Avidemux vs Neiro
Avidemux
avidemux.sourceforge.netNeiro
github.comSide by side
| Figure | Avidemux | Neiro |
|---|---|---|
| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | Yes | — |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| Self-hosted | — | Yes |
| Plans published | 2 | 0 |
| Spec score · Audio Restoration Software | 8.0 (#4) | 7.3 (#16) |
| License | The program is available under the GNU GPL license. | The repository license is MIT for the Neiro engine source, while model weights have separate licenses. |
| Purpose | Avidemux is a free video editor designed for simple cutting, filtering and encoding tasks. | Neiro is a local audio worksuite for source separation, restoration, transcription, and audio editing. |
| Support | The homepage welcomes patches, translations and bug reports. | The maker directs users to documentation and public GitHub Discussions or Issues, and asks security reports to be sent privately. |
Plans
In their own words
Avidemux
Avidemux has no write-up on Specifiction yet; its figures are above.
Neiro
Neiro is a local audio worksuite for separating sources, restoring recordings, transcribing audio and editing waveforms. Processing takes place on the user's machine and audio does not leave it. Neiro offers a Tauri desktop app and a browser interface launched with `neiro ui`; desktop installers are listed for Windows, macOS and Linux. Separation covers vocals, instrumentals, harmonic and percussive parts, four- or six-stem mixes and drum kits, with a null-test residual for each result. Restoration tools include declipping, hum removal, denoising, dereverberation, bandwidth extension and reference mastering. Transcription can export MIDI, MusicXML, ASCII tablature and LRC lyrics. Studio provides non-destructive waveform edits, while Learn includes loop regions, count-in, metronome, step mode, WebMIDI and DAW wait mode. VST2 and CLAP injectors can capture audio from a DAW into Neiro. Core DSP works without model downloads, but optional neural backends download weights on first use. The Python package requires Python 3.10–3.12; compressed or video inputs also require ffmpeg on PATH.