By using our detector, you agree to our Terms.
Astra AI Detector shows probability, not proof — no AI checker is 100% accurate.
Model-aware detection
See if text came from ChatGPT (GPT-6 Astra, Sol), Claude or Gemini, and which sentences give it away.
By using our detector, you agree to our Terms.
Astra AI Detector shows probability, not proof — no AI checker is 100% accurate.
One detector for ChatGPT, GPT-5, GPT-4, Claude, Gemini, DeepSeek and Llama.
ChatGPT and the wider GPT family are the most common source of AI-generated writing, so a ChatGPT detector is where most people start.
Astra checks text for the statistical patterns these models leave behind — low perplexity, even sentence rhythm and the giveaway transitions GPT models favor — and highlights the sentences that look generated. It then does the same for Claude, Gemini, DeepSeek and Llama, so you don't need a separate detector for every model.
Paste any passage or upload a file above to check whether it came from ChatGPT, GPT-5, GPT-4 or another model, and see the AI-or-human balance sentence by sentence.
From paste to an explainable result in a few seconds, with nothing sent to a server.
Drop in the passage, essay, message or article you want to check — or upload a TXT, PDF, DOC or DOCX file.
Astra analyzes the writing on your device and compares it against patterns typical of ChatGPT and other large language models.
See an overall AI score plus highlights marking the sentences most likely to be ChatGPT-generated, so a flag is explainable rather than a bare number.
The same statistical read, tuned for ChatGPT, Claude, Gemini and the open models.
The most-tested family. Raw output is the easiest to flag; the score falls as text is edited or paraphrased.
Anthropic's models write fluently and evenly — Astra reads perplexity and rhythm to separate them from genuine human drafts.
Google's models are covered the same way, with sentence-level highlights showing where the signal is strongest.
Open models are included and refreshed as new versions ship.
Two statistical tells separate machine drafts from the zig-zag of human writing.
Generated text tends to be predictable (low perplexity) and even (low burstiness): steady sentence length, smooth transitions, and a habit of reaching for phrases like “Furthermore,” “It's important to note,” and “In conclusion.”
Human drafts zig-zag between the expected and the surprising, and vary their pace — a long sentence, then a short one, then a fragment. Astra surfaces those signals per sentence, so you can see the reasoning behind a flag.
You can read the full method on how AI detection works.
Different search terms, one evolving family of OpenAI models.
“GPT detector,” “GPT-4 detector” and “GPT-5 detector” all point to the same task: spotting text from OpenAI's models.
Astra treats them as one evolving family. Older GPT output is generally easier to flag; the newest models write more naturally, which is exactly why a low score is never a guarantee of human authorship and detection has to be kept up to date.
Check any passage without knowing in advance which tool produced it.
A modern detector can't only be a ChatGPT detector.
Astra also works as a Claude detector, Gemini detector, DeepSeek detector, and a detector for Llama, Grok and Mistral, so you can check text without knowing in advance which tool produced it. New models are added as they appear.
If you're specifically checking reworded model output, the paraphrase detector targets AI that has been rewritten or humanized.
New models and light edits both move a score — so read it as probability, not proof.
AI detection is an ongoing arms race: when a new model ships, detectors can lag until they're updated, and adding a few short sentences or paraphrasing can lower a score.
So a low score is never proof of human authorship, and a high score is never proof of cheating.
We publish what we can verify on the accuracy page and treat every result as a probability, with the evidence shown so you can judge it yourself.
A detector reads the statistics; you can also read the surface.
ChatGPT's default voice has recurring habits, and knowing them helps you decide when a passage is worth checking. Treat them as hints, not a verdict — careful human writers do some of these, and a quick edit removes most.
restating the question, or starting with "In today's fast-paced world" or "In the ever-evolving landscape of."
"Furthermore," "Moreover," "It's important to note," "That said," and a tidy "In conclusion" or "Overall" to close.
often with bolded lead-ins, even when the point does not need a list.
similar sentence and paragraph lengths, clean grammar, no typos, and no half-finished thoughts or lived-in detail.
that covers every angle and commits to none.
such as delve, tapestry, testament, underscore, robust, leverage, and navigate the complexities.
when text is pasted straight from a chat: "Certainly!", "Sure — here's," "I hope this helps," or "As an AI language model."
