more control than any other tested tool. It requires more configuration than fully automatic tools, which adds steps under deadline pressure, but the output quality on portraits justifies it.

Download video: Demo videoWatch video (streaming): Demo video

In-Depth Review

Our detailed analysis of Topaz Gigapixel AI — features, performance, and real-world testing.

AJ
Athulya Jaikish
AI Demos Team
Verified Review

Feature-by-Feature Breakdown

We tested each feature individually. Click any card to see inputs, outputs, and our observations.

Standard V2 Model
8/10
▾
Test Summary
Feature tested: Standard V2 Model
Result: Passed (8/10)

Feature tested: Standard V2 Model

Result: Passed (8/10)

Expected behavior: Claims to deliver balanced enhancement of detail, sharpness, and denoising across all image types.

Test case: Image → Image

Input type: Image

Input used: Input artifact (Image): Input — Input 1 - Headshot-9.png

Observed output: Output artifact (Image): Output — Screenshot 2026-04-23 150022-2.png

Input artifact: Input artifact (Image): Input — Input 1 - Headshot-9.png

Output artifact: Output artifact (Image): Output — Screenshot 2026-04-23 150022-2.png

What changed: Image transformed into Image

Test case: Image → Image

Input type: Image

Input used: Input artifact (Image): Input — Input 1 - Headshot-12.png

Observed output: Output artifact (Image): Output — image (1)-5.png

Input artifact: Input artifact (Image): Input — Input 1 - Headshot-12.png

Output artifact: Output artifact (Image): Output — image (1)-5.png

What changed: Image transformed into Image

Why it matters / Conclusion: Standard V2 is the best default choice for clean portrait and product inputs. Consistent, natural output with no hallucination.

Claims to deliver balanced enhancement of detail, sharpness, and denoising across all image types.

IMAGE
Input artifact for "Standard V2 Model" test: Input, Input 1 - Headshot-9.png
↓
IMAGE
Output artifact for "Standard V2 Model" test: Output, Screenshot 2026-04-23 150022-2.png
IMAGE
Input artifact for "Standard V2 Model" test: Input, Input 1 - Headshot-12.png
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IMAGE
Output artifact for "Standard V2 Model" test: Output, image (1)-5.png
Bottom Line
Standard V2 is the best default choice for clean portrait and product inputs. Consistent, natural output with no hallucination.
Archival Image Upscaling (Standard V2)
7.5/10
▾
Test Summary
Feature tested: Archival Image Upscaling (Standard V2)
Result: Passed (7.5/10)

Feature tested: Archival Image Upscaling (Standard V2)

Result: Passed (7.5/10)

Expected behavior: No dedicated archival model available. Standard V2 used for degraded greyscale inputs.

Test case: Image → Image

Input type: Image

Input used: Input artifact (Image): Input — Input 2 - Historic_photo-8.png

Observed output: Output artifact (Image): Output — Screenshot 2026-04-23 150138-2.png

Input artifact: Input artifact (Image): Input — Input 2 - Historic_photo-8.png

Output artifact: Output artifact (Image): Output — Screenshot 2026-04-23 150138-2.png

What changed: Image transformed into Image

Test case: Image → Image

Input type: Image

Input used: Input artifact (Image): Input — Input 2 - Historic_photo-7.png

Observed output: Output artifact (Image): Output — image (2)-8.png

Input artifact: Input artifact (Image): Input — Input 2 - Historic_photo-7.png

Output artifact: Output artifact (Image): Output — image (2)-8.png

What changed: Image transformed into Image

Why it matters / Conclusion: Strong structural detail recovery without dedicated archival model. Grain managed conservatively. Lacks the purpose-built archival restoration capability of LetsEnhance's Old photo model.

No dedicated archival model available. Standard V2 used for degraded greyscale inputs.

IMAGE
Input artifact for "Archival Image Upscaling (Standard V2)" test: Input, Input 2 - Historic_photo-8.png
↓
IMAGE
Output artifact for "Archival Image Upscaling (Standard V2)" test: Output, Screenshot 2026-04-23 150138-2.png
IMAGE
Input artifact for "Archival Image Upscaling (Standard V2)" test: Input, Input 2 - Historic_photo-7.png
↓
IMAGE
Output artifact for "Archival Image Upscaling (Standard V2)" test: Output, image (2)-8.png
Bottom Line
Strong structural detail recovery without dedicated archival model. Grain managed conservatively. Lacks the purpose-built archival restoration capability of LetsEnhance's Old photo model.
Product Image Upscaling
8/10
▾
Test Summary
Feature tested: Product Image Upscaling
Result: Passed (8/10)

Feature tested: Product Image Upscaling

Result: Passed (8/10)

Expected behavior: Claims to upscale product photography with preserved edge sharpness, surface texture fidelity, and label text legibility using the Standard V2 model.

Test case: Image → Image

Input type: Image

Input used: Input artifact (Image): Input — Input 3 - Product_image-4.png

Observed output: Output artifact (Image): Output — Screenshot (230)-1.png

Input artifact: Input artifact (Image): Input — Input 3 - Product_image-4.png

Output artifact: Output artifact (Image): Output — Screenshot (230)-1.png

What changed: Image transformed into Image

Why it matters / Conclusion: Strong product upscaling result. Full label text — "MĀRY & MAY", "Idebenone + Blackberry complex", "Serum", ingredient list, and volume — all legible on the right side of the fullscreen comparison. Clean white background preserved with no noise. Bottle edges and glass surface reflections rendered cleanly with no haloing. 4x recommended for print catalogue use.

Claims to upscale product photography with preserved edge sharpness, surface texture fidelity, and label text legibility using the Standard V2 model.

