Claude AI Detector

Looking for a Claude AI detector or Claude AI checker? Paste a passage of 100 words or more into the free checker and V4, our current engine, returns an AI-writing signal score from 1 to 99, a stability range and one of three verdicts: Likely human-written, Uncertain or Likely AI-written. V4 was trained on writing from current Claude models alongside eight other families, and in our sealed test of 17 October 2026 it scored 65 or more on 1,045 of 1,048 new Claude texts of 150 words or more. Use the result to decide what deserves a closer look, not as proof of who wrote a text.

This guide explains what a Claude AI checker can and cannot tell you, how to check a text step by step, how to read each part of the result, and how V4 learned Claude’s writing patterns.

What Is a Claude AI Detector?

A Claude AI detector is a tool for checking whether a piece of writing was generated, or heavily assisted, by Anthropic’s Claude. People use the phrase for anything from a quick check on a student essay to an editor reviewing a freelance draft. In practice no detector reads a hidden Claude signature: ordinary text carries no watermark that names the model behind it.

What a detector can do is measure how closely a passage matches the writing patterns of the AI models it has studied. AI Detector Checker’s V4 engine is a fine-tuned text classifier that reads a passage in overlapping windows. It was trained on texts from nine model families, Claude among them, and on a large body of human writing dated 2021 or earlier, before writing assistants were in wide use. That is why the same check works for text from Claude, ChatGPT, Gemini, DeepSeek and other assistants.

Used well, a Claude detector is a screening tool. It points you to the passages that deserve a closer look; it does not replace the evidence of how a document was actually written. How the detector works explains the engine in plain terms.

How to Check Text That May Have Been Written With Claude

1. Open the detector. Go to the free AI detector on the homepage. No account is needed.
2. Paste at least 100 words. A full paragraph or longer gives the engine more to read. From 150 words up, human writing is wrongly flagged far less often.
3. Check the original wording first. Run the passage exactly as you received it, before anyone edits it, and do not rewrite it just to move the score.
4. Read the whole result card. Note the score, the verdict, the stability range and the line that says how often human texts of that length reach the same zone.
5. Add context. Compare drafts, sources, revision history and earlier writing samples before you draw any conclusion.

Checking several documents? Run them one at a time, or use compare mode to check up to three passages side by side. Pasting unrelated texts into one box can hide real differences between them.

How to Interpret a Claude Detector Result

Every check returns an AI-writing signal score between 1 and 99. The same number means the same thing at every text length, because each length band is anchored to its own measurements and 65 is always the line where the AI verdict starts. The score is not the share of the text written by AI, and it is not a probability.

Under the verdict, the card shows two figures from our sealed test for your text’s length: how often human texts reached 65 or more, and how often AI texts did. At 150 to 299 words, for example, about 1 in 1,000 human texts reached the AI zone.

Reading the passage

V4 scores the passage as a whole and does not highlight individual sentences. When a text lands in the AI zone, read it yourself: look for claims without sources, generic phrasing, and a structure or tone that does not match the writer’s other work.

Uncertain results

An Uncertain verdict means the evidence is mixed. Add more of the same text if you have it, look at the drafts, and leave the question open rather than forcing a verdict. Every line on the card is explained in Understanding AI Detector Results.

Can It Detect Claude Sonnet, Opus, or Haiku?

Yes, as AI writing, and with similar results across the Claude models we tested. Every tier scored high in the sealed test: the largest group, from Claude’s flagship model, was caught 99.83% of the time at 150 words or more, the mid-tier model 100.00%, and the smallest model 97.78% on a smaller sample. The full list is in the evidence table below.

What V4 cannot do is tell you which tier wrote a passage. It does not separate Opus from Sonnet or Haiku, or Claude from another assistant. Labels such as “Claude Opus detector” describe the text you are checking, not a model-identification feature.

Why Claude-Generated Text Can Be Hard to Identify

Claude has no single style. The same model writes a terse email, a lab-report summary or a long opinion column depending on the prompt, and people edit what it gives them. Our previous engine caught only 27.58% of the same sealed Claude texts, partly because its training data included Claude writing from just one model. V4 was trained on texts from the current Claude models, but some things still make any Claude text harder to judge:

• Prompts change style: tone, audience and format can move a text toward or away from typical AI patterns.
• Editing changes the signal: rewriting, cutting and rearranging can lower the score in ways no one can predict.
• Translation changes the language: a translated passage carries choices from both the source and the translation.
• Short text gives less evidence: at 100 to 149 words V4 caught 98.00% of Claude texts, against 99.71% at 150 words or more, and short human texts are flagged more often too.
• Careful human writing overlaps: formal, academic and policy writing can be as regular as AI text.

How V4 Was Trained on Claude Text, and How Well It Detects It

Claude writing was part of V4’s training data, alongside eight other model families. To measure what that achieved, the frozen engine was scored once, on 17 October 2026, on new Claude texts that were locked away before training began and never used to tune it. A text counts as caught when it scores 65 or more.

How the test texts were made

From 10 to 13 October 2026 we generated Claude texts for 35 kinds of writing, from cover letters and lab-report summaries to opinion columns and forum answers, in 6 styles: plain, humanised, student, formal, non-native and casual. Half of the topics came from a broad list and half were derived from real human writing, so the subjects stayed realistic. Most texts came through the Anthropic API, and the two larger Claude models wrote half of their texts with extended reasoning switched on. A further set was written in Claude Code on a Claude subscription: 356 of 359 of those texts were caught. Only the final answer was scored, and near-duplicates were removed first.

What else the test showed

• Length: 98.00% of Claude texts were caught at 100 to 149 words, 99.34% at 150 to 299, 99.72% at 300 to 599 and 100.00% at 600 or more.
• Unseen models: when Claude was left out of training entirely in the development test, V4 still caught 96.67% of Claude texts, so it does not depend on having seen Claude before.
• Rewriting tricks: on the development set, the hardest trick still left 97.40% of AI texts in the AI zone.
• Human writing: 4 of 2,863 human texts of 150 words or more, from sources the engine never trained on, reached 65.

The full sealed test, with every family, length band and human source, is on the evidence page. The methodology explains how the sets were built and locked.

False Positives, Missed Detections, and Edited Text

A false positive is human writing that lands in the AI zone. In the sealed test that happened to 11 of 1,136 human texts of 100 to 149 words, about 1 in 100, and to 4 of 2,863 at 150 words or more. A missed detection is AI text that scores below 65; for Claude, V4 caught 1,045 of 1,048 texts of 150 words or more.

Some kinds of human writing are flagged more often than others. Non-native English and formal speeches from 2024 and 2025 had higher false-flag rates than other human writing; the evidence page lists them. Editing works the other way: once a Claude draft is rewritten, paraphrased or translated, the sealed-test figures no longer apply and the score usually falls.

A low score after editing does not prove the final text is human, and a high score does not prove misconduct. Read what to do if your text is flagged before acting on any result.

Use a Claude AI Checker as One Part of a Review

If your own writing was flagged, follow the steps in What to Do If Your Text Is Flagged.

Compare Other AI Model Guides

V4 was tested on nine model families, and each guide reports that family’s own sealed-test results:

• ChatGPT AI Detector
• Gemini AI Detector
• DeepSeek AI Detector
• Kimi AI Detector
• Qwen AI Detector
• GLM AI Detector
• MiniMax AI Detector
• Llama AI Detector
• Microsoft Copilot Detector
• View all AI model guides

Claude AI Detector FAQ