None of these is proof. Each is easy to paraphrase away, and plenty of polished human writing shares the same traits — which is exactly why a keyword blacklist makes a poor detector. Astra instead scores the underlying patterns, how predictable and how even the writing is, and highlights the sentences behind a flag so the reasoning is visible. Use the tells above to decide when to run a check, not to reach a conclusion on their own.
Short answer: no — and the reason is worth understanding.
OpenAI released an AI Text Classifier on 31 January 2023 and quietly withdrew it on 20 July 2023, citing a "low rate of accuracy."
By OpenAI's own reporting, the tool correctly flagged only about 26% of AI-written text as likely AI while mislabeling roughly 9% of human writing as AI — figures low enough that keeping it online did more harm than good. OpenAI has since said it is researching better provenance methods rather than shipping a replacement.
On watermarking, OpenAI has reportedly built a method that hides a statistical signal inside generated text, but it has not released it publicly — weighing user pushback and the risk of unfairly flagging non-native English speakers who use ChatGPT as a legitimate writing aid. So ChatGPT output today carries no public, verifiable watermark, unlike the SynthID signal Google runs in Gemini.
The practical takeaway: there is no first-party, authoritative "was this ChatGPT?" button. Every working detector — Astra included — is a third-party tool reading statistical patterns, and every result is a probability rather than a certificate. That is also why no single score should ever stand as proof. Astra's response to that limit is transparency: it shows the specific sentences behind a flag, so you can weigh the evidence yourself instead of trusting a bare number.
A detector reads AI-vs-human patterns; it can't fingerprint the exact release.
People search for a "GPT detector," a "GPT-4 detector," and a "GPT-5 detector" as if each needs its own tool.
Under the hood it is one job: estimating whether writing matches AI patterns or human ones. A detector reads signals like predictability and rhythm — it does not fingerprint OpenAI's specific model or version. From the text alone it cannot reliably tell GPT-4 from GPT-5, or ChatGPT from Claude.
So treat "GPT-4 detector" and "GPT-5 detector" as names for the source you are checking, not a promise that the tool can identify the release. Two honest implications follow:
What genuinely shifts across generations is difficulty, not identity. Raw output from newer, more heavily tuned models reads more naturally and tends to score lower or softer than older output — one more reason a low score is never proof of human authorship. Astra reports a single AI-versus-human probability across the whole GPT family and flags the sentences driving it, rather than pretending to pin down which version wrote your text.
Whether ChatGPT can spot itself, how much text you need, and what a high score really proves.
No. A chatbot cannot inspect its own training or reliably recognize AI text, so if you paste a passage and ask, it simply guesses — often with false confidence. It will sometimes insist a human paragraph is AI, or the reverse. Rely on a detector's statistical read, not the model's opinion.
Aim for at least about 40 words, and more is better — a paragraph or two gives the statistics room to stabilize. Single sentences and very short snippets are unreliable for every detector, Astra included, so widen the sample before you trust a score.
No. Some OpenAI models were seen inserting invisible Unicode characters in longer replies in 2025, but OpenAI described these as an unintended quirk, not a watermark. Editing, reformatting, or a copy-paste can strip them, so they are not a dependable signal — reliable detection reads statistical patterns instead.
Yes — Astra is built to flag text from ChatGPT and the GPT family, and highlights the specific sentences that read as generated.
Yes. Raw output is easiest to detect; heavily edited or paraphrased text is harder for any detector to catch, so treat the score as a probability.
Yes — Claude, Gemini, DeepSeek and Llama are all covered, so you can check text without knowing which model produced it.
They're covered too, and the model list is updated as new ones ship. Because the newest models write most naturally, treat any single result as a probability, not proof.
Paste or upload the text above and run the check, then read the AI score and the highlighted sentences. No detector can name the exact tool used — it estimates whether the writing matches AI patterns.
Often — reworded AI keeps patterns like uniform rhythm. See the AI paraphrase detector for humanized and rewritten output.
No. It's a strong probability, not proof — use it as evidence alongside context. See accuracy & limits.
Yes — free, no sign-up, and analysis runs entirely in your browser.