DeepFilterNet vs RNNoise: which noise remover is better?

RNNoise: small, fast, live

RNNoise is tiny and quick enough to run inside a live call with negligible delay. That is what it was designed for, and it is still widely used in voice chat for exactly that reason.

The trade is bandwidth and subtlety. It works on a narrower range than a modern full-band model, and on difficult material it removes less and leaves more behind.

DeepFilterNet: full-band, for finished audio

DeepFilterNet is a later, larger model that works across the full audio band. It separates speech from the background rather than suppressing what sits below a level, which is why it holds up on room reverb and steady mechanical noise where simpler approaches smear the voice.

It costs more processing time. For a live call that matters; for a file you are cleaning before publishing, it does not — the file is not in a hurry.

Which to use

Live conversation, a headset, a call: RNNoise or whatever your platform already ships. You will not notice the difference and you will notice latency.

A recording you are going to publish: the full-band model, every time. That is the kind this application runs, and the reason it does.

Neither of them fixes the room

Both work far better on a recording that was not terrible to begin with. Get the microphone closer, turn the fan off, put something soft behind you. Ten minutes of that beats any model.

In short: RNNoise for live audio where latency matters. A full-band model like DeepFilterNet for anything you are publishing.