# Run pyannote speaker diarization

Works out who spoke when, so a transcript can be labelled by person. Ready in about 90 seconds on an RTX 3090, from $0.22/hr. No install, no code.

## What it does

This model listens to a recording with several people in it and marks which stretches belong to which speaker.

It does not know their names. It gives you Speaker 1, Speaker 2, and so on, with timestamps, and you attach the names afterwards.

On its own it is not very useful. Run it alongside Whisper and you get a transcript where every line is attributed, which is what most people actually want from a meeting or interview recording.

## Your setup

We run pyannote speaker diarization on an RTX 3090 with 24GB of memory, at $0.22 per hour, billed by the minute. It takes about 2 minutes per hour of audio.

The model is small, under 100MB, so it barely touches memory. There is no reason to pay for a bigger card. The one thing worth knowing is that we run it on the same machine as the transcription rather than a separate one, because moving the audio twice costs more time than the diarization itself.

## What it costs

40 hours of audio takes about 60 minutes of GPU time, which is about $0.22.

## Two ways to run it

- **Open the app.** Upload a recording and see a timeline coloured by speaker.
- **Run a batch job.** Usually bundled with transcription rather than run alone.

## Model facts

| Field | Value |
|---|---|
| Parameters | 25M |
| License | MIT |
| Memory required | 4GB minimum |
| Base model | Trained from scratch |
| Publisher | pyannote |
| Recommended hardware | RTX 3090, 24GB |
| Category | [Voice and audio](https://gpuvault.io/working-on/voice-and-audio/) |

## Questions people ask

### Do I need to install anything to use pyannote speaker diarization?

No. We start a machine with pyannote speaker diarization already loaded and hand you a link. Everything runs in your browser, there is nothing to download, and nothing is left on your computer afterwards. It works the same on a Mac, a Windows laptop, or a Chromebook. A workspace is usually ready in about 90 seconds.

### How much does it cost to run 40 hours of audio?

About $0.22. pyannote speaker diarization takes about 2 minutes per hour of audio on the RTX 3090 we recommend, so 40 hours of audio is roughly 60 minutes of GPU time at $0.22 per hour. Billing is by the minute, and a batch job shuts the GPU off the moment the last item finishes. The calculator above works this out for your own numbers.

### Can I run pyannote speaker diarization on a cheaper card?

Sometimes, and the calculator will not always make it look worth it. The model is small, under 100MB, so it barely touches memory. There is no reason to pay for a bigger card. The one thing worth knowing is that we run it on the same machine as the transcription rather than a separate one, because moving the audio twice costs more time than the diarization itself. If you want to try a different card anyway, the advanced catalog lets you pick one and shows the estimated time before you commit.

### Can I use pyannote speaker diarization commercially?

Yes. pyannote speaker diarization is released under the MIT license, which permits commercial use with no conditions worth worrying about. You can use the output in paid client work and in products you sell.

### What happens to my files after I stop?

Anything you save into your workspace folder stays in your account and is there when you come back. Everything else is destroyed: the machine is terminated and its disk is wiped. Batch job inputs and outputs are deleted from our storage 24 hours after you download them. We do not read your files or use them to train anything.

### What if it fails partway through?

You are not charged for work that did not complete, and failed sessions are refunded automatically. Batch jobs write each output as it finishes rather than at the end, so a failure at item 380 of 400 leaves you 379 usable files and a message saying what broke. Restarting picks up where it stopped rather than redoing the work.

---

*Source: https://gpuvault.io/model/pyannote-diarization/ — GPUVault, GPU rental by the minute.*