Enlarge images 2× or 4× with real AI — sharper photos, larger prints, restored old pictures. 100% free, no upload, all in your browser.
Drag & drop your image here
or click to browse — JPG, PNG, WebP, BMP
Result will appear here
Old-school image enlarging (the kind your computer's "make this image bigger" function uses) just stretches the pixels. If you double the size of a 500×500 image, you get a 1000×1000 image where every original pixel has become a 2×2 block. The result is blurry, blocky, and obviously upscaled. There's no new detail — you just have more space to put the same data.
AI upscaling does something fundamentally different. The model has been trained on millions of high-resolution images paired with their downscaled versions. It learned what "this is what a low-res version of a real photo looks like, and here's what the real high-res original looked like." When you give it a low-res image, it doesn't just stretch pixels — it tries to predict what realistic detail would be there if the photo had been taken at higher resolution. The result is genuinely sharper images with realistic edges, textures, and detail.
This tool brings that capability into your browser, free and private. Drop in any image, pick 2× or 4× upscaling, and the AI produces a larger, sharper version. The model runs entirely on your device — no upload, no waiting in a queue, no daily quota.
2× doubles the dimensions (a 500×500 image becomes 1000×1000), 4× quadruples them (becomes 2000×2000). 4× takes longer and uses more memory; for most uses, 2× is plenty.
Drag and drop your image into the upload area, or click to browse. JPG, PNG, WebP, and BMP all work. To keep things fast in the browser, the tool caps input images at about 1024 pixels on the longest side. At 4× scale, that produces outputs up to 4096 pixels — large enough for most printing and display needs.
Processing takes 5–30 seconds depending on the input size and your device's speed. The first time you use the tool, the model downloads (about 80MB, one-time cost cached in your browser). Subsequent uses skip the download.
Save the upscaled image as PNG (lossless, best quality) or JPG (smaller file, slight compression).
Your image never leaves your device. Most popular AI upscalers — including the big-name ones — upload your image to their servers, run the AI there, and stream the result back. Their AI is genuinely impressive, but the upload is a privacy risk if your image is anything sensitive: family photos, ID scans, product mockups under NDA, work-in-progress designs. We run the AI in your browser using transformers.js. No upload, no logs, no copies of your image anywhere except your device.
No queues, no rate limits. The big cloud services often throttle free users or make you wait in a processing queue when they're busy. Because we run on your device, there's no queue — your CPU is the only resource.
No daily quota. Most cloud-based AI upscalers limit free users to 1–5 images per day before requiring payment. We don't have a limit because we don't have ongoing costs per image — your device does the work.
Works offline after first load. Once the model is cached in your browser, the upscaler runs fully offline. None of the cloud-based alternatives can do that.
The honest tradeoff: our model is a solid baseline, but it's not quite as advanced as some paid cloud services running multi-billion-parameter models. For most everyday photos, the difference is invisible. For very challenging cases (extremely low-res, very noisy, unusual subjects), a paid cloud service might produce a sharper result. But for the 95% of cases where you just want a good 2× or 4× upscale of a real-world photo, this is the right tool.
Rescuing low-resolution photos. You have a great photo from years ago — maybe taken on an old phone, maybe a screenshot — and you want to print it or use it large. Upscaling adds back the detail that the low capture resolution couldn't preserve.
Old family photos and scans. Scanned snapshots from the pre-digital era often look low-res when displayed on modern screens. Upscaling restores some of the apparent sharpness without losing the photo's character.
E-commerce and product photos. If you have a product photo at a low resolution that needs to be displayed larger on your store or marketing material, AI upscaling beats stretching.
Print preparation. Printing photos requires more pixels than displaying them. A 1000×1000 image looks fine on a phone screen but soft as a 8×8 inch print. Upscaling to 4× before printing solves the resolution gap.
Restoring old digital art and screenshots. Pixel art and old digital images often need careful upscaling to show on modern high-resolution displays. AI handles this far better than naive stretching.
Profile photos and avatars. If the only photo you have for a profile is small, upscaling makes it usable as a high-resolution avatar without weird artifacts.
