Free AI Text Detector
Paste any post, comment, or article and see how likely it is to be AI-written. Runs two independent open-source detection models plus a stylometry and quote-similarity scan — built to catch the exact tricks that fool single-score tools, right in your browser.
What it can catch
It doesn't identify which specific model wrote a text — it estimates the overall likelihood of AI involvement, and flags a couple of specific manipulation patterns common on forums:
ChatGPT-style replies
The generic, evenly-structured paragraphs typical of ChatGPT and similar chat assistants.
AI-written articles
Longer-form blog posts, guides, and "explainer" content produced end-to-end by an LLM.
Punctuation-stripped text
Removing commas and apostrophes is a known trick to fool single-score detectors — this tool flags it instead of being fooled by it.
Quoted-post rewriting
Replies that are really just a spun/reworded version of the post they're quoting, via a dedicated similarity check.
Short forum replies
Built to score short-form text natively, without needing to pad it to a minimum character count.
Mixed human + AI edits
Text that's mostly human-written but AI-polished may show up as a partial or inconclusive signal rather than a clean pass or fail.
Why this catches what single-score detectors miss
Most free AI text checkers — the kind commonly linked in forum "AI spam" reports — give you one percentage from one model. That approach has well-documented blind spots. Here's how this tool is built differently:
| Capability | Typical single-score detector | Cointikka AI Text Detector |
|---|---|---|
| Detection signals shown | One model, one score | 2 independent ML models + a stylometry heuristic, shown separately in green/red |
| Robust to punctuation-stripping | Score can swing 50+ points from removing commas | Flags abnormally low punctuation density as a manipulation signal |
| Catches quoted-post rewriting | Not checked | Dedicated quote-similarity scan (optional 2nd text box) |
| Handles short forum replies | Some need padding to a character minimum | Built for short-form text natively |
| Shows its work | One opaque percentage | Full signal breakdown with each model's raw label |
| Your text leaves your device | Usually, for the ML scoring | Never — models run locally via WebAssembly |
| Matching toolkit | Standalone | Same site also has a free AI Image Detector and a Bitcointalk Rank & Merit Tracker |
One documented example of the blind spot this is built to close: in community testing on a well-known crypto forum, one popular detector's score for the same post swung from over 90% "AI-likely" down to roughly 30% simply by removing the commas and apostrophes — nothing about the actual writing changed. Any detector that scores raw text fluency alone can be gamed this way; this tool treats an unusually low punctuation density in long, evenly-structured sentences as a signal in its own right, not something that silently lowers the score.
How to check if text is AI-generated
Three steps, no software to install.
Paste your text
Drop in a post, comment, or article — 50+ words gives the most reliable result.
Optionally add the quoted post
If it's a reply, paste the original post to check for rewording.
Analysis runs locally
Two models download once (cached after that) and run entirely inside your browser.
Get a full breakdown
See a plain-language verdict plus every signal that fed into it, not just one number.
Understanding AI text detection
A little context on how detection works, why one score isn't enough, and where it falls short.
How the detector works
The tool runs three independent signals and shows each one on its own, rather than blending them into a single score. Two are open-source language models — one trained on early ChatGPT-era text, one trained on the more recent RAID benchmark dataset across many modern generators — each downloaded once from a public model hub and cached by your browser afterward. The third is a stylometric heuristic that runs instantly, with no download: it looks at sentence-length variance ("burstiness"), vocabulary diversity, and the density of stock transition phrases (like "moreover" or "it's important to note") that show up disproportionately often in AI-generated prose. Each signal gets its own green (human-like) or red (AI-likely) badge so you can compare them and judge for yourself, and separate pattern checks flag things like abnormally stripped punctuation or high overlap with a quoted post.
Why combining signals matters
A single model scoring raw text fluency has a specific, well-documented weakness: it can be gamed by superficial changes — like stripping punctuation — that don't change the actual meaning of the text at all. Combining multiple, differently-trained signals and explicitly checking for known manipulation patterns makes the overall result harder to fool with any single trick, and showing the breakdown (rather than one bare percentage) lets you judge for yourself when the signals disagree.
Why local, browser-based detection matters
Every check on this page happens directly on your device using WebAssembly — the text itself is never sent to Cointikka or any third party. That matters if you're checking something sensitive: a draft you haven't published yet, a message someone sent you, or a post you're deciding whether to report. There's no server-side copy of your text and results come back in seconds. The only thing that does leave your device is an anonymous result summary — verdict, AI-probability %, word count — used solely to power the live usage stat on this page.
Limitations to keep in mind
No AI detector is perfect, and this one is no exception. It's most reliable on English prose of 50 or more words; very short replies, non-English text, and text that's been substantially paraphrased after being AI-written are all harder to score confidently, and the tool will show an inconclusive result rather than a forced verdict when its signals disagree. It also can't tell you which specific AI model produced a piece of text, only how likely AI involvement is overall. Treat the result as a helpful signal to combine with your own judgment and context, not as definitive proof either way.