Audio

BPM detector

Upload an audio file and automatically detect its tempo in beats per minute using the Web Audio API.

Drop your audio file here, or

MP3 · WAV · OGG · AAC · FLAC · M4A · Max 100 MB

Upload an audio file and click Detect BPM to analyse its tempo. Best results with rhythmic music (electronic, pop, rock, hip-hop) that has a clear, consistent beat.

100% private. All processing happens locally in your browser — no files or data are ever sent to a server.

How to use BPM detector

01 Drag and drop your audio file onto the upload area, or click to browse
02 Choose your settings (format, quality, timestamps, etc.)
03 Click the action button — the engine loads on first use, then processes your file
04 Click Download to save the result to your device

Frequently asked questions

Common questions about BPM detector.

Is BPM detector free to use?

Yes, BPM detector is completely free. No account, subscription, or payment is ever required — just open the page and start using it.

Does BPM detector upload my data to a server?

No. BPM detector runs entirely in your web browser using client-side JavaScript. Your files, text, and data never leave your device, making it 100% private.

Can I use BPM detector on my phone or tablet?

Yes. BPM detector is fully responsive and works on all modern smartphones, tablets, and desktop browsers without installing any app.

Are my audio files kept private?

Yes. BPM detector processes all audio entirely in your browser using ffmpeg.wasm (a WebAssembly build of FFmpeg) or the Web Audio API. Your files are never uploaded to any server.

Why does it take a moment to start the first time?

The audio engine uses ffmpeg.wasm, a ~30MB WebAssembly library that loads on demand — only when you click the action button. Once loaded, subsequent operations are instant. It is not loaded on page arrival to protect page speed.

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About BPM detector

The BPM Detector analyses the rhythmic content of an audio file and estimates its tempo in beats per minute (BPM). It uses the Web Audio API to decode the audio, extracts a low-frequency energy envelope to highlight kick and bass transients, then applies autocorrelation to find the dominant periodic rhythm. Results are most accurate for music with a clear, consistent beat — electronic, pop, rock, and hip-hop. Jazz and classical music with variable tempos may show less consistent results. No file is uploaded; all analysis happens locally in your browser.