HanoLab Mastering vs Matchering

HanoLab Mastering is a browser-based mastering tool within HanoLab’s broader set of AI audio tools for music generation, voice conversion and stem separation. It can move a mix toward a commercial reference’s loudness and tonal balance, or toward a streaming loudness target. Uploads can be MP3, WAV, FLAC or M4A, and mastered tracks export as lossless 24-bit WAV. Each mastered track uses one subscription credit; the listed REST API rate is $0.02 per track. The browser canvas combines generation, stem splitting, voice conversion and mastering without installation. The free plan includes 30 monthly credits, but its outputs expire after seven days and are for personal and evaluation use. Credits reset monthly, do not roll over, and generation pauses when they run out until renewal or upgrade. Paid plans start at $19.90 a month and grant a commercial license for outputs generated while the plan is active. Free accounts have model-improvement data sharing enabled by default; paid accounts have it disabled by default. Users can change that preference in Account Settings.

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.