Photo BlowUp vs Upscayl: Which AI Upscaler Should You Use?

Upscayl is the go-to recommendation in a lot of Reddit threads about free AI upscalers. It is open-source, it works on every major platform, and it does not cost a thing. But free does not always mean best. I spent two weeks running both Upscayl and Photo BlowUp through the same set of test images to figure out where each one actually shines — and where it falls short.

Quick Comparison Table

What is Upscayl?

Upscayl is a free, open-source desktop application that uses the Real-ESRGAN deep learning model to upscale images. It was created by a small team of developers who wanted to make AI upscaling accessible to everyone without paying for expensive software. The project is hosted on GitHub and has gained a loyal following, especially among Linux users who do not have many options in this space. As of mid-2026, it has over 12,000 stars on GitHub and an active community of contributors.

The software is straightforward: you load an image, pick an enlargement factor (2x, 3x, or 4x), choose a model, and hit the upscale button. It processes everything locally on your machine. No cloud uploads, no accounts, no subscriptions. The download is small — around 80MB — and installation takes less than a minute on most systems.

Photo BlowUp takes a similar local-first approach but is built on a proprietary AI model that the company trained specifically for photo enlargement. It costs $39.95 as a one-time purchase and includes batch processing, noise reduction, and format support that Upscayl does not offer. Both tools keep your photos on your machine, which matters if you care about privacy.

Quality Comparison: Side by Side

I tested both tools on the same 25 images at 2x, 3x, and 4x enlargement. Here is what happened.

Phone Photos (12MP, JPEG)

I took a series of phone photos — landscapes, street scenes, and a few close-ups of food. At 2x, both tools produced nearly identical results. The differences only became visible when I zoomed in past 150%.

At 3x, Photo BlowUp started pulling ahead. Edges were cleaner, textures were more defined, and there was less of the "watercolor" effect that Upscayl sometimes produces on fine details like grass and fabric. When I printed a 3x enlarged landscape at 20x30 inches, Photo BlowUp held up noticeably better at normal viewing distance.

At 4x, the gap widened. Upscayl's output on a 12MP photo looked acceptable on screen but started showing visible artifacts when I zoomed in to check individual pixels. Photo BlowUp kept things cleaner — not perfect, but noticeably better.

Product Photography

I run a small online store, so product photos are important to me. I tested both tools on a batch of 30 product shots taken with a mid-range mirrorless camera (20MP, RAW converted to JPEG).

Photo BlowUp handled product edges cleanly. The white backgrounds stayed white without color fringing, and the product details — stitching on a leather bag, texture on a wooden cutting board — came through sharp. Upscayl did a decent job but occasionally introduced slight color shifts on the product edges, which I had to correct manually.

For someone processing product photos regularly, the time saved on corrections alone is worth the $39.95 price of Photo BlowUp.

Old Scanned Photos

I digitized a box of old 4x6 prints from the early 2000s using a flatbed scanner at 300 DPI. These came out to roughly 1.5-2MP files with visible film grain and scanner noise.

Upscayl did a reasonable job cleaning up the noise while enlarging, but it sometimes smoothed out important details like facial features and text on signs. Photo BlowUp handled these better — it reduced noise while keeping the key details intact. The faces in my old family photos looked more natural after processing with Photo BlowUp.

Batch Processing Speed

I timed both tools on the same machine (Intel i7-12700H, 16GB RAM, integrated graphics only — no discrete GPU).

• Photo BlowUp: 50 photos at 2x completed in about 2 minutes and 50 seconds
• Upscayl: 50 photos at 2x completed in about 5 minutes and 40 seconds

Upscayl supports batch processing, but it is basic. You select multiple files and they process one at a time. Photo BlowUp lets you set output format, quality, and destination folder for the entire batch, which saves time when you are working through a large set of images.

Interface and Ease of Use

Upscayl has a clean, minimal interface. It is a single window with a big "Upscay" button. There are not many settings to configure, which is both a strength and a limitation. You pick a model (there are a few options like Real-ESRGAN General, Digital Art, and Compact), choose your scale factor, and go. The whole interface fits on one screen without scrolling, which is nice for users who get overwhelmed by too many options.

Photo BlowUp has a more polished interface with a file browser, preview window, and batch queue. It feels more like a professional tool. The downside is that there is slightly more to learn upfront, but the learning curve is gentle — most people will be comfortable within five minutes. The batch queue is particularly useful: you can see all your queued images, reorder them, and monitor progress in real time.

Upscayl runs on Linux, which is a major advantage for users on that platform. There are very few AI upscaling tools available natively on Linux, so Upscayl fills an important gap. If you are a Linux user, this alone might make Upscayl the right choice regardless of what the other tools offer. Photo BlowUp supports Windows and macOS, so if you use Linux, Upscayl may be your only practical option unless you want to run a Windows VM.

Installation and Hardware

Upscayl installs quickly — the download is under 100MB and setup takes about a minute. It does not require an account or internet connection after installation. However, you may need to install additional GPU drivers depending on your system. On Ubuntu, I had to install the NVIDIA CUDA toolkit separately to get decent processing speeds. On Windows and macOS, the experience was smoother.

