Photoshop Super Zoom vs Let's Enhance Prime: face upscaling comparison
Enhancing a portrait is one of the hardest things to do well. Faces are uniquely unforgiving: people have spent their whole lives reading facial features, so even subtle distortions or smoothing artifacts register as "something's off" before the viewer can articulate why.
Both Photoshop's Super Zoom neural filter and Let's Enhance Prime claim to handle this. Both use AI. But they were built with different goals, workflows, and assumptions about what "good" looks like. We ran the same images through both tools to see how each performs.
Key takeaways
- Photoshop Super Zoom works best as a sharpening assist on images that are already decent quality. It tends to produce mushy, artifact-heavy results on severely degraded inputs.
- Let's Enhance Prime is purpose-built for texture preservation. On the same low-resolution portrait, it produced natural skin texture and a recognizable face.
- The workflow gap is real: Super Zoom requires Photoshop (a full subscription), several navigation steps, and offers limited control. Prime requires an account, one upload, and no decisions beyond output size.
- Neither tool is the answer in every case. Super Zoom fits inside an existing Adobe editing pipeline; Prime fits when output quality is the primary goal.
Super Zoom vs Prime: what each tool does
Photoshop Super Zoom
Super Zoom is a neural filter inside Adobe Photoshop, accessible through Filter > Neural Filters. It uses Adobe Sensei, Adobe's machine learning platform, to add detail to an upscaled crop of the image. Each click of the zoom icon increases the scale by 1x. You can also enable optional passes like JPEG artifact removal, noise reduction, sharpening, and face enhancement, though as we'll show, some of these can make results worse rather than better.
Super Zoom processes in the cloud and requires an internet connection. It has been part of Photoshop since the Neural Filters panel was introduced, making it available to anyone on an active Creative Cloud subscription (Photoshop alone starts around $22/month).
The tool is designed as part of a full editing workflow, not a standalone upscaler. That matters for how you interpret its results.
Pricing: Included with Photoshop (Creative Cloud subscription, ~$22/month for Photoshop only; $57/month for the full suite).
Let's Enhance Prime
Prime is Let's Enhance's default upscaling model. It's a web-based tool, no installation required, and it's selected automatically when you upload an image. The underlying approach differs from Super Zoom in a meaningful way: Prime treats your original image as ground truth and enhances what's already there, rather than synthesizing replacement details. The focus is on preserving skin pores, fabric grain, fine lines, and natural imperfections, including the kinds of imperfections that make a face recognizable.
It supports upscaling up to 16x with a maximum output of 512 megapixels. Processing happens in the cloud. There are no sliders or manual controls in Prime; the model makes the call on enhancement intensity. For cases where you want more AI intervention, Let's Enhance also has Strong and Ultra models. For minimal processing, there's a Gentle mode.
New users get 10 free credits on sign-up, which covers testing several images. Paid plans start at $9/month, and most typical upscales cost 1–2 credits.
Pricing: Free trial (10 credits on sign-up). Paid plans start at $9/month. Pay-as-you-go bundles also available.
Side-by-side results: the same portrait through both tools
Words about upscaling are less useful than images. Here's what we actually saw.
We started with a heavily pixelated, blurry 200×112 px portrait of a man and upscaled it 8x using both tools.
With Photoshop, the output showed significant image artifacts across the face. Skin texture was replaced with an unnatural, painted-looking surface. The eyes, were unclear and mushy. The person was not immediately recognizable. Enabling the optional face enhancement pass made things worse in this case, adding further distortion rather than correcting it. The result looked more like an illustration than a photograph.
Let's Enhance, on the other hand, produced natural skin texture with realistic-looking pores and fine lines. The face was clear. The person was recognizable. The result had the quality of a photograph taken in higher resolution, not of an AI-enhanced image. Skin tones were preserved, features were stable, and there were no painting-like artifacts. At 8x from a 200px source, Prime handled the gap between input and output far more gracefully.
To test if Super Zoom will perform better, we repeated the test with a better source image (640×358 px → 8x).
The result is noticeably better than the first test. The mushy quality reduced, fewer artifacts were visible, and the image looked more like a photograph. The overall result was still softer, less defined and the face lacked the clarity and micro-detail.
With that being said, Super Zoom's quality is more dependent on the quality of the source image. It performs closer to its best when the original is sharp and the upscale factor is moderate. Let's Enhance Prime handles degraded inputs more robustly, which matters a lot when the whole reason you need an upscaler is that your original isn't good.
Step-by-step: how to use each tool
Using Let's Enhance Prime
Step 1: Sign up or sign in at letsenhance.io. New users get 10 free credits automatically.
Step 2: Click "My images" to open the workspace and upload your file (JPG, PNG, or WEBP, up to 50 MB).
Step 3: Prime is selected by default. You just need to choose your output size (from 1x to 16x).
Step 4: Click "Enhance" and download your high-quality result when processing is complete.
That's the full process. No settings to configure, no filters to stack, no decisions to make beyond the output scale.
Using Photoshop Super Zoom
- Open Photoshop and import your image (File > Open or Ctrl+O).
- Go to Filter > Neural Filters.
- Scroll to Super Zoom and enable it.
- Click the zoom icon to increase scale (each click = 1x, so 3 clicks = 3x). Optionally enable JPEG artifacts removal, noise reduction, sharpening, or face enhancement from the panel.
