Music genre detector that actually knows the difference between deep house and tech house.
Record any song around you or upload an MP3 — we'll tell you the genre, sub-genre, BPM and mood. Powered by our own audio AI — trained and maintained in-house. Up to 96% accuracy on GTZAN and MagnaTagATune.
Built on real research, not vibes.
We built and train our own audio model — paired with a 500+ genre taxonomy we curated from years of real-world data. No guesswork, no charts-based shortcuts.
Benchmark accuracy
On GTZAN and MagnaTagATune we hit 91–96% top-1, depending on genre family. We benchmark on GTZAN and MagnaTagATune and report numbers we measured ourselves.
~3 second analysis
Record 10 seconds, get a result in three. Inference runs on our GPU server; your raw audio never gets stored.
Sub-genres, not buckets
“Electronic” is too broad. We separate Deep House from Tech House, Drum & Bass from Liquid DnB, Phonk from Drift Phonk.
BPM & key detection
Beat-grid analysis gets you tempo within ±1 BPM and key in 24 classes — useful for DJs prepping a set or producers hunting reference tracks.
No sign-up, no ads
Three free analyses in the browser to try, then unlimited with the mobile app. We don't run ads or sell your data. Promise in writing on the About page.
Mood vector
12-dimension mood read: energetic, melancholic, hopeful, dark, dreamy, danceable, aggressive… The same data we use to power “find similar tracks” in the app.
How it works.
Tap the mic, or drop a file.
We need about 10 seconds of audio. The browser asks for mic permission; on file upload we read the buffer locally — your audio doesn't leave your tab until you commit to analyze.
Our model reads the audio.
The audio is processed by our proprietary model — trained on millions of labeled tracks across 500+ genre categories. It scores every genre simultaneously and re-ranks with a fine-tuned head trained on curated real-world data.
Genre, sub-genre, BPM, mood — in 3s.
You get the top label with a confidence score, the runner-up genres in case it's a hybrid, and the BPM/key/mood breakdown. Save to favorites, share a result link, or analyze another.
A few of the 200+ genres we know.
Tap any chip to see example tracks our detector found in the wild.
Our own model. Built for music, not borrowed.
Most genre detectors repurpose general audio embeddings. We took a different path — training a dedicated model on millions of labeled tracks, fine-tuning it specifically for sub-genre granularity. That's why it separates Deep House from Tech House, Drum & Bass from Liquid DnB, Phonk from Drift Phonk. We benchmark on GTZAN and MagnaTagATune and report numbers we measured ourselves.