Hardware requirements are modest. Upscayl runs on CPU if no GPU is available, but it is much slower. With a GTX 1060 or equivalent, processing a single 4MP image at 2x takes about 5-8 seconds. Without a GPU, that same image takes 20-30 seconds. Photo BlowUp handles CPU-only processing better — on the same machine without a GPU, it completed the task in about 4 seconds.

One thing to note: Upscayl's performance can vary depending on your GPU drivers and operating system. I encountered a few hiccups on Linux where the software would not detect my GPU until I updated the drivers. On Windows, it worked without issues. If you are not comfortable troubleshooting driver problems, this is something to consider.

AI Models and Processing

Upscayl uses Real-ESRGAN, which is a well-known open-source model. It has several variants: General (for photos), Digital Art (for illustrations), and Compact (for faster processing). The models are decent, but they are the same ones available in any Real-ESRGAN implementation, including command-line tools. If you are technically inclined, you can get the same results by running Real-ESRGAN from the terminal — Upscayl just wraps it in a GUI.

Photo BlowUp uses a proprietary model that is not publicly available. In my experience, it produces more consistent results across different photo types. I did not have to think about which model to use — the software automatically detected the content and applied the right processing. This is convenient for users who do not want to experiment with model selection. The consistency matters when you are processing a batch of mixed images — landscapes, portraits, product shots — and want them all to come out looking good without manual intervention.

Noise Reduction

This is one of the bigger differences. Upscayl applies basic noise reduction as part of its upscaling process, but you cannot control it separately. If your source image is noisy, the output may still show grain, or the model may over-smooth the image trying to remove it. There is no slider, no strength setting — you get whatever the model produces.

Photo BlowUp has a dedicated noise reduction step that runs before enlargement. You can adjust the strength, which gives you more control over the balance between noise removal and detail preservation. For noisy high-ISO shots or old scanned prints, this is a meaningful advantage. I tested this on a set of indoor photos shot at ISO 6400, and Photo BlowUp cleaned up the noise while preserving edge detail much better than Upscayl's automatic approach.

File Format Support

Upscayl supports JPEG and PNG for both input and output. That covers most use cases, but if you need TIFF output for print production or BMP support for legacy workflows, you are out of luck.

Photo BlowUp supports JPEG, PNG, TIFF, BMP, and WebP. The WebP support is useful if you are working with web-optimized images, and TIFF output is important for anyone sending files to a print shop.

Support and Community

Upscayl has a GitHub repository where you can report bugs, request features, and browse discussions. The community is active but small. If you run into a problem, you might get help in a few hours or a few days, depending on the issue. There is no formal support channel, no chat, and no email support. The documentation is community-maintained and covers the basics but can be sparse on edge cases.

Photo BlowUp offers email support and has documentation covering installation, usage, and troubleshooting. In my experience, responses came within 24 hours. For users who need reliability and timely help, this matters. When I hit a snag with batch processing on a specific file type, the Photo BlowUp team responded with a solution the same day. With Upscayl, I would have been digging through GitHub issues hoping someone else had the same problem.

The Price Question

Let me be honest about this: Upscayl is free. That is a hard argument to beat. If you are a student, hobbyist, or someone who only upscales a few photos per month, Upscayl does the job well enough. The output quality is decent, and the fact that it costs nothing makes it easy to recommend for casual use.

But free comes with trade-offs. No dedicated support. Limited batch processing. Fewer output formats. A less polished interface. For occasional use, these trade-offs are tolerable. For regular or professional use, they add up. The time you spend troubleshooting an issue or manually processing files one at a time has a real cost, even if the software itself is free.

Photo BlowUp at $39.95 is not expensive, and the improvements in quality, speed, and workflow efficiency are real. If you process more than a handful of photos per month, the paid tool pays for itself in time saved. Think of it this way: if Photo BlowUp saves you 10 minutes per batch and you process two batches per week, you save over 17 hours per year. That is worth $39.95 to most people.

Who Should Choose Photo BlowUp?

• You process photos regularly and need reliable batch processing
• Product or e-commerce photography where edge quality matters
• You want better noise reduction controls for noisy or old photos
• You need TIFF or WebP output for print or web workflows
• You prefer polished software with customer support
• You want consistent results without tweaking AI model settings

Who Should Choose Upscayl?

• Budget is the primary concern and you cannot spend $39.95
• You use Linux and need a native upscaling tool
• You only upscale a few photos per month
• You prefer open-source software and community-driven development
• You want to experiment with Real-ESRGAN models manually
• You are comfortable troubleshooting technical issues on your own

Photo BlowUp Team

Image Processing & Photography Software Reviewers

We've spent hundreds of hours testing AI photo enlargement tools — comparing output quality, processing speed, and real-world results. Our team includes photographers, graphic designers, and print shop professionals who rely on these tools daily. When we recommend something, it's because we've actually used it.