Text only · free to try
AI Watermark Remover for Text
Paste your text to remove deterministic hidden characters exactly, then rewrite the phrasing to reduce the statistical token patterns that current text watermarks rely on. Both steps run on every clean.
Privacy mode
Our app and AI provider process your text.
Who can read your text?
Private1× credits
Plaintext goes through the Simple Unmark app to the cleaning workload.
The app, the ordinary HTTPS and load-balancer path, the Python workload, and DeepInfra all process plaintext. Text and output are not stored in our database or analytics.
Confidential2× credits
Your browser verifies the workload before encrypting text to it.
The web backend receives metadata only. The attested workload decrypts the text, and DeepInfra still processes plaintext for the rewrite.
Confidential AIComing soon · 4× credits when available
The cleaner and rewrite model run together inside an attested GPU.
No external model API will receive plaintext. The browser and the approved confidential workload remain the only content endpoints.
Select to register interest — no text, no credits.
Local scan runs as you type.
Fresh wording. Same meaning.
Choose the privacy boundary before every rewrite.
Private is the lowest-cost path and stores no text in our application database. Confidential verifies Google Confidential Space in your browser and encrypts to a key the workload created for that one request, so our web backend receives no text — though DeepInfra still performs the rewrite. Confidential AI, with the model inside a confidential GPU, is coming soon.
Compare the three modes and their limitsHow this works
Deterministic marks can be removed exactly. Probabilistic patterns can only be reduced. Simple Unmark keeps the two separate and does not promise detector outcomes.
- The first step is deterministic: hidden Unicode controls, zero-width artifacts, tag characters and unusual spaces are removed or normalised, and the count of each is reported back to you.
- The second step rewrites sentence structure, clause order, transitions and vocabulary while preserving facts, names, numbers, tone and meaning.
- The two steps solve unrelated problems. Deleting invisible characters cannot affect a token-choice watermark, and rewriting alone leaves copy-paste artifacts in place.
Three steps
- 1
Paste the text you want to clean. A local scan runs in your browser as you type and shows which categories of hidden character it found, before anything is sent anywhere.
- 2
Run the clean. Hidden characters are removed first, then the wording is rewritten with the meaning held steady.
- 3
Compare the result against your original, then copy it. Check numbers, names and quotations before publishing anything that matters.
Worked example
Before
The report[U+200B] shows a 12% rise[U+00A0]in weekly signups.
After
The report shows a 12% rise in weekly signups.
One zero-width space (U+200B) removed and one non-breaking space (U+00A0) normalised to a plain space. The visible wording is untouched by this step; only the invisible layer changed. The rewrite step then changes the wording itself.
Scope
What this page can and cannot do
Can
- Remove the invisible code points it covers, exactly, and tell you how many of each it found
- Normalise non-breaking and typographic spaces that break search, validation and formatting
- Rewrite the passage so its token-choice pattern is no longer the model's original one
- Show you the before and after so you can judge the result yourself
Cannot
- Guarantee any particular detector's verdict, now or after that detector changes
- Prove that a piece of text was or was not written by a person
- Remove media provenance on this text page—the separate Media workspace handles supported image, video, and audio containers
- Preserve wording, because reducing a statistical watermark requires the wording to change
Submitted content and cleaned output are not stored in our application database, and no content is sent to analytics. For rewrites, Private mode routes plaintext through the application, its load balancer, and the processors; Confidential mode encrypts browser-to-workload so our web backend receives metadata only, while DeepInfra still performs text rewrites. Deterministic inspection on the invisible character remover runs entirely in your browser. See the privacy policy and methodology.
Questions
About ai watermark remover for text
Sources
- SynthID text watermarking and detectionGoogle AI for Developers · first-party
- How Claude's text watermarking worksAnthropic · first-party
- UTR #36: Unicode Security ConsiderationsUnicode Consortium · first-party
- Can an AI watermark really be removed from text?
- It depends on the mechanism. Hidden characters can be removed exactly, because they are literal code points. A statistical watermark is spread across the wording itself, so it can only be reduced by rewriting — and providers describe thorough rewriting as the thing that actually degrades detection. No tool can promise a specific detector outcome.
- Does this remove watermarks from images or PDFs?
- This page is the text cleaner. Use the Media tab or media watermark remover for provenance metadata in supported images, video, and audio. Visible logos and PDF editing are not part of the current media pass.
- Is the first clean free?
- Yes. Guests get three free cleans of up to 100 words each with no account. An account adds 10 starter credits and raises the limit to 5,000 words per clean.
- Will the meaning change?
- The wording changes by design; the meaning is instructed not to. Facts, numbers, proper nouns, tone and intent are preserved, but you should still read the result before using it.
Read the evidence
Guides behind this tool
- How AI Text Watermarks WorkHow hidden-character marks and statistical token watermarks differ, how detection works, and why removal claims should always be bounded.
- How to Remove AI Watermarks From TextA step-by-step method: identify which mechanism you are dealing with, remove hidden characters exactly, rewrite the statistical layer properly, then verify.
- Provider Text Watermark Status TrackerWhich AI providers document text watermarking, by what mechanism, whether a public detector exists, and when we last checked the primary sources.
Other cleaners
- Gemini Watermark RemoverSynthID Text · documented
- SynthID Watermark RemoverMechanism-specific
- Claude Watermark RemoverDocumented as of August 2026
- ChatGPT Watermark RemoverCopy artifacts · no text watermark documented
Need more than three cleans?
Private text starts at 0.1 credit per 100 words; Confidential mode uses 2× credits. Credits never expire, there is no subscription, and accounts unlock up to 5,000 words per clean.
See pricing