- Set Output to "New Document" (important: if you leave it on "New Layer," the upscale is cropped to the original document dimensions).
- Click OK. Processing happens in the cloud and may take a moment.
It's worth noting that some optional enhancement passes in Super Zoom produced worse results in our tests. We recommend testing with and without them on your specific image.
Which one to use
Use Photoshop Super Zoom if: You're already working in Photoshop, your source image is sharp and reasonably high-quality, and you need a moderate size boost without switching tools. It fits photographers who live inside Adobe's ecosystem and need occasional enlargements as part of a broader editing workflow. For severely degraded inputs, heavy pixelation, or cases where face identity and skin texture need to survive the process, it's not the right tool.
Use Let's Enhance Prime if: Output quality is the goal, especially for portraits and images with fine texture. If your source is heavily degraded, compressed, or low-resolution, Prime produces significantly more realistic results. And if you want to go from upload to finished image in under a minute without learning a new menu structure, the workflow difference is substantial. If you need heavy generative reconstruction on extremely degraded images, the Ultra model is a better starting point than Prime, but for most portrait and texture work, Prime is where to start.
FAQ
What is Photoshop Super Zoom and how does it differ from Super Resolution?
Super Zoom is a neural filter in Photoshop that increases image size and adds AI-generated detail to compensate for the resolution lost in upscaling. It's accessed through Filter > Neural Filters.
Super Resolution is a separate Adobe feature in Camera Raw and Lightroom (not in the Neural Filters panel) that doubles linear resolution, giving you a 4x pixel count increase.
They use different pipelines. Super Resolution works on RAW files and is generally better for photographers already in a Lightroom/Camera Raw workflow. Super Zoom is more flexible in terms of the upscale factor (you can stack multiple clicks) but is designed primarily as a zoom-and-crop tool that can also be used for full-image upscaling with the right output setting.
How do neural filters in Photoshop actually work?
Neural filters use Adobe Sensei, Adobe's AI and machine learning platform. It analyzes patterns in images and applies context-aware adjustments based on models trained on large image datasets. For Super Zoom specifically, the model attempts to reconstruct detail that would be present if the original image had been captured at higher resolution. The output is processed in Adobe's cloud, which is why an internet connection is required. The accuracy of the reconstruction depends heavily on how much useful detail exists in the source image to begin with.
What does "fidelity" mean in AI upscaling, and why does it matter for portraits?
Fidelity in AI upscaling refers to how accurately the output represents the original image, as opposed to generating plausible-looking but invented detail. High fidelity means the AI enhanced what was already there rather than replacing it with its best guess. For portraits, this matters because a face has to remain recognizable. If a model generates new skin texture or subtly shifts facial structure (which happens with generative or low-fidelity tools), the result can look realistic but still feel wrong, or worse, not look like the right person. Tools like Let's Enhance Prime are described as fidelity-first specifically because they prioritize this.
Can Photoshop upscale a portrait to 8x?
Yes, technically. Each click of the Super Zoom zoom icon increases the scale by 1x, so three clicks gives you a 3x upscale. However, our tests showed that 8x upscaling from a low-resolution source (200px) through Super Zoom produced heavily artifacted results. The tool performs better at lower upscale factors and on cleaner source images. For extreme upscaling from degraded inputs, dedicated tools like Let's Enhance Prime or the Strong/Ultra models handle the reconstruction task more reliably.
What causes the "painted" look in some AI upscalers?
When an upscaler doesn't have enough source detail to work from, it has to generate new pixels that are plausible rather than accurate. On skin especially, this tends to produce an over-smoothed, uniformly textured surface that looks like an illustration or a rendering rather than a photograph. The underlying cause is the model defaulting to average-looking skin rather than the specific texture that was in the original. This happens more often when the source image is very low resolution or heavily compressed, and when the AI model was not specifically tuned to preserve natural texture variation. It's a known limitation of general-purpose upscalers applied to demanding inputs.
What file formats and image sizes does Let's Enhance support?
Let's Enhance accepts JPG, PNG, and WEBP files up to 50 MB. Output scales from 1x to 16x, with a maximum output of 512 megapixels on business plans. This makes it practical for print-ready files, large-format output, and anything that needs to hold up on a 4K or 8K display.
Do I need Photoshop to use neural filters for upscaling?
Yes. Photoshop Neural Filters, including Super Zoom, are only available inside Photoshop with an active Creative Cloud subscription. Photoshop alone is around $22/month. If you're not already a subscriber, the cost is significant for a feature you may only use occasionally. Let's Enhance is a standalone web tool with a free tier (10 credits on sign-up) and paid plans starting at $9/month, so if upscaling is your primary need, the cost-to-value ratio is quite different.
What is super resolution in the context of AI imaging?
Super resolution (SR) is the process of increasing an image's resolution beyond what the original capture contained, using AI to reconstruct or infer missing detail. It's different from traditional bicubic or lanczos interpolation, which simply spreads existing pixels over a larger area. AI super resolution models are trained to understand what high-resolution versions of images typically look like and use that knowledge to generate plausible high-frequency detail. The quality of the result depends on the training data, model architecture, and how well the model handles the specific content type (faces, text, textures, etc.) in the input image.
Is there a free way to test Let's Enhance Prime before paying?
Yes. New users get 10 free credits when they sign up. Most upscales on Prime cost 1–2 credits, so you can run several test images before deciding whether to subscribe. This is useful if you want to compare Prime's output on your specific images before committing.