Free AI Text Detector

AI Text Detector — Was This Written by AI?

DeepFakeCheck's AI text detector helps educators, editors, recruiters, and editors-in-chief estimate the likelihood that a passage was written by ChatGPT (GPT-4, GPT-5), Claude, Gemini, Llama, or another large language model. Paste up to 10,000 characters of text and get a confidence score — no signup, no quota, no paywall.

How AI text detection works

Detecting AI-written text is fundamentally harder than detecting AI-generated images or audio, because text is a low-bandwidth signal and good prose from a human and good prose from a model can look almost identical. We use a layered approach to maximize signal:

• Perplexity and burstiness. Human writing tends to have higher variance in sentence complexity (some short sentences, some long, some weird) while LLMs trend toward an unusually even style. We measure both at the paragraph level.
• Stylistic fingerprints. Each major LLM has lexical and structural tells — GPT-4's "delve", "underscore", "embark"; Claude's longer sentences and triadic phrasing; Gemini's reliance on bulleted lists for almost every answer.
• Citation and fact-pattern analysis. LLMs hallucinate citations in characteristic ways. The detector flags suspect citation patterns even when the surface prose looks natural.

Which AI writing tools we cover

The text detector is evaluated against the current production releases of OpenAI ChatGPT (GPT-4, GPT-4 Turbo, GPT-5), Anthropic Claude (Opus 4, Sonnet 4.5, Haiku 4), Google Gemini (1.5 Pro, 2.0), Meta Llama 3 and 4, Mistral Large, and DeepSeek. We also detect text from popular wrappers like Jasper, Copy.ai, and Notion AI, which use one of those models underneath.

Common use cases for text detection

• Teachers and academic integrity offices screening student submissions — paired with a conversation with the student, not as a sole judgment.
• Editors and content managers reviewing freelance submissions for undisclosed AI use.
• Recruiters evaluating cover letters and writing samples.
• Publishers and PR teams spotting AI-generated press releases or astroturf reviews.
• Marketplace trust teams identifying AI-generated product descriptions or fake reviews.

Honest limits of AI text detection

We need to be candid: text detection is the least reliable of the four modalities we support. Carefully edited AI output, mixed AI/human passages, translated text, and writing from non-native English speakers can all produce false positives. We recommend using the detector as one input among several — never as a sole basis for accusing someone of academic dishonesty or contract violation.

Text detection FAQ

How long does the text need to be? 200 words is the practical minimum. Below that, neither perplexity nor stylistic signal is strong enough to be reliable.

Can it detect AI text in other languages? Our English signal is strongest. We also detect Chinese, Japanese, Korean, Spanish, French, and German with decent accuracy; smaller languages are less reliable.

What if the student edited the AI output heavily? The more a human revises the output, the harder it becomes to detect — by design. A heavily-edited piece may register as borderline or human.

Can it tell which AI model wrote the text? Sometimes. Strong stylistic fingerprints (Claude's structure, GPT's vocabulary) can identify the family of model. We surface this when confident.

Is my text stored? No. Submitted text is held in memory long enough to run the analysis, then discarded. We do not log, store, or train on it.