AI image detector
ChatGPT & DALL·E image detector
Images created in ChatGPT or through OpenAI’s image API are signed with Content Credentials. GPTTrace reads that signature — and when it has been stripped, falls back to a neural classifier and the image’s shape.
Free · no sign-up · your file never leaves your device
Drop a suspected ChatGPT image, click to choose, or paste
JPEG · PNG · WebP · AVIF · HEIC (Safari) — checked on your device
OpenAI labels its images — if you have the original file
OpenAI is a member of the C2PA coalition and has attached Content Credentials to its generated images since early 2024, starting with DALL·E 3. The credential is a signed manifest stored inside the file. It records that the picture was created by an OpenAI tool, using an action marked with the IPTC digital source type trainedAlgorithmicMedia, and it is signed with a certificate issued to OpenAI.
When GPTTrace finds that manifest, the verdict is marked “(provenance)”: the file itself says where it came from. You will also see who signed it and which actions were recorded, and you can open the full manifest in the C2PA viewer.
The limitation is equally important. Content Credentials live in metadata, and metadata is fragile. Screenshots, most social networks and many messaging apps remove it. So the absence of credentials never proves that an image is real — it only means the easy check is unavailable.
When the credentials are gone
For stripped copies, GPTTrace uses three weaker signals.
Image size
OpenAI’s models output a handful of fixed sizes: 1024×1024 squares, 1536×1024 or 1792×1024 landscapes and their portrait versions. An image at exactly one of those sizes with no camera data is suggestive. Re-sharing often resizes images, though, so this is only a nudge.
The look
Images from ChatGPT’s native generator became known for a warm, slightly yellow colour cast and very clean, even lighting, and for strikingly accurate text in signs, labels and posters. None of that is proof, but it is why so many viral “photos” of shop signs and documents turned out to be ChatGPT output.
The neural classifier
The classifier that runs in your browser was trained on output from thousands of generators. It looks at texture and noise statistics rather than content, so it can flag an OpenAI image even when the scene is mundane. Its confidence drops with heavy compression and small sizes, which is reflected in the result.
Where ChatGPT images cause problems
Because ChatGPT is the most widely used assistant, its images turn up everywhere: product listings with impossible photos, fake screenshots of conversations, invented historical pictures, school projects and insurance or refund claims with doctored evidence. In each case the best defence is the original file. Ask for it. A person who really took a photo can usually send the camera original, with its make, model and timestamp intact — and GPTTrace will show those fields too.
What OpenAI leaves in a file
These are the traces GPTTrace checks for. “Some files only” means the trace is often missing — a re-save, screenshot or social-media upload removes metadata — so its absence proves nothing.
| Generator | Where | What to look for | How reliable |
|---|---|---|---|
| OpenAI (DALL·E / ChatGPT images / Sora) | C2PA manifest | Content Credentials signed by OpenAI, with a c2pa.created action and digitalSourceType trainedAlgorithmicMedia | Documented by the vendor |
| OpenAI (DALL·E / ChatGPT images / Sora) | Pixels | Square or 3:2 sizes such as 1024×1024, 1536×1024 and 1024×1536 | Commonly seen |
How accurate is it? Our measured numbers
We test GPTTrace on labelled image samples and publish the results, including where it does badly. It is tuned to keep false accusations rare, so it misses some AI content rather than flag real work.
image check: AUC 0.938 (cross-validated)
679 labelled samples (399 AI, 280 human), run 2026-10-08. At the “Likely AI” line it caught 64% of AI samples and wrongly flagged 5% of human ones.
| Source | Truth | Samples | Result at “Likely AI” |
|---|---|---|---|
| gpt-image | AI | 40 | 30% caught |
| fullsize-photos | Human | 40 | 10% wrongly flagged |
| open-images-photos | Human | 40 | 5% wrongly flagged |
| lfw-faces | Human | 40 | 0% wrongly flagged |
| caltech-objects | Human | 40 | 3% wrongly flagged |
| coco-photos | Human | 40 | 0% wrongly flagged |
| ffhq-faces | Human | 40 | 0% wrongly flagged |
| celeba-faces | Human | 40 | 18% wrongly flagged |
Data sources and method: methodology & accuracy.