Dated benchmark · August 9, 2026

AI Music Detector Benchmark: 60-Track Blind Test

We tested the detector used by aimusicdetect.com on 60 independent, anonymously named clips: 20 human performances, 20 Suno generations, and 20 Udio generations. It classified all 60 as expected in this specific test set. That is a batch result, not a claim of universal 100% accuracy.

60 / 60

Expected classifications on independent tracks

0 / 20

Human tracks falsely classified as AI

0 / 15

Verdict flips after 128 kbps mono compression

Results by source

Known sourceTracksCorrectObserved result
Human performance202020 Human, 0 AI
Suno202020 AI, 0 Human
Udio202020 AI, 0 Human

Overall agreement was 60/60. The 95% Wilson lower confidence bound is 94.0%, which is one reason a perfect observed batch must not be read as proof that future accuracy is 100%. Median provider latency was 7.3 seconds and P95 latency was 16.5 seconds in the complete primary run.

How the blind test worked

  1. We selected 20 independently sourced tracks for each of the three known labels.
  2. Every track was clipped to 30 seconds, normalized to MP3 at 192 kbps stereo and stripped of metadata.
  3. Files were renamed to anonymous IDs such as B001.mp3 before being submitted to ACRCloud model h2zt2l57.
  4. Ground-truth labels stayed in a local manifest and were compared only after the provider returned its verdict.
  5. Five tracks per class were also encoded at 128 kbps mono. All 15 retained the same verdict as their parent clip.

Sample provenance

Download the underlying results

The public files contain anonymous sample IDs, SHA-256 hashes, known labels, returned verdicts, probabilities, model version, latency, and run identity. They do not contain audio, credentials, private paths, or source download URLs.

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Focused analysis

See the paired MP3 compression robustness test for every original and 128 kbps mono probability comparison. The 20-track Suno analysispublishes the complete Suno subset, probability range, per-track latency, and practical interpretation. A separate Udio page will only be published when it adds material analysis beyond this benchmark.

Want to judge a track before relying on a score? Follow the five checks in how to tell if a song is AI generated.

Important limitations

Use the result as evidence, not proof

Never use one detector score alone to accuse a creator, reject a submission, or make a legal or financial decision. Check provenance, project files, disclosures, and listening evidence as well.