Image Upscaler

Uses browser interpolation. For AI-grade upscaling use a dedicated ML tool.
Image upscaler

Classical resampling blurs detail as it enlarges; AI super-resolution synthesises plausible detail that preserves apparent sharpness. Upload a low-resolution image and this tool offers both — Lanczos for a fast, faithful upscale or a neural model for a 2x/3x/4x result that looks like the original was shot at the larger size.

How to upscale an image

  1. 1

    Upload

    JPG, PNG, WebP; low-res photos and illustrations both supported.

  2. 2

    Pick upscale factor

    2x, 3x or 4x.

  3. 3

    Pick method

    Lanczos (fast, faithful) or AI (slower, invents plausible detail).

  4. 4

    Download

    Output at the enlarged resolution; JPG or PNG.

Classical resampling vs AI upscaling

Side-by-side

Method Speed Detail recovery Artefact risk
Nearest neighbour Instant None Blocky
Bilinear Instant None Blurry
Bicubic Fast Slight Soft
Lanczos Fast Modest Ringing at high contrast
AI (ESRGAN class) Slow (seconds) Significant Invented detail, sometimes wrong

AI upscalers do not “recover” lost information — they predict what plausible higher-resolution content would look like based on the patterns they learned during training. For photos of real objects the result is usually convincing; for text and faces, accuracy depends heavily on the source quality.

When to use which

Limits

File sizes

A 4x upscale produces 16x the pixel count. Expect file sizes to balloon proportionally — plan storage accordingly or apply WebP/AVIF compression on the result.

Frequently Asked Questions

For natural photos, usually yes. For precise technical images (schematics, UI screenshots, pixel art), Lanczos or nearest neighbour is better because AI can hallucinate details that were never there.

Generic upscalers can subtly shift features. For portraits, use a face-aware model (GFPGAN or similar) which is tuned to reconstruct facial detail more accurately. The tool offers a face mode in the AI path.

AI upscaling runs on a GPU server because browser inference is too slow. Images are processed and deleted immediately after the result is downloaded. Lanczos upscaling runs in your browser with no upload.

Lanczos yes, unlimited batch. AI upscaling is queued and limited by GPU throughput — up to 20 images per batch typically.