We Benchmarked 5 AI Image Upscalers on the Same Photo
Updated · May 3, 2026
The moment a client asks for a print-ready version of a 640×480 JPEG, you start paying close attention to what AI upscalers actually do — versus what they claim. We picked one deliberately tricky test image: a café exterior with a woman sitting at an outdoor table, a chalk menu board visible in the background, and a wall of potted foliage. Skin, text, and organic edges all in a single frame — exactly the tripwires that separate real recovery from confident hallucination. We ran it through five tools and scored the results blind. Here’s the short answer: Topaz Gigapixel AI still leads for photographic accuracy, but Magnific AI outperforms it whenever visual impressiveness matters more than faithfulness to the original.
The setup
One source file, tested five ways: a single 640×480 JPEG exported from a smartphone camera roll, EXIF data stripped, saved at quality 85. Our target was a 4× upscale to 2,560×1,920 pixels — enough for a clean 8×6-inch print at 300 DPI, which is the minimum recommended by most commercial print services for wall-quality output. Every tool ran on its default settings. If a tool offered a specific “photo” mode as a separate option, we ran one pass with defaults and one with photo mode; we scored the photo mode result where applicable.
The five tools in the test: Topaz Gigapixel AI (version 7, standalone desktop app), Adobe Super Resolution accessed through Lightroom Classic on a Creative Cloud photography plan, Magnific AI on its Starter plan, Let’s Enhance on a pay-as-you-go basis, and Upscayl, the free open-source desktop app using its Real-ESRGAN general photo model.
Three team members reviewed each output blind — filenames stripped, images shuffled. We cropped three zones from each result: the woman’s face, the text on the chalk board, and a section of the foliage. Each zone was scored 1–5 on face/skin rendering, edge sharpness, and artifact presence (5 meaning zero visible artifacts). Processing time and effective cost per image were tracked separately.
One limitation worth naming upfront: all local processing ran on a MacBook Pro M3 without an external GPU. Topaz and Upscayl both run faster on Windows machines with a dedicated Nvidia GPU — your speed numbers will differ.
How did the five tools handle faces and skin?
Topaz Gigapixel AI led on face rendering, producing natural skin texture without the plastic smoothing common in lower-tier tools. Magnific AI was visually impressive but occasionally introduced detail that wasn’t in the original source. Adobe Super Resolution was the most conservative — it rarely distorted, but it rarely surprised us positively either. Let’s Enhance and Upscayl both struggled with the face crop, with Upscayl producing results that worked better on foliage than on human subjects.
| Tool | Face rendering (1–5) | Edge sharpness (1–5) | Artifact score (1–5) |
|---|---|---|---|
| Topaz Gigapixel AI | 4.5 | 4.3 | 4.1 |
| Magnific AI | 4.2 | 4.0 | 3.2 |
| Adobe Super Resolution | 3.8 | 3.5 | 4.3 |
| Let’s Enhance | 3.2 | 3.4 | 3.8 |
| Upscayl | 2.8 | 3.6 | 3.3 |
The gap between Topaz and the rest was clearest in the face crop. Topaz preserved the fine transition between the woman’s jawline and the background without either blurring it or introducing ringing. Magnific produced a result that read as sharper at first glance but, under close inspection, had reconstructed some pore texture that didn’t exist in the source. Adobe was clean but soft — like viewing the image through a very thin layer of gauze.
Magnific’s foliage output was genuinely striking. Individual leaves had visible stem structures and what read as subsurface light scatter. The problem: none of that detail was in the original frame. It was invented, confidently, and it looked plausible. Whether that’s a feature depends entirely on what you’re upscaling for.
Where things fell apart: text, edges, and fine detail
The chalk menu board was our stress test for text legibility. The source showed blurred letterforms — readable at a squint, not printable at 8×6. We wanted to see which tools could recover the shapes and which would smooth them into noise.
Topaz handled it best, producing readable text on most of the words with only slight artifacts in the chalk texture. Magnific generated sharper letter edges but hallucinated at least one word mid-board — a character string that changed between the source and the upscaled output. That’s acceptable if the image is decorative. It’s not acceptable if the text needs to be accurate.
Let’s Enhance was the weakest on text by a clear margin, producing blurry letterforms that looked like the source with aggressive sharpening applied on top rather than any real reconstruction. Adobe scored the highest on our artifact metric overall (4.3) — it almost never introduced anything that wasn’t there — but that conservatism cost it on text recovery and skin detail alike.
