Topaz vs Magnific vs Crystal — Which AI Upscaler Should You Use?

Topaz Gigapixel wins for faithful photo upscaling on your desktop. Magnific wins for creative upscaling of AI art and low-res illustrations — its creativity slider invents plausible detail. Crystal (Replicate) is the cleanest API-based upscaler, scales up to 200 megapixels, and costs about $0.025 per image. Stack them through your own API keys to avoid two $40+/mo subscriptions.

This is the honest 2026 head-to-head of the three biggest AI upscalers. Each one belongs to a different school — faithful, creative, or programmatic — and the right pick depends entirely on what you are upscaling and where the source came from. The wrong pick will either smooth your photo into plastic or invent a face that is not the face in the original. Below is the section-by-section breakdown by job, with pricing math and a verdict you can act on today.

Which upscaler is best for old photos?

For old family photos and historical archives, Topaz Gigapixel is still the industry leader and it is not particularly close. Three things put it ahead. First, its face recovery model is trained specifically on degraded portrait data — old wedding photos, faded school pictures, scanned passport photos — and it reconstructs eyes, mouths, and skin texture in a way that preserves identity rather than inventing a generic face. Second, it runs locally on your GPU with no API roundtrip, which means no cloud upload of sensitive personal photos. Third, the batch interface lets you process a 200-photo family scan in one drag-and-drop operation.

The catch is the October 2025 pricing change. Topaz Labs moved both Photo AI and Gigapixel to subscription-only billing at $33 to $67 per month, ending perpetual licenses for new buyers. For a working photographer who restores client jobs regularly, that math works. For a one-time family-archive project, it does not — and that is exactly where Crystal becomes the better answer.

Magnific, on old photos, is the wrong tool unless the source is so destroyed that no faithful information remains to recover. The creativity slider will produce a beautiful image — but it will not be the same person.

Which is best for AI art and low-res illustrations?

For AI-generated images and low-resolution illustrations, the calculus inverts. The source has no fine detail to faithfully recover because the source was generated at low resolution to begin with. There is nothing to preserve at the pixel level — what you actually want is for the upscaler to invent plausible new detail consistent with the style of the source.

This is exactly what Magnific was built for. Its creativity slider is the killer feature: at low creativity it behaves like a faithful upscaler, at medium creativity it adds skin pores and fabric weave, and at high creativity it adds entirely new elements — leaves on a tree that the original image showed as a blurred green mass, individual cobblestones where the source had a brown smear. For AI art, low-res illustrations, sketches, and concept art, Magnific produces results that the faithful upscalers simply cannot match because they refuse to invent what is not there.

Crystal also handles AI art well — many photographers use it as the final pass on Nano Banana Pro, Midjourney, and Flux outputs to push them to print resolution. The choice between Magnific and Crystal for AI art comes down to whether you want clean enhancement (Crystal) or stylistic re-imagination (Magnific). Topaz, designed for camera output, is the weakest of the three on AI art — it tends to smooth the painterly quality that made the AI image interesting.

Which is best for product photos and e-commerce?

Product photography sits in the middle of the faithful-vs-creative spectrum. You want sharper detail, but you absolutely cannot invent texture on the product itself — the customer who receives a watch with different lug holes than the listing will return it. Faithful wins for product, and within faithful, Crystal wins on speed and cost.

For a high-volume e-commerce workflow — 50 to 500 product shots per week — Crystal at $0.025 per image is the obvious answer. The API integrates into any image-processing pipeline (Lightroom plugin, Node script, Zapier, custom dashboard), runs in seconds per image, and produces clean output up to 200 megapixels for marketplace listings and large hero banners. Topaz is the desktop alternative if you prefer a GUI batch workflow and your photo team values local processing. Magnific is the wrong tool here — its creative tendency to invent texture will hurt you on products where exact reproduction matters.

How big can each upscale?

Max output matters more for print and large-format work than for screen delivery, but when it matters, it really matters. Here is the honest math.

Crystal leads at up to 200 megapixels per upscale, with 2x to 10x scaling. That is enough for a 24-inch-by-36-inch print at 300 DPI (the gallery-print gold standard), a 40-inch-by-60-inch print at 200 DPI (large-format poster), or a 60-inch-wide banner at 150 DPI (trade-show backdrop). For most working creators, this is the largest output any of the three will produce in a single pass.

Magnific caps lower on standard plans, typically at 64 megapixels, with higher caps on enterprise tiers. The creative invention process is computationally expensive enough that pushing it to Crystal-level output is impractical on the consumer plans.

Topaz Gigapixel scales up to 6x the input. The absolute max depends on your source. A 24-megapixel mirrorless camera file becomes a 144-megapixel print-ready file at full 6x. A 4-megapixel phone photo from 2015 caps at 144 megapixels in the other direction — but the quality at 6x from a low-quality source rarely justifies the math.

The 8x upscale math worth memorizing: a 2000×3000 image upscaled 8x becomes 16000×24000, which is a 16-inch-by-24-inch print at 1000 DPI or a 32-inch-by-48-inch print at 500 DPI. For 95% of print work, you do not need maximum resolution — you need the right resolution at the print size.

Cost-per-image — which is cheapest at scale?

Pricing is where the three tools diverge most. Two different cost models compete: subscription (Topaz, Magnific) and per-image API (Crystal, Magnific API).

The honest takeaway: under 100 upscales per month, Crystal wins decisively — you pay $2.50 to $5.00 total instead of a $33+ subscription. Between 100 and 1,500 per month, it depends on whether you need local processing — Crystal is still cheaper, but Topaz adds the privacy and batch-GUI advantages. Above 1,500 per month, a Topaz subscription wins on amortized cost and you should probably own it anyway as a working photographer.

Magnific's pricing is the trickiest to evaluate because the per-image cost varies with creativity and quality settings. At standard creativity on the Plus tier, you can expect 200–800 images per month before exhausting credits. For creative work where Magnific is the right tool, this is usually fine; for high-volume faithful upscaling, it is the wrong economic match.

Switching between Crystal (faithful) and Magnific (creative) for different jobs means two subscriptions adding up to $80+/mo. Rangy gives you both through your own Replicate and Freepik API keys — no Rangy subscription, pay providers per image. Crystal at ~$0.025 plus Magnific at ~$0.05–$0.20 typically runs $5–$15/mo for moderate use, instead of $80 in stacked monthly subs.

Topaz vs Magnific vs Crystal — head-to-head capabilities table

The cleanest way to see all three side by side, capability by capability.

The pattern is clear: no single tool wins every category. Topaz wins on local face recovery and batch GUI workflow. Magnific wins on creative invention and destroyed-photo reconstruction. Crystal wins on price, max output, and the no-subscription model. The right answer for most working creators is to have at least two of them available — not stacking two subscriptions, but routing each job to the right tool through one workflow.

For the broader category context including Recraft, GFPGAN, Real-ESRGAN, and the open-source alternatives, see our best AI image upscalers in 2026 roundup. For the workflow side of upscaling AI-generated images specifically — print sizing, DPI math, and which model to upscale through — read upscale AI images for print and the broader how to upscale images without losing quality guide. For restoration-adjacent workflows (colorization, scratch removal, denoise), our best AI photo restoration tools rundown covers the full set.

The verdict — which to actually pick

Three honest scenarios. Pick whichever matches your work.

Frequently asked questions

Last updated May 2026. Pricing and rankings change frequently — verify the latest figures on each provider's official page before committing.