The Best Free AI Detector

It measures a handful of statistical fingerprints that separate most machine-written text from most human-written text. The biggest ones are burstiness (humans mix long, winding sentences with short punchy ones; language models keep sentence length oddly even), contractions (people write "don't" and "it's" far more often than models do), stock phrasing ("delve into," "in today's digital landscape," "it's important to note"), sentence openers (a parade of "Furthermore," "Additionally," and "Moreover"), rule-of-three lists, and paragraph uniformity. Each signal is scored on its own, then weighted and combined into the overall AI likelihood you see in the gauge.

Honestly: good enough to be useful, not good enough to be proof. On unedited output from popular models it usually lands in the "likely AI" range, and on everyday human writing (emails, forum posts, first drafts) it usually lands in "likely human." The tricky middle is polished writing. A press release or a textbook chapter written by a careful human shares many of the same traits as AI output, and an AI draft that a person has rewritten by hand can pass as human. That's true of every detector on the market, including the paid ones, which is why universities and publishers have been backing away from using them as evidence.

Our advice: use the score as a prompt to look closer, then read the signal breakdown. If the only thing driving a high score is a lack of contractions, that's a style choice, not a smoking gun.

No. The whole analysis runs as JavaScript in your browser. Nothing you paste is uploaded, logged, or kept, which also means there's no usage limit and no account to create.

Usually one of three reasons. You write formally and avoid contractions. You lean on transition words at the start of sentences. Or your sentences are all about the same length, which happens a lot after heavy editing. Check the breakdown: if your text is being flagged for style rather than for stock AI phrases, a few small changes (vary your sentence lengths, cut the "Furthermore"s, let a contraction or two in) will usually bring the score down and, as a bonus, make the writing more readable.

It isn't tied to any one model. The patterns it looks for show up in text from ChatGPT, Claude, Gemini, Copilot, Llama, and most other large language models, because they come from how these models are trained rather than from any single product. Newer models and custom prompts that ask for a casual voice are harder to catch, so expect more "mixed" results on those.

At least 100 words for a reading, and ideally 300 or more. The signals are averages, and averages over two or three sentences swing wildly. There's no upper limit, though anything past a few thousand words won't make the result more reliable.