Marks and provenance
How the big model providers now tag their own output, what the tags can and cannot tell you, and the open standards around them.
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SynthID for text Google DeepMind Built into Gemini. Detector portal for images, audio and video; text detection through the open-source library.
A statistical watermark that tilts word choice while the model writes. Applied to text in the Gemini app since May 2024. The method was published in Nature in October 2024 and released as an open-source library with Hugging Face, so anyone can apply and detect a mark with their own key.
Detection needs the key that made the mark, so a Gemini mark can only be checked by Google or by a party Google authorises.
deepmind.google, checked 2026-10-31 -
Reference implementation of the text watermark for Hugging Face Transformers. Useful for anyone who wants to watermark their own model's output, or to study how the signal behaves after editing.
github.com, checked 2026-10-31 -
Developer guide to applying SynthID to Gemma and Gemini outputs, with the configuration options and the trade-offs between mark strength and output quality.
ai.google.dev, checked 2026-10-31 -
Claude text watermark Anthropic Applied automatically. Detection API in private preview for eligible organisations.
Announced August 14, 2026 and updated September 1, 2026. A version of SynthID-Text applied globally to future Claude models, with models released before August 2, 2026 to follow over the coming months. Detection uses Anthropic's key and answers only whether Claude likely wrote part of a passage. Access is open by application to regulators, law enforcement, media, fact-checkers, researchers, educators, EU civil society groups and enterprises with EU compliance duties.
Anthropic's own words: light editing probably will not remove the mark completely; a complete rewrite where every word is replaced will.
anthropic.com, checked 2026-10-31 -
textGrain OpenAI Opt-in for API customers worldwide, off by default. Rolling out to ChatGPT and Codex output in the EU only. Detector by application.
Announced October 5, 2026. OpenAI reports that at a 1 percent false positive rate its detector found the mark in about 95 percent of 400-token passages and about 80 percent of 200-token passages, with lower rates on constrained text such as mathematics. Detector access is limited to approved researchers and expert organisations. OpenAI says it plans to open-source the technique.
In OpenAI's own evaluation, replacing 10 percent of words with synonyms cut detection on 400-token passages from about 92 to 66 percent, and replacing 25 percent cut it to 17 percent.
openai.com, checked 2026-10-31 -
C2PA Content Credentials Coalition for Content Provenance and Authenticity Open specification. Free verification at contentcredentials.org.
A signed manifest that travels with a media file and records where it came from and what was done to it. Widely adopted for images, audio and video by camera makers, creative software and the large model providers. The EU Code of Practice treats secured metadata like this as one of its two marking layers.
Coverage for plain text is thin, because text is usually copied without any file container to carry a manifest.
c2pa.org, checked 2026-10-31 -
Drop in an image, video or audio file and read any attached C2PA manifest, including the signing organisation and recorded edits.
contentcredentials.org, checked 2026-10-31