Every unblur image tool sells the same promise. We degraded a portrait we own to 240px, ran it back up two ways, and compared both against the original we still had. Upscaling kept the woman and stayed soft. Generative restore got sharp and returned a different face — narrower jaw, smaller mouth, the open smile closed, the hairline moved. Neither is a bug. Detail that is not in the file cannot be recovered, only invented, and the tools selling "unblur image" never say which one you are buying.
Most unblur image write-ups compare a blurry input against a sharp output and stop there. That comparison can tell you the result got sharper; it cannot tell you whether it is still the same photo, because there is nothing left to check it against.
So we kept one. We degraded an image we own and held the original back as a reference, which turns "it looks better" into something you can verify.
Last updated: September 2026.
How we tested every unblur image claim
We took a studio portrait we generated and own, at 896×1200. We resized it to 240px on the long edge and saved it as a JPEG at quality 22 — the file dropped to 2,983 bytes. Then we pushed it back to 668×896 by plain resampling, so every tool got the same soft input.
Because we still had the 896×1200 file, every output has a ground truth to be checked against. That is the whole method, and it costs nothing.
Both unblur image paths were run on 1 September 2026:
| Path | Model | Price | Output | Same person? |
|---|---|---|---|---|
| Plain upscale | Topaz Image Upscaler, 2× | $0.050/image | 1336×1792 | Yes |
| Generative restore | Nano Banana 2, 1K | $0.040/image | 1792×2400 | No |
| Plain upscale | Recraft Crisp Upscale | $0.003/image | task failed on our input | — |
Unblur image path 1: plain upscaling
The upscaler kept the person
Topaz returned 1336×1792 — each edge doubled, so four times the pixels — and kept the person. Face proportions, the open smile, the parting in the hair, the neckline of the navy sweater — all unchanged from the original we held back.
But it could not unblur what was gone
It also stayed soft. The skin has no pores, the hair has no strands, the sweater has no weave. It could not add them, because they were not in the 2,983-byte file.
A pure upscaler is an honest tool with a hard ceiling: it will never lie to you about who is in the photo, and it will never recover a detail that was destroyed. If your image is merely small, an upscaler is the right unblur image tool. If it is genuinely destroyed, no upscaler on any price tier will unblur an image back into existence.
Unblur image path 2: generative restore
It looks like a real unblur image result
Nano Banana 2 returned a genuinely sharp 1792×2400 portrait with skin texture, individual hair strands and knit detail in the sweater. It looks like a professional headshot.
Against the original, it is a different woman
Compared against the original, it is a different woman.
- The jaw is narrower and the chin more pointed
- The mouth is smaller, and the original's open smile is closed
- The hairline sits differently and the hair has less volume
- The eyebrows changed shape
- The skin is smoothed to a degree the original never had
Nothing in the prompt asked for any of that. We explicitly wrote keep the same person, identical facial structure, do not beautify. The model complied with the parts it could and invented the rest, because reconstructing a face from 2,983 bytes is not restoration, it is generation conditioned on a hint.
The rule that decides every unblur image result
Put the two runs side by side and one line covers them:
A model preserves what it can still see, and invents what it cannot.
That is not a quality ranking between models. In a different test on the same day we asked the same Nano Banana 2 to delete every parked car from a street photo, and it kept the walking woman's face perfectly — because her pixels were never destroyed, so it only had to rebuild the road behind her. The face survived when the face was intact, and was replaced when the face was gone. Same model, opposite outcome, and the deciding factor was the input, not the price tier. We wrote that experiment up separately in remove an object from a photo.
So the useful question is never "which unblur image tool is best." It is: is the detail I want still in this file? Every honest unblur image answer starts there.
Which unblur image path fits your job
When any unblur image tool is fine
Scanned document, screenshot, small product photo. Nothing sentimental, nobody's face. Any generative unblur image tool is fine here, and usually better — invented texture is a feature rather than a lie.
When to unblur an image conservatively
A photo of a person you know. Use an upscaler to unblur the image and accept softness, or accept that the sharp version is a portrait of someone who resembles them. For a passport-adjacent, legal, or memorial use, the second option is not an option.
Old family photos. This is the case the unblur image category is sold on, and the case it handles worst. Generative restore will hand you a crisp, plausible, subtly wrong ancestor. If you use it, keep the scan.
