UPSAMPLER

AI Image Upscaler

Upscale Blurry Text in Your Images with AI for Enhanced Readability

Enlarge scans, screenshots, and signage so every letter stays readable and every glyph stays the glyph it was. Nothing gets repainted into something that only looks like text.
Scale
Up to 6x
Ceiling
100 MP
Glyph edges
Sharpened
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Before
Neon shop signage at night upscaled by AI, with the lettering becoming sharp and legible before enhancement and upscaling
After
Neon shop signage at night upscaled by AI, with the lettering becoming sharp and legible after enhancement and upscaling
IN 572²OUT 2288²
Faithful models

Enlarge Text Without Rewriting It

The faithful models enlarge textual content while keeping the original font, crisp strokes, and fine details exactly as they are, with no unwanted alterations.

Before
Text within an image faithfully enlarged, highlighting the preservation of original font characteristics, sharp lines, and exact details for maximum readability. before enhancement and upscaling
After
Text within an image faithfully enlarged, highlighting the preservation of original font characteristics, sharp lines, and exact details for maximum readability. after enhancement and upscaling

Read the Small Print

The upscaler itself, loaded with real results. Zoom in on the lettering to see which model keeps glyph edges legible.

Examples
Compare all AI image upscaler models

Text Is Where Upscalers Get Caught Lying

A slightly hallucinated tree branch is invisible. A slightly hallucinated letterform is gibberish. Text is the hardest content for AI enhancement because readers verify every stroke, which is why generic creative upscalers turn small print into convincing nonsense. The faithful model treats each letterform as structure to be sharpened, not repainted, and keeps font, stroke weight, and the contrast between text and background while multiplying resolution.

Where Legible Text Actually Matters

Scanned contracts and archival documents where every clause must stay verifiable, historical materials being digitized, screenshots in documentation and bug reports, whiteboard photos, old signage, and infographics that get reshared until compression destroys them. In each case the test is the same: can a reader zoom in and trust what they see? Upscaled output holds up to that test at print size and on high-DPI displays.

Settings That Work

  • Model: any faithful model; P Image Upscale is the default in the upscale tool
  • Scale: 2x for screens, 4x for reprints and OCR
  • Enhance Faces: off
  • Source: a PNG screenshot beats a re-saved JPEG, and a 300 DPI scan beats a phone photo

Before You Publish

Proofread any AI-touched text before it goes out. For documents headed to OCR, upscale first so the engine gets clean strokes to work with. Test a difficult scan on the free no-signup upscaler and zoom to 100% on the smallest line.

More in Restoration & Technical Improvement

Guides for neighboring workflows, powered by the same models.

Ready to Create?

Create and Enhance Images and Videos

Upsampler puts every step of AI image and video work in one place. Generate new visuals from a prompt, upscale images and videos to crisp high resolution, and make targeted edits with AI, all in one platform. Everything runs online with no downloads or installs, on any device and any operating system. Pay as you go with one-time credits, no subscription required.

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Frequently Asked Questions

With the faithful model, yes: it sharpens the strokes that are there and never substitutes characters.

Screenshots are an ideal source because they are already lossless. Menus, code, and small UI labels come out crisp at 2x or 4x, which is useful for documentation and slides.

It enlarges and sharpens small print cleanly as long as the strokes are distinguishable in the source. Text that is already merged into blobs by compression is beyond any upscaler; start from the best copy you have.

Usually. A 2x to 4x faithful upscale gives the OCR engine clean, well-separated strokes to work with, which helps most on small print. Test one page before batching a scan.