Is my image uploaded because this uses AI?
No. The input image stays in your browser. AI mode downloads the model and ONNX Runtime code, then runs inference locally on your device.
AI Image Upscaler
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About this tool
Browser-based AI image upscaling
AI Enhance uses a compact Real-ESRGAN super-resolution model through ONNX Runtime Web. The model is downloaded to your browser and inference happens on your device. Your selected image bytes are not uploaded by NowConverter. A Fast resize mode is also available when you only need conventional enlargement.
Why does AI mode need internet access?
NowConverter does not bundle the machine-learning model into every page visit. When you start AI Enhance, the browser fetches the open-source runtime and model files from public CDNs. Those files travel to your browser; your image does not travel back to them. After that, the actual image processing happens locally.
Before you upscale
AI super-resolution creates plausible detail based on patterns learned by the model. It can make small or compressed images look sharper, but it cannot reconstruct information that no longer exists. Processing speed depends heavily on the device, and very large outputs are limited to reduce browser crashes on phones.
What is the difference between 2× and 4×?
2× doubles width and height. 4× quadruples width and height, producing sixteen times as many pixels as the original image and using substantially more memory.
Why can AI upscaling take longer on phones?
The model performs many numerical operations for every image tile. Mobile processors and browser memory limits are usually lower than desktop hardware, so NowConverter uses smaller tiles and conservative output limits on mobile devices.
Does AI recover the exact original detail?
No. Real-ESRGAN can synthesize convincing high-frequency detail, but generated detail is an informed estimate rather than recovered ground truth.
AI upscaling can improve presentation, but it cannot recover certainty
An AI upscaler predicts plausible high-resolution detail from a lower-resolution image. That can make edges look cleaner and make a small image more usable on a larger canvas, but the new pixels are inferred rather than recovered from hidden source information. Tiny text, faces, logos and repeated patterns deserve extra checking because the model may invent shapes that look convincing at first glance.
For screenshots, diagrams and line art, a conventional resize can sometimes preserve geometry more faithfully than an enhancement model. For photographs, AI mode may look more natural. Compare the original and result side by side, and avoid treating an enlarged image as forensic evidence or as a source of details that were not visible before.
Practical checks
- Use 2× first when you only need a moderate size increase.
- Inspect eyes, letters, jewellery, textures and straight lines for invented detail.
- Keep the original image alongside the enhanced copy.
Practical walkthrough · image upscaler
Prepare a small illustration for a larger layout
Example task: A 512-pixel illustration needs a larger working copy for a slide.
Try this workflow
- Start with the cleanest available source and choose 2× or 4× only if needed.
- Compare fine lines, facial details and text after processing.
- Treat AI-generated detail as an interpretation rather than a faithful recovery of lost pixels.
What to expect
The local AI path can synthesize additional detail; a fast resize fallback may simply increase dimensions.
When to take extra care
AI artifacts can alter faces, logos, letterforms or evidence. The first model download and GPU/memory needs may be substantial.