What free unblur image tiers cost, and when they reset
The daily quota is not what it looks like
The unblur image sites are not priced like the model APIs underneath them. EzEnhancer — 1.32M monthly visits, DR 15, on Columbus's July 2026 snapshot — publishes this on its own pricing page, read 1 September 2026:
| Plan | Price | Monthly credits | Daily free quota | Rollover |
|---|---|---|---|---|
| Free | $0 | — | 10/day, same-day only | None |
| Starter | $8/mo | 200 | 20/day, same-day only | up to 600 |
| Mid | $25/mo | 1,000 | 30/day, same-day only | up to 6,000 |
| Top | $45/mo | 2,000 | 50/day, same-day only | up to 12,000 |
Read the phrase "same-day only." The daily quota and the subscription credits are two different pools, and the daily one is deleted every night whether or not you used it. A plan advertised as "800 credits a month" is 200 credits that roll over plus 600 that evaporate in nightly instalments of 20.
For comparison, here is the wholesale rate card under this whole category, read from the provider shelf on the same date:
| Model | What it does | Published rate |
|---|---|---|
| Recraft Crisp Upscale | pure upscale | $0.003/image |
| Topaz Image Upscaler | pure upscale | $0.050 (2K) · $0.100 (4K) · $0.200 (8K) |
| Nano Banana 2 | generative redraw | $0.040 (1K) · $0.060 (2K) · $0.090 (4K) |
| Nano Banana Pro | generative redraw | $0.090 (1/2K) · $0.120 (4K) |
| Qwen image-edit | generative redraw | $0.030 per megapixel |
| Ideogram v3-remix | generative redraw | $0.018 (turbo) · $0.050 (quality) |
A free unblur image tier of 10 operations a day is giving away somewhere between three cents and forty cents of compute — which is why the daily reset exists at all.
One thing worth knowing before you start clicking: lowqualityimage.org sits in the same search results and is not an enhancer at all — it compresses images to make them worse, for file-size limits. If your actual problem is an upload cap rather than softness, that is the tool you want, and no amount of upscaling will help.
How to unblur an image without being fooled
- Check the source file size before you try to unblur the image. Ours was 2,983 bytes. Under about 50KB for a full frame, there is no detail left to recover and every "unblur" result you get will be invented.
- Never overwrite the original. It is the only evidence you have that the output is honest.
- Upscale first; reach for a generative unblur image run only if upscaling is not enough. It costs less and it cannot change who is in the photo.
- If a face matters, compare the eyes and the mouth corners against the original, not the overall impression. Those move first.
- Run the same input through two models before trusting either. On Kavel that is one balance and one dropdown — the credit cost per model is shown before you generate, and the pricing page lists it per image.
The original we held back — the reference every output above was checked against.
Sources
Every figure was produced or read on the date named.
- Our own degrade-and-restore run, 1 September 2026: source 896×1200, degraded to 2,983 bytes, outputs from Topaz Image Upscaler 2× and Nano Banana 2 at 1K. Files linked above.
- EzEnhancer pricing — daily free quota, "same-day only", monthly credits and rollover caps. Read 1 September 2026.
- Topaz Image Upscaler and Recraft Crisp Upscale — published per-image rates. Read 1 September 2026.
- lowqualityimage.org — a compression tool, not an enhancer. Read 1 September 2026.
- Traffic and DR figures for EzEnhancer and lowqualityimage.org: Columbus AI-site index, July 2026 snapshot.
Unblur image FAQ
Can AI really unblur an image?
It can produce a sharp image from a blurry one. Whether that is the same image depends on how much was destroyed. Our test at 2,983 bytes produced a sharp portrait of a different person, from a prompt that explicitly forbade changing the face.
What is the difference between an upscaler and an AI unblur image tool?
An upscaler adds pixels by interpolation and cannot invent content. A generative enhancer redraws the picture using the blurry input as guidance. The first is safe and limited; the second is powerful and unfaithful.
Which unblur image method is better for old family photos?
Upscale, and keep the scan. Generative restore on a degraded face returns a plausible stranger, which is the one outcome that matters most in exactly this use case.
How small is too small to unblur an image?
Our source was 2,983 bytes for a full frame, and at that size every result is invented. As a rough line: under roughly 50KB for a full-frame photo, treat any sharp output as a new picture rather than a recovered one, and check the eyes and mouth corners against the original before you trust it.
Is any unblur image tool actually free?
Free tiers in this category are daily allowances, and on EzEnhancer they are explicitly same-day only. On Kavel, image tools run on free browser credits with no account, and the credit cost per model is shown before you commit.