Upscayl was a different story on the foliage crop. It scored 3.6 on edge sharpness, second only to Topaz, and produced leaf edges that were crisp without obvious ringing. On images without faces or text, the free model holds up respectably.
Which AI upscaler gives you the best value for money?
Adobe Super Resolution is the most cost-effective option if you already pay for Creative Cloud — the feature is already in Lightroom, costs nothing extra, and processes each image in around 20 seconds. Topaz at around $99/year makes sense for anyone regularly rescuing low-resolution photos for print. Magnific AI and Let’s Enhance cost significantly more per image on their base plans, and Upscayl has no per-image cost at all.
| Tool | Processing time | Effective cost per image | Plan used |
|---|---|---|---|
| Topaz Gigapixel AI | ~45 seconds | ~$0.25 | Annual plan (~$99/year) |
| Adobe Super Resolution | ~20 seconds | ~$0.03 | CC Photography (~$20/month) |
| Magnific AI | ~15 seconds | ~$0.08/credit | Starter (~$39/month) |
| Let’s Enhance | ~25 seconds | ~$0.45 | Pay-as-you-go |
| Upscayl | ~90 seconds | $0 | Free / open source |
The Topaz cost-per-image figure assumes around 400 images per year on an annual license. Process more, and it drops. There’s no per-image cap on the desktop plan. Adobe’s figure assumes you’re already a subscriber — if you’re not, it’s not a reason to start.
Let’s Enhance’s pay-as-you-go rate punishes volume work. It makes more sense for one-off rescues than any kind of regular workflow.
What surprised us
Upscayl was slower than Topaz on this hardware, which we hadn’t expected. On the M3 MacBook without a dedicated Nvidia GPU, Upscayl’s Real-ESRGAN model fell back to a slower processing path in our configuration, resulting in an average of around 90 seconds per image. On a Windows machine with a modern GPU, that number would drop significantly — but if you’re on Apple silicon hoping for a quick free option, the wait is real.
Magnific’s cloud processing was the fastest at roughly 15 seconds per image, and it consistently produced results that looked best in a quick thumbnail comparison. The issues only appeared on close inspection of the face and text crops. That pattern suggests it’s optimized for an audience doing first-look reviews at reduced zoom — which, honestly, is most clients. But if you’re submitting work for publication or print proofing, the hallucinated detail matters.
Adobe’s Lightroom integration changed its effective speed entirely. The 20-second processing time doesn’t include the export/import cycles that every other tool in this test requires. Measured from “open the file in editing software” to “upscaled image ready in my folder,” Adobe was faster than everything else by a meaningful margin. That workflow advantage doesn’t show up in raw processing time, but it shows up every day you use it.
The raw verdict
For photographers and designers who need accurate, printable results from low-resolution originals — client photos, archival scans, rescued assets — Topaz Gigapixel AI is still the most reliable tool in this test. It doesn’t invent what isn’t there, and it recovers more usable detail from faces and text than any alternative we ran.
Magnific AI is the right call when the output is going to a screen — a client presentation, a social post, a website hero — and visual impressiveness matters more than strict fidelity to the source. Its hallucinated detail looks good. It just isn’t real.
Adobe Super Resolution is the path of least resistance for anyone already on Creative Cloud. The results are good enough for most use cases, and the workflow savings are real. Upscayl is the best free option — genuinely better than a bicubic resize, genuinely worse than anything with a paid model behind it. Use it when budget is the binding constraint and faces aren’t in the frame.
Frequently asked questions
Can any AI upscaler turn a 640×480 photo into a billboard-quality image?
No. A 4× upscale from 640×480 gets you to 2,560×1,920 — usable for prints up to roughly 8×6 inches at 300 DPI. For larger output, you’re limited by the information in the original file regardless of which tool processes it.
Is Topaz Gigapixel AI worth the subscription cost?
If you regularly upscale photos for print, yes. If you’re only doing it occasionally, Adobe Super Resolution (included with Creative Cloud) or a pay-per-use tool will cost less. The Topaz subscription makes more financial sense above around 50 images per month.
How does Upscayl compare to paid tools for non-photographic content?
Significantly better than its score here suggests. For illustrations, screenshots, and graphic assets with flat colors and sharp lines, Upscayl’s Real-ESRGAN model performs well. The gap between free and paid narrows considerably when there are no faces or fine text involved.
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