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Sometimes—but not reliably for every passage attributed to ChatGPT. OpenAI announced textGrain on October 5, 2026, an invisible statistical watermark for eligible ChatGPT and Codex text in the European Union and for select API models when customers opt in. Its detector is initially limited to approved researchers and expert organizations. OpenAI’s own evaluations show that the watermark can be missed, especially in short or constrained text, and that editing can weaken it. A detection is a limited clue that a supported OpenAI signal is present—not proof of who wrote the text or how much a person contributed.
What an AI text watermark checks
OpenAI’s textGrain watermark is a statistical pattern embedded in generated wording, not a visible label or hidden character. The model subtly adjusts its random choices among possible words or word pieces; a detector checks for the resulting pattern. OpenAI describes the mechanism and its limits in its text provenance explanation and the OpenAI Help Center overview.
This differs from a third-party AI-writing classifier. A watermark detector looks for an embedded, provider-specific signal in eligible output. A classifier instead estimates whether text is AI-generated by analyzing patterns in the writing after it has been produced. A classifier’s result is not a check for an OpenAI watermark.
Where OpenAI watermarking is available
OpenAI’s October 5, 2026 announcement says API customers globally can opt in to text watermarking for select models; it is off by default in the API. Eligible ChatGPT and Codex text output in the European Union is scheduled to receive invisible watermarks over the coming weeks. That is not a global default for ChatGPT at launch.
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OpenAI is initially restricting text-detector access to approved researchers and expert organizations, with applications reviewed case by case. Its content provenance documentation describes the checker’s scope. Most readers therefore cannot assume that a passage has a watermark or that a public tool is available to check it.
How well does the watermark detect text?
OpenAI reports the following textGrain results. They come from separate evaluations and specific test conditions; they are not guarantees for arbitrary passages.
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| OpenAI evaluation | Reported result | What it means |
|---|---|---|
| Psychology passages, 200 tokens | About 80% detected at a target 1% false-positive rate | In this evaluation, roughly one in five passages was not detected. |
| Psychology passages, 400 tokens | About 95% detected at a target 1% false-positive rate | Longer passages performed better in this test than 200-token passages. |
| Editing evaluation, 400 tokens, baseline | About 92% detected | The baseline result applies to this editing evaluation, not to every 400-token passage. |
| Same editing evaluation, 10% of words replaced with synonyms | About 66% detected | Synonym edits reduced detection in the test. |
| Same editing evaluation, 25% of words replaced with synonyms | 17% detected | More extensive synonym replacement sharply weakened detection. |
OpenAI also reports substantially lower detection for mathematics, where wording choices are more constrained. Taken together, these results show why a negative result cannot rule out ChatGPT use: length, subject matter, and editing can all affect whether the signal is found.
What a positive or negative result can establish
A positive result
A positive textGrain check means the detector found a supported OpenAI watermark signal. OpenAI says, “A watermark does not identify the user.” It does not reveal an account, prompt, or conversation, or establish how much a person edited or contributed. It also does not determine ownership, responsibility, legality, or accuracy.
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A negative result
A negative check does not show that ChatGPT was uninvolved. The passage may come from a legacy model, predate supported watermarking, or have had its signal weakened by editing. OpenAI’s API documentation also says the provenance checker does not currently detect content generated by another company’s AI system.
A chatbot’s self-report
Asking ChatGPT whether it wrote a passage is not verification. OpenAI warns that ChatGPT cannot reliably identify its own writing and may make up an answer. Its guidance is in “Can I ask ChatGPT if it wrote something?”
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How watermarks differ from AI-writing classifiers
| Method | What it checks | Key limitation |
|---|---|---|
| OpenAI text watermark detector | A provider-specific signal embedded in eligible OpenAI output | It only applies when supported watermarking was used, and detection can fail or weaken after editing. Access is initially restricted. |
| Third-party AI-writing classifier | Patterns in the finished text that may suggest AI generation | It does not detect an embedded OpenAI watermark and is not proof of ChatGPT authorship. |
| ChatGPT self-report | The chatbot’s response to a question about a passage | OpenAI says the model cannot reliably know whether it generated the text. |
For historical context, OpenAI’s separate AI Text Classifier correctly labeled 26% of AI-written examples as “likely AI-written” and mislabeled human-written text as AI-written 9% of the time in its English challenge-set evaluation. OpenAI discontinued that classifier on July 20, 2023, citing low accuracy. Those figures describe a classifier—not textGrain—and should not be used to estimate watermark performance. OpenAI’s original notice is “New AI classifier for indicating AI-written text.”
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to interpret a claim that text came from ChatGPT
- Check what was actually tested. A generic classifier score is not an OpenAI watermark result.
- Consider whether the text could be eligible. OpenAI’s rollout is limited by region, product, model, and API opt-in; not all ChatGPT text carries a watermark.
- Treat a positive result narrowly. It supports the presence of a watermark signal, not a claim about a particular writer, the extent of human involvement, or misconduct.
- Do not treat a negative result as exoneration. Short or constrained text and subsequent edits can make a watermark harder to detect.
- Use other evidence for consequential decisions. A watermark does not establish authorship, intent, accuracy, or responsibility.
The broader landscape includes provenance and detection techniques beyond text watermarking; the National Institute of Standards and Technology surveys these approaches in its overview of technical approaches to digital content transparency.
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