Matchering vs SONDIQ
Matchering
github.comSONDIQ
sondiq.comSide by side
| Figure | Matchering | SONDIQ |
|---|---|---|
| Price from | Free | $7.99/mo |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | Yes | — |
| Web | Yes | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | — |
| API | Yes | — |
| Self-hosted | Yes | — |
| Plans published | 1 | 2 |
| Spec score · AI mastering tools | 8.6 (#6) | 7.0 (#46) |
| What it does | Matchering processes a target recording against a reference recording and returns a master intended to match the reference’s loudness, frequency response, peak amplitude and stereo width. | SONDIQ uses AI to master music, podcasts, and AI voices into release-ready audio. |
Plans
In their own words
Matchering
Matchering is open-source software for matching and mastering audio. Give it a TARGET track and a REFERENCE track, and it produces a mastered TARGET that follows the reference’s RMS, frequency response, peak amplitude, and stereo width. Matchering 2.0 comes as a containerized web application, Python library, and ComfyUI node, and is integrated into the UVR5 Desktop App. The Python library also provides a command-line application and can connect with the Python ecosystem. It requires Python 3.8.0 or later and a machine with 4 GB of RAM. WAV and MP3 are supported input formats, though MP3 loading needs a separate FFmpeg installation. The project says the algorithm uses digital signal processing rather than a neural network, and works well across nearly all genres, especially EDM, with an exception for experimental music with a very specific form. The free plan is listed at free under GPLv3, with no published paid plans. The maker advises against exposing its web application to the public Internet without security and scalability changes.