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AI Detector

Detect whether text is AI-generated.

This tool outputs the probability that a piece of content was AI-generated by a model such as GPT-3.5 or ChatGPT.

Tags: ai detector chatgpt detector ai content detector gpt-3 output detector gpt-4 detector ai text detector

Access AI Detector API

API Docs Contact Us

Install Extension

Install browser extension Install Sapling


Type or paste text above to score. Note that the AI detector becomes much more accurate after 50 or so words. The token count (approximately the word count) will be shown as part of the score output.

No current AI content detector (including Sapling's) should be used as a standalone check to determine whether text is AI-generated or written by a human. False positives and false negatives will regularly occur.

The top section will show the overall score and highlight portions of the text that appear to be AI-generated.

The bottom section will highlight sentences that appear to be AI-generated.

The detector for the entire text and the per-sentence detector use different techniques, so use them together (along with your best judgement) to make an assessment.

Developed by former researchers at:

Cal Stanford Google

Looking for other ways to score content? Contact us.



  • Better handling of whitespace.
  • Better calibration.


  • Trained on more ChatGPT-like data.
  • Sections that are likely to be AI-generated highlighted in red.
  • Improved robustness to small changes.
  • Sentence scores using a complementary method.

Coming soon

  • Improved GPT-4 support.
  • Increased text length limit (8K characters currently available for Pro users).
  • Improved accuracy for shorter texts.

Frequently Asked Questions

Recently, models such as GPT-3, GPT-3.5, ChatGPT, and GPT-4 have led to the rise of machine-generated content. This synthetic content is increasingly indistinguishable from human-written content.

Despite rapid progress, these models continue to have shortcomings such as hallucinated facts as well as consequences such as enabling cheating in language courses.

This AI text detector tool provides a way of screening whether a piece of content is written by a human or machine.

The AI detector uses a machine learning system (a Transformer) similar to that used to generate AI content. Instead of generating words, the AI detector instead generates the probability it thinks each word or token in the input text is AI-generated or not. The result is visualized above for both the entire text as well as for each sentence.

Accuracy must be measured on a specific test or benchmark. There are also multiple measurements of "accuracy" for detection tools. These measurements balance catching as many AI-generated texts as possible while keeping false positives low. On our internal benchmarks, Sapling catches more than 97% of AI-generated texts while keeping false positives below 3%. Please note that these benchmarks tend to use longer texts and may not be representative of your text.

Sapling can have false positives. The shorter the text is, the more general it is, and the more essay-like it is, the more likely it is to result in a false positive. We are working on improving the system so that this occurs less frequently.

The free version is currently truncated to 2000 characters (roughly 400 to 500 tokens). Pro and Enterprise Sapling subscribers can paste texts of up to 8000 characters (roughly 1600 to 2000 tokens). For texts beyond that, please break up the text into multiple sections, or consider using our API. If you plan to process more than 10 million characters/month, contact us to see how we can better support your use case.

Yes! You can find the API documentation here.

While language models are becoming more advanced, they usually use a similar machine learning architecture and a similar dataset on which they're trained. Hence, even AI detectors trained on earlier versions of language model outputs should perform significantly better than random on successive models.

That said, to get the best performance, detectors should be trained on the outputs of the latest systems. Sapling regularly updates its detector after re-training it to keep it up-to-date with new systems.