the short version
- →one image detector is one opinion. a panel of independent ones, plus a confidence range, gives a steadier answer.
- →two signals carry the read. classifiers catch unwatermarked models and return a probability. provenance (C2PA, SynthID) is solid when present, and covers only models that embed it.
- →detection is hardest on the newest models, screenshots and heavily compressed re-shares. older Midjourney, DALL·E and Stable Diffusion are the most reliably flagged.
- →amige. is free to start, runs more than one detector on the free tier, and names the most likely model alongside the call.
how to tell if an image is AI-generated
the old visual tells still help, though they fade as models improve. read them as hints, not proof:
- →hands, teeth and ears. extra fingers, fused knuckles, too-even teeth and mangled ears are classic giveaways, though the 2025–2026 models have mostly fixed hands.
- →text and logos. garbled signage, invented letters and melted brand marks remain one of the more durable tells.
- →physics and reflections. shadows that point the wrong way, reflections that don’t match, jewelry or eyeglasses that dissolve at the edges.
- →backgrounds. warping, repeating patterns, and objects that blur into nonsense away from the focal point.
- →skin and texture. an airbrushed, plasticky over-smoothness, or pores and hair that look painted on.
the next model release trains away each of these tells. a clean image no longer proves a human made it, and a real photo can carry a weird artifact too. a detector helps here because it reads statistical fingerprints in the pixels the eye misses, and amige. reads several at once.
AI photos and AI art are checked differently
photos (a “real” person, place or event) carry the higher stakes, since a fake photo is the one that misleads. provenance matters most here: many phone cameras and editing tools now write C2PA Content Credentials, and an AI photo usually lacks a genuine capture trail. face-swaps and deepfakes count as a photo problem too; for clips, use the video detector.
AI art (illustration, concept art, “in the style of”) plays to classifier fingerprints and model attribution. the look of a model often reads more clearly than any single artifact. amige. keeps a per-model guide for each major image generator: Midjourney, DALL·E, Stable Diffusion, Flux, Imagen and Adobe Firefly.
what amige. checks
amige. runs a panel of independent detectors on your image, including Hive, AI or Not, Sightengine, BitMind, Winston, Illuminarty and Reality Defender, and shows you where they agree and where they split. several of these power other detector sites; amige. runs more of them at once and shows the disagreement.
on top of the panel you get two things a single score leaves out:
- →model attribution. a best guess at which model made it, like “looks like Midjourney v6”, always carrying the question mark.
- →provenance. a read of any C2PA Content Credentials and SynthID watermark in the file. strong evidence when it’s there, silent when it isn’t.
the free daily tier runs more than one detector. the Pass widens the panel and lifts the limits. the full method, limits included, sits on how it works.
where image detection falls short
image detection carries real limits. the main ones:
- →the newest models are the hardest. accuracy drops on the latest releases, which are tuned to look photographic. a confident call on a current-gen image carries weight without settling the matter.
- →screenshots and compression hurt. re-saving, cropping and screenshotting strip metadata and erode classifier signals. scan the original file when you have it.
- →watermarks cover only some models. C2PA and SynthID hold up when present, though most open models embed nothing. a missing watermark proves little on its own.
- →false positives happen. a real photo can read as AI, especially after heavy editing or upscaling. one number won’t carry a serious decision.
amige. shows a range and a panel for this reason. read the number as a starting point.
questions
how do I check if an image is AI-generated?
drop the image into an AI image detector. amige. runs it through several independent image classifiers at once and shows you where they agree and where they split, names the most likely model (‘looks like Midjourney v6’), and reads any embedded provenance (C2PA Content Credentials and SynthID watermarks). a panel of detectors gives a steadier read than one score on its own.
is there a free AI image detector?
yes. amige. has a free daily scan tier that still runs more than one detector on your image. Google’s SynthID check is also free, though it only flags images from models that embed the SynthID watermark. a free tier covers a gut-check. for anything that carries weight, read the per-detector breakdown over a single free score.
how accurate are AI image detectors?
they score higher in lab benchmarks than on real, re-shared images. classifier-based detection is probabilistic, and independent testing shows accuracy falls on the newest image models and on screenshots, crops and heavily compressed re-shares. watermark and metadata checks (SynthID, C2PA) hold up well when present, but cover only models that embed a signal. a panel of independent detectors fails less often than any one, which is why amige. shows all of them. read any single percentage as a starting point.
can it detect Midjourney, DALL·E and Stable Diffusion images?
those are the models classifier-based detection is trained hardest on, so a confident call on older versions usually rests on solid ground. the newest releases (Midjourney v7, Flux, Firefly, Imagen) are built to be harder to flag and accuracy drops on them, so amige. shows a wide ‘uncertain’ band on borderline cases. amige. also keeps a per-model guide for each major image generator.
does it work on screenshots?
a screenshot makes it harder. it strips C2PA metadata and can weaken classifier signals, so a screenshotted AI image is harder to call than the original file. SynthID’s pixel watermark survives screenshots and compression better than metadata does. scan the original file when you have it.
can an AI image detector be fooled?
yes, and a trustworthy tool says so. editing, compositing, upscaling, re-screenshotting and adversarial tweaks can all push an image past a detector, and a real photo can occasionally trip a false positive. that is why amige. shows a panel of detectors and a confidence range, and reports the model guess alongside the call. read the number as the start of the question.
sources.
- 01C2PA Content Credentials — technical white paper (2025)the provenance standard amige. reads; also covers why C2PA metadata gets stripped by most social platforms.
- 02Google — SynthID detection built into Chrome and Searchbacks the free, watermark-only SynthID check and its survival through screenshots and compression.
- 03