QuillBot AI Checker Tested: Does It Lower Your Score?

QuillBot AI Checker gives you a percentage, not a verdict — and on its own it will not bring that percentage down. In our own scoring run on 2026-09-28, 709 reference passages from 61 metadata-selected guides averaged an AI score of 26% while 12 unedited DeepSeek model passages averaged 33%. Human authorship of the reference passages was not independently verified. The checker tells you where the signal sits; the fix is the editing you do afterwards.

What does the QuillBot AI Checker actually measure?

It reads your text and estimates the probability that a language model produced it. The output is a percentage per document, and QuillBot’s own documentation describes it as a tool for checking whether content reads as AI-generated. It is not proof of authorship. Neither is ours. No detector can tell you who typed the words — only how closely the statistical texture matches model output.

That distinction matters when someone waves a score at you. A reading of “high” means the sentences share habits with generated text. Those habits are real and measurable: low variation in sentence length, uniform paragraph shape, connector words used at mechanical intervals, and a narrow band of common vocabulary. If you paste a human paragraph and the checker returns a low reading, you have learned almost nothing. If it returns a high reading on your own writing, you have learned which sentences to look at.

For a fuller picture of what the scores mean across tools, see AI Detector Accuracy — the short version is that two detectors can disagree on the same paragraph and both be reporting honestly.

How do you get the rate down once you have the score?

The rate comes down when you change the sentences that carry the signal. Not the whole document. Not the vocabulary. The flagged lines.

Here is the editing order that works, based on what our sentence-level detector highlights:

1. Score first, edit second. Run the text through a detector that shows per-sentence output. DeAIze’s detector scores the whole document and highlights each sentence by AI probability, so you are not guessing which lines caused the number.
2. Read the flagged sentences aloud. If a sentence is grammatically perfect but you would never say it that way, that is the tell. Rewrite it the way you would say it to a colleague.
3. Break the rhythm. Generated text tends to hold a steady clause length. Mix a four-word sentence into a run of long ones. Do it because the idea calls for emphasis, not as a trick.
4. Cut the connectors you did not choose. “Moreover”, “furthermore”, “in addition” — if you would not write them in an email, delete them or replace them with a full stop.
5. Re-score. You need to know whether the edit moved the number. If it did not, you changed style without changing signal.

That last step is the one people skip. It is also the one that turns a guess into a decision.

If you want the loop closed for you: DeAIze scores the text, rewrites only the flagged sentences, keeps a rewrite only when semantic similarity says the meaning survived, then re-scores and shows you before and after. The pricing page lists what that costs per word — no subscription, credits that do not expire.

What does a comparison of the options actually look like?

Here is the honest trade-off table. The third-party figures come from a writehuman.ai review of the Grammarly AI checker, which we checked against the sources it names; the DeAIze row is our own product.

Option	What it costs	What it is built for	Where it stops helping
QuillBot AI Checker	Free to use as a checker	A quick gut check on whether a draft reads generated	It reports a score; it does not edit your text or tell you which sentences caused it
Grammarly AI detection (inside Authorship Pro)	$12/month on annual billing, $30/month month-to-month, per grammarly.com/plans, as reported by writehuman.ai	Detection bundled with grammar and authorship logging	Accuracy claims around it range widely — writehuman.ai notes claims from 99% down to 33% depending on who tested, and says detection can fall to 12–16% once text is paraphrased
DeAIze	Free tier: 200 words on signup, no card. Paid: $20.99 / 1,000 words up to $199.99 / 30,000 words	Sentence-level detection plus a humanizer that rewrites only flagged sentences and re-scores	English-first — detection and rewriting cover English and 9 other languages, but non-English nuance is thinner
Manual editing only	Your time	Full control, no tooling cost	Slow on long documents, and you cannot tell whether your edit moved the score

The lesson in that third column is worth stating plainly: a checker that only reports a number leaves the whole job to you.

Why does the rate stay high after you paraphrase?

Because paraphrase does not remove the underlying signal. It swaps words while keeping the sentence architecture, the pacing and the paragraph shape. A detector reading for those patterns sees the same thing it saw before.

writehuman.ai reports that detection can collapse to 12–16% once text is lightly paraphrased, citing third-party tests. Read that carefully. It does not mean paraphrasing makes text undetectable. It means a detector’s ability to catch AI text drops when the text has been reworked — which is a statement about the detector, not a recipe for you. If your goal is to pass a check, paraphrasing is a weak lever. If your goal is to make the writing yours, it is the wrong lever entirely.

A 2023 Stanford study, cited in the same writehuman.ai piece, found GPT detectors flagged 61% of TOEFL essays as AI-written. That is the clearest argument I know for treating any single score as a probability estimate and nothing more. Non-native English writers get hit hardest, because the habits detectors read as machine-like — regular sentence length, formal connectors, limited idiom — overlap with what careful second-language writing looks like. If that is you, Why an AI Detector Flags Non Native English Writers covers what to document.

A worked example

Illustration, not a real submission. Take this sentence:

Moreover, the implementation of renewable energy policies is essential for the mitigation of long-term climate risks.

Every word is correct. It also has the shape of generated text: opener connector, nominalisation (“implementation”, “mitigation”), no named actor, no specific number or place. A detector reading burstiness and perplexity will find it flat.

Now the same idea, rewritten:

Renewable policy matters because climate risk compounds. Delay is expensive.

Two sentences. One is five words. The claim is narrower, the actor is implicit, and the rhythm is uneven. That is the edit that moves a rate — not a synonym swap.

You can run that pair through DeAIze’s detector yourself on the free tier and watch the sentence-level highlights change. On the example paragraph used on the site, a 92% AI score becomes 4% after humanizing, and the site reports an average reduction of 60%+ (best case 71%) — those are our own predicted scores, not a verdict from QuillBot or any other third party.

When this is the wrong choice

Do not buy a humanizer if any of these describe you.

• You need to pass a specific detector’s threshold as a guarantee. No tool can promise that. Detector scores are probability estimates, and DeAIze does not guarantee any score on any detector. If someone tells you otherwise, they are selling certainty they cannot deliver.
• The ideas are not yours. Humanizing cleans up your own AI-assisted draft. It is not a way to pass off someone else’s work or to submit generated analysis you cannot defend in a viva or a client call. That is a different problem, and a rewrite does not solve it.
• You have under 200 words and a deadline in ten minutes. Use the free tier, edit the flagged sentences by hand, move on.
• Your text is in a language outside the ten we cover. Detection and rewriting are English-first. Check before you pay.
• You want a subscription to a grammar tool anyway. Grammarly’s bundle may be the better buy if you need the grammar layer; the detection is a component, not the product.

What to do in the next ten minutes

Score the text. Find the flagged sentences. Rewrite those sentences the way you would say them out loud. Re-score. If the number moved, you are done. If it did not, you edited style instead of signal — go back to the sentences, not the vocabulary.

For the wider method, including how to handle a formal accusation rather than a casual flag, read AI Checkers Flagged You: How to Lower the Rate Honestly and the humanizing hub at Humanize AI Text. The ideas, data and conclusions in the final draft have to be yours. Everything else is editing.

---

Measurement note: figures in this article come from our own local detector observation on 2026-09-28 — n = 709 reference passages from 61 metadata-selected guides versus n = 12 unedited DeepSeek model passages, median AI score 25% and 34% respectively. Human authorship was not independently verified; passages from the same guide are correlated, so these figures do not establish a human false-positive rate. Method: methodology. Dated evidence: corpus observation, 2026-09-28.