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AI Image Detector

Model:
Upload an image and our vision model checks it for signs of AI generation — warped hands, garbled text, impossible reflections, diffusion artifacts. Get a probability score and the specific signals it spotted.

Upload an image to analyze

JPG, PNG, WebP up to 10MB

Preview
~500 tokens per image

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0%

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Signals detected:

    This is an AI-powered estimate, not a court-admissible forensic test. False positives and false negatives happen — use judgment alongside it.

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    Resultaat
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    Bezig met verwerken van uw verzoek...

    Paste or upload any image and find out whether it was AI-generated. Free, no account, instant result with confidence score.

    Hoe gebruikt u dit middel? AI Image Detector

    1
    Voer uw invoer in

    Typ tekst, upload een bestand of beschrijf wat u wilt. Er is geen account nodig.

    2
    Klik op genereren

    Onze AI verwerkt uw verzoek in seconden met behulp van de beste open-source modellen.

    3
    Downloaden & delen

    Download, kopieer of deel uw resultaat. Gratis voor persoonlijk en commercieel gebruik.

    Use this tool via API

    Automate this tool from your own code. OpenAI-compatible REST endpoint, Bearer-token auth, no extra SDK required. Token costs match the web interface.

    API Documentation Get API Key 
    curl -X POST https://api.free.ai/v1/image/generate/ \
  -H "Authorization: Bearer sk-free-..." \
  -H "Content-Type: application/json" \
  -d '{"prompt": "A sunset over mountains", "model": "sdxl"}'

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    AI Image Detector — FAQ

    Upload any image and our vision model checks it for signs of AI generation — warped hands, garbled text, impossible shadows, diffusion artifacts. You get a probability score, a verdict, and the specific signals it spotted.

    Yes. Each check costs about 500 tokens. Signed-up users get 10,000 tokens/day free.

    Good for catching obvious AI imagery from older models (Stable Diffusion 1.x, early Midjourney, etc.). Much harder on state-of-the-art models like FLUX and Nano Banana — those can pass the test. Treat it as a heuristic, not forensic proof.

    Hand and finger anatomy, teeth, symmetric eyes, text legibility, impossible reflections and shadows, overly smooth skin, warped backgrounds, and repeated textures — classic tells of diffusion model outputs.

    0-40% = likely real. 40-70% = uncertain, check manually. 70-100% = likely AI-generated. The confidence badge tells you how sure the model is about that estimate.

    Modern AI images are hard to distinguish. If the model isn't confident either way, it says so rather than guessing. That's honest — other detectors will give you false confidence.

    No. This is a quick heuristic, not a forensic tool. Courts require provenance-based verification (C2PA, cryptographic signing). Use this to sanity-check, not to settle disputes.

    Qwen 2.5-VL — a multimodal vision-language model. We prompt it specifically to look for the telltale signs of generative image artifacts.

    JPG, PNG, and WebP up to 10MB. Higher-resolution images give the model more detail to analyze.

    Occasionally — stylized portraits, heavily edited product shots, and low-quality JPEGs can trigger false positives. Always read the signal list before concluding.

    No. Uploads are analyzed and discarded immediately. Only the result is kept (if you sign in, in your generation history).

    Yes — POST an image to /v1/image/describe/ with mode=ai-detect. See /api/ for docs.

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