Stock photos at the wrong size. If you bought or licensed a photo at lower resolution than you ended up needing, upscaling is faster and cheaper than re-licensing the larger version.
It can't invent detail that wasn't there. The AI predicts what realistic detail would look like in the image, but it can't conjure information that the original sensor never captured. A blurry photo of a license plate won't suddenly become readable.
Heavy JPEG compression artifacts. If the input is a heavily-compressed JPG with visible blocky artifacts, upscaling tends to amplify those artifacts rather than smooth them away. Start with the cleanest source you have.
Motion blur or out-of-focus shots. Upscaling preserves the blur — it just makes it a bigger, sharper-edged blur. For these, an AI deblurring tool is what you need, not an upscaler.
Identifying specific subjects in a too-small image. If a face occupies 20 pixels in the original, upscaling makes those 20 pixels into 80 pixels, but it's still working from 20 pixels of information. Don't expect to "enhance" tiny faces or text the way TV shows pretend you can.
Fixing color or exposure problems. Upscaling is about adding pixels, not adjusting colors. Color correction is a separate operation.
Start with the cleanest, highest-quality source you have. If you have both a JPG and a PNG of the same image, use the PNG. If you have multiple versions, use the one with least compression.
Crop first, then upscale. If you only need part of an image, crop to that area before upscaling. The AI gives all its detail-budget to the area you upscale, so a tight crop of just the subject upscales sharper than the whole frame.
For text-heavy images, results vary. AI upscalers are tuned for photographs. Sharp, anti-aliased text in images usually upscales well, but heavily compressed or stylized text can produce artifacts. For text, vectorizing (using tools that recognize characters and recreate them) often produces cleaner results than pixel upscaling.
Try both 2× and 4×. Sometimes 4× actually produces worse results than 2× because the AI has to invent more detail than it can do convincingly. If 4× looks artificial, fall back to 2×.
Compare side-by-side at 100% zoom. The upscaled result might look great on a thumbnail and disappointing when zoomed in to actual pixels. Always check at full size before deciding the result is good enough.
This tool uses a neural network model called Swin2SR (or a similar super-resolution architecture). The model was trained on millions of paired examples: high-resolution images alongside their downscaled versions. Through that training, it learned the statistical patterns of what real-world detail looks like — how edges sharpen, how textures resolve, how skin and hair and fabric reveal fine detail at higher resolution.
When you upload an image, the model takes the low-resolution input and runs it through a series of neural network layers that progressively predict higher-resolution detail. The output is an image where each pixel of the original has been replaced by a predicted patch of higher-resolution pixels that look like what the original scene would have produced if photographed at higher resolution.
The model itself is about 80MB and runs entirely in your browser using ONNX Runtime through the transformers.js library by Hugging Face. First visit downloads and caches the model; future visits load it instantly. No cloud servers involved, no upload, no server cost on our side.
Yes — completely free, no signup, no watermark, no limit. Most cloud AI upscalers charge or cap free use; we don't have those costs because the AI runs on your device.
No. The AI model is downloaded once to your browser and runs locally. Your image never leaves your device, ensuring complete privacy.
Input is capped at about 1024 pixels on the long side (for performance). At 4× scale, output can be up to 4096 pixels — large enough for prints and most retina displays.
Photos of people, landscapes, products, and pets typically upscale very well. Text-heavy images and very fine vector graphics may show artifacts; for those, vectorizing instead of upscaling produces cleaner results.
The AI model (~80MB) downloads once and gets cached in your browser. After that initial download, every visit loads the model instantly from cache and processing starts immediately.
Reasonably well, but general-purpose AI upscalers like ours are tuned for photographs. There are specialized upscalers for anime and cartoon art that can produce sharper results on those specific styles — we may add a mode for it in a future update.
Yes — the output is yours. We don't claim any rights over your images. Just make sure you have rights to the original source image.
Not currently. 8× and higher generally produces lower-quality results because the AI has to invent too much detail relative to what's in the source. For very large outputs, upscale 2× or 4×, then upscale that result again — usually better than a single huge jump.