IMAGE
Input artifact for "Product Image Upscaling" test: Input, Input 3 - Product_image-4.png
↓
IMAGE
Output artifact for "Product Image Upscaling" test: Output, Screenshot (230)-1.png
Bottom Line
Strong product upscaling result. Full label text — "MĀRY & MAY", "Idebenone + Blackberry complex", "Serum", ingredient list, and volume — all legible on the right side of the fullscreen comparison. Clean white background preserved with no noise. Bottle edges and glass surface reflections rendered cleanly with no haloing. 4x recommended for print catalogue use.
Preserve Face Toggle, Sharpen and Denoise Sliders
7/10
▾
Test Summary
Feature tested: Preserve Face Toggle, Sharpen and Denoise Sliders
Result: Passed (7/10)

Feature tested: Preserve Face Toggle, Sharpen and Denoise Sliders

Result: Passed (7/10)

Expected behavior: Claims to prevent face distortion during upscaling by applying face-specific processing to portrait regions. Allows the editor to adjust sharpening intensity and noise reduction independently. Both default to 50, adjustable per image.

Test case: Image → Image

Input type: Image

Input used: Input artifact (Image): Input — Input 1 - Headshot-11.png

Observed output: Output artifact (Image): Output — Screenshot (229)-2.png

Input artifact: Input artifact (Image): Input — Input 1 - Headshot-11.png

Output artifact: Output artifact (Image): Output — Screenshot (229)-2.png

What changed: Image transformed into Image

Why it matters / Conclusion: Preserve face is the strongest portrait-specific feature of any tool tested. Directly prevents the plastic skin effect common in AI upscaling. Recommended on for all portrait editorial inputs. The most granular enhancement controls of any tool tested. Requires manual judgment per image type but gives editors direct control over output quality

Claims to prevent face distortion during upscaling by applying face-specific processing to portrait regions. Allows the editor to adjust sharpening intensity and noise reduction independently. Both default to 50, adjustable per image.

IMAGE
Input artifact for "Preserve Face Toggle, Sharpen and Denoise Sliders" test: Input, Input 1 - Headshot-11.png
↓
IMAGE
Output artifact for "Preserve Face Toggle, Sharpen and Denoise Sliders" test: Output, Screenshot (229)-2.png
Bottom Line
Preserve face is the strongest portrait-specific feature of any tool tested. Directly prevents the plastic skin effect common in AI upscaling. Recommended on for all portrait editorial inputs. The most granular enhancement controls of any tool tested. Requires manual judgment per image type but gives editors direct control over output quality
Scale Factor (Up to 8x)
7/10
▾
Test Summary
Feature tested: Scale Factor (Up to 8x)
Result: Passed (7/10)

Feature tested: Scale Factor (Up to 8x)

Result: Passed (7/10)

Expected behavior: Offers 1x, 2x, 4x, 6x, and 8x scale options.

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Three low resolution input images.

Observed output: Output artifact (Image): Output — Screenshot (226)-1.png

Input artifact: Input artifact (Text prompt): Three low resolution input images.

Output artifact: Output artifact (Image): Output — Screenshot (226)-1.png

What changed: Text prompt transformed into Image

Offers 1x, 2x, 4x, 6x, and 8x scale options.

TEXT
Three low resolution input images.
↓
IMAGE
Output artifact for "Scale Factor (Up to 8x)" test: Output, Screenshot (226)-1.png

Use Case Track Record

Enhance and Upscale Images from Low-Resolution Inputs

Pricing & Access

TESTED
Free credits
$ 0
10 crefits available in free trial
Topaz Studio
$37 /month
All the apps, Unlimited local rendering, Unlimited cloud image rendering, 300 monthly video cloud credits, 2—image cloud concurrency, 32MP cloud export limit*, Limited commercial use*,
Topaz Studio Pro
$ 75 / month
All the apps (Pro licenses) Unlimited local rendering Unlimited cloud image rendering 600 monthly video cloud credits 4—Image cloud concurrency 100MP cloud export limit* Full commercial use Seat management

* Pricing as of April 2026. We re-check quarterly

Is This Right For You?

A side-by-side guide based on our hands-on testing.

✓ Use This If
●Portrait detail fidelity is a priority — you need natural skin, eye, and hair recovery
●You want fine-grained control over sharpening and denoising per image
●You work with a mix of portrait, archival, and product inputs
●You need scale factors up to 8x for large format print
●You are comfortable with a semi-manual configuration workflow
✕ Skip This If
●You need a fully automatic one-click workflow with no configuration
●You work primarily with archival or degraded historical images and need a dedicated restoration model
●You need DPI explicitly confirmed in the interface
●You need TIFF input confirmed as supported
●You are on a tight free tier credit budget
image-editingtext-to-imagetextEditors
No dedicated archival or Old photo model was available during testing. Standard V2 was used for the archival scan input and produced clean results, but it does not apply the conservative grain management of a purpose-built restoration model.
Preserve face applies face-specific processing to portrait regions during upscaling, preventing distortion of facial features. In our testing, it produced noticeably more natural skin texture and eye detail compared to upscaling without it.
Both default to 50 on a 0–100 scale. Both are fully adjustable. For archival inputs, lowering Sharpen and increasing Denoise produced cleaner grain management. For clean portraits, the defaults gave natural results.
4x is recommended for most editorial print use cases. 2x is sufficient for web publishing and large-format digital display. For very large print formats, 6x or 8x is available.
Topaz Labs offers desktop apps and plugins for Lightroom and Photoshop as part of the Topaz Photo AI suite. The web app tested here does not require software installation but the plugin offers tighter workflow integration for editors already in Lightroom or Photoshop.

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