Grammarly AI Checker Free: The Verdict and How to Lower the Rate

Grammarly’s AI checker free tier lets you paste text and see a percentage, and that is most of what the free version does. It does not tell you which sentences raised the number, and it does not rewrite them. If you just got a high reading, the useful next step is sentence-level detection plus targeted edits, not another paste into another box.

What does the free Grammarly AI checker actually show you?

You paste a paragraph into the Grammarly editor, and the AI detection feature returns a share of the text it considers likely machine-generated. The number is a probability estimate, not proof of authorship. Grammarly’s own plans page lists paid tiers, and the detection feature sits inside those paid plans rather than standing alone: grammarly.com/plans shows $12/month on annual billing and $30/month month-to-month, which writehuman.ai describes as a 2.5x penalty for paying monthly. That is the trade-off. A free or trial read gives you a single verdict on the whole document, and the paid plan gives you the same style of verdict with more room to run it.

What the checker does not hand you is a repair plan. A document-level score of any size tells you that something in the text triggered the model. It does not say whether the trigger is one long sentence, a stock transition, or a paragraph that repeats the same rhythm six times. Without that breakdown you are guessing at edits.

There is a second thing worth knowing before you panic. Detection accuracy claims for tools in this category are all over the place. writehuman.ai reports that published accuracy claims range from 99% (Grammarly’s own figure) to 33% (a competitor’s counter-test), and that detection collapses to 12-16% once text is paraphrased, per 2026 third-party tests. Both numbers can be real and still describe different test sets. Treat any single reading as one signal.

Why did a human-written draft still get flagged?

This is the part that unsettles people, and it deserves a straight answer rather than reassurance.

We ran our own measurement on 2026-09-28, scoring two corpora with the DeAIze detector at a 30% flag threshold. The human-written sample was 709 hand-written DeAIze guides. Mean AI score 26%, median 25%, range 0-69%. At that threshold, 239 of the 709 were flagged. These are real human documents, written by people, and roughly a third of them crossed the line we set. Meanwhile 12 unedited model passages from fixed prompts scored a mean of 33% and a median of 34%.

Read those two sets of numbers side by side. The human sample and the unedited machine output are close, and the human sample has a wider spread. That is what a probability estimate looks like in practice. A flag is a prompt to edit, not a verdict on who you are.

If you want the score and the sentence-level breakdown in one pass, DeAIze shows both, and the humanizer only rewrites the lines that carried the signal. Free tier is 200 words on signup, no card: start here.

Which option should you use for your situation?

The right tool depends on what you need out of the reading, not on which one has the loudest claim.

Option	What it costs	What you get	Good for	Watch out for
Grammarly AI checker	Free to try; grammarly.com/plans lists $12/month annual and $30/month monthly	A document-level AI share inside a broader writing assistant	A quick gut check on one paragraph while you are already editing there	No sentence-level map, no rewrite loop
DeAIze	Free tier 200 words; Starter $20.99 / 1,000 words, credits never expire	Sentence-level scores, closed-loop rewrite, before/after re-score	Knowing which lines carry the signal and fixing only those	It is a focused tool, not a full grammar assistant
Manual editing pass	Your time	Full control, no cost	Short documents, or when you need to keep every claim exact	Slow, and easy to over-edit your own voice out
Do nothing	Nothing	Nothing changes	Almost never the right answer if a deadline is close	The reading will not improve on its own

Grammarly’s checker and DeAIze answer different questions. Grammarly tells you whether the document reads machine-made. DeAIze tells you which sentences do, and then runs the rewrite as a closed loop: score, rewrite only the flagged lines, keep a rewrite only when semantic similarity says the meaning survived, re-score, report before and after. On the example paragraph used on the site, a 92% AI score becomes 4% AI.

How do you bring the rate down without wrecking your meaning?

Work at the sentence level, in this order.

1. Score first, edit second. Get a reading on the whole document so you know how much work you have. Do not start rewriting blind.
2. Find the flagged lines. A document-level number without a per-sentence view sends you editing paragraphs that were never the problem. You want the two or three lines carrying the signal.
3. Fix the pattern, not the synonym. Swapping words does not change rhythm. Long, evenly weighted sentences with the same structure are the tell. Break one, merge two, and put a short sentence where the reader expects a long one.
4. Re-score and compare. If the reading did not move, your edit did not touch the trigger. Try the next flagged line.
5. Read it aloud. Anything you would not say out loud is a candidate. This catches more than most people expect.

Here is a labelled illustration, not a real score. Before: “It is important to consider the various factors that contribute to the overall outcome of the process.” After: “Three things decide how this turns out.” Same idea, different rhythm, and the second version sounds like a person wrote it.

The 2023 Stanford finding that writehuman.ai cites is worth holding in mind here: GPT detectors flagged 61% of TOEFL essays as AI-written. Those essays were written by people, many of them non-native English writers whose prose is more regular than a native speaker’s. If that is your situation, the fix is the same sentence-level work, but you should also document your process, because the flag is more likely to be a false positive. Our guide to why AI detectors flag non-native English writers covers what to keep on record.

When is this the wrong choice?

Be honest with yourself about the situation before you pay for anything.

Do not run this if the text is not yours. Humanizing a draft you did not write and cannot defend is misrepresentation, and no score reduction changes that. The ideas, data and conclusions have to be your own work.

Skip it if you have already made the text worse. If you have paraphrased twice and the reading went up, stop. More passes flatten your voice further. Go back to your original draft and edit that instead.

Skip the paid tier for a one-off 200-word email. The free tier or a manual pass will do. Credits are useful when you have a backlog, not for a single paragraph.

Skip it if you need a guaranteed number. No tool can promise a specific score on a specific detector. DeAIze does not guarantee any particular score on any detector, and neither does anyone else who is being straight with you. If you need the output checked against real third-party detector APIs, DeAIze cross-checks against configured services such as GPTZero, Turnitin, Copyleaks, Originality.ai and Sapling rather than trusting an internal guess. That is a stronger signal, still not a promise.

A short checklist before you submit

• Run detection on the whole document, then read the per-sentence breakdown.
• Edit only the flagged lines. Leave the clean ones alone.
• Vary sentence length deliberately, including at least one short sentence per paragraph.
• Re-score after editing and compare before and after.
• Keep your original draft and your edit history in case you are asked how the text was produced.
• If you used AI anywhere in the process, follow your institution’s or client’s disclosure rules. Our humanize AI text hub covers the workflow end to end.

The uncomfortable truth is that a free checker reading is one data point from one model on one day. It can be wrong in both directions. What you control is the text, and a sentence-level pass is the part that actually moves the number.

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Measurement note: figures in this article come from our own detector run on 2026-09-28 — n = 709 hand-written guides versus n = 12 unedited model outputs, median AI score 25% and 34% respectively. Method: /methodology/.