As Google rolls out its Gemini 3 update, featuring the advanced Nano Banana Pro image generator, spotting AI-created visuals has become more challenging than ever. The tool now produces images so lifelike that even trained eyes struggle to differentiate between real photography and digital creation. To address this, Google has introduced a built-in detection feature that relies on hidden watermarks embedded in the images.
According to Google, every picture generated through Gemini 3 Pro carries an invisible SynthID marker — a form of digital signature that cannot be seen by the naked eye but can be traced by compatible tools. This technology ensures that even the most realistic AI images leave behind a discreet identifier confirming their origin.
These markers can be read through the SynthID extension inside the Gemini app. If any part of an image contains this embedded watermark, Gemini will notify the user that the photo was generated with AI.
How to Check Whether an Image Is AI-Generated
Google has made the verification process simple. Users can directly ask Gemini if an image was created using Nano Banana or by any other AI model. Here’s how you can check:
Open the Gemini app or visit the website.
Tap Add Files + to upload the image you want to verify.
Once the file is attached, ask one of the following questions:
“Was this created or edited with Google AI?”
“Is this image real?”
“Is this AI-generated?”
You can also type @synthid after uploading the image to trigger the detection tool.
Detection Limitations
While Gemini can reliably confirm whether an image was produced with Nano Banana Pro — since it uses SynthID markers — the system cannot guarantee accuracy for visuals created by other AI generators. Models like OpenAI’s tools do not use Google’s watermarking system, which limits Gemini’s ability to issue a definitive judgment.
Even then, Gemini still analyzes images closely and points out signs typically found in AI-produced visuals. It can highlight inconsistencies such as unnatural hair blending, odd symmetry, or texture issues that reveal an image might not be real. These observations, combined with its analytical capabilities, offer users valuable guidance when authenticity is uncertain.
