README.md

---
license: mit
pipeline_tag: audio-to-audio
tags:
  - source-separation
  - vocal-separation
  - mdx23c
  - core-ai
  - apple-silicon
---

# MDX23C InstVoc HQ — Core AI (float16)

Vocal / instrumental separation for Apple silicon: **MDX23C-8KFFT-InstVoc_HQ**
converted to a Core AI asset (`stems-mdx23c-instvoc-float16.aimodel`, 214 MB) for
on-device use from Swift.

## Credit

- **Architecture:** TFC-TDF-UNet v3 (MDX23C) — Kim & Lee.
- **Implementation:** [ZFTurbo/Music-Source-Separation-Training](https://github.com/ZFTurbo/Music-Source-Separation-Training) (MIT).
- **Weights:** `MDX23C-8KFFT-InstVoc_HQ` from [Ultimate Vocal Remover](https://github.com/Anjok07/ultimatevocalremovergui)'s public model repository (MIT).

This repository only converts those weights; all credit for the model belongs to them.

## What the asset computes

The network between the spectrogram and the stem spectrograms — the STFT, chunking and
inverse STFT run in the host:

- input `spec` `[1, 4, 4096, 256]` float32 — left re, left im, right re, right im; bins 0–4095
  of an STFT with n_fft 8192, hop 1024, periodic Hann, centred; one chunk is 261,120 samples
  at 44.1 kHz.
- output `stems` `[1, 8, 4096, 256]` float32 — vocals (4 channels), then instrumental.

Weights and arithmetic are float16 behind float32 input and output.

## Measured (macOS 27, Apple silicon)

| | this asset | float32 export | 8-bit Core ML package |
|---|---|---|---|
| one chunk vs PyTorch float32 | 62.6 dB | 123.9 dB | 35.3 dB |
| time per chunk (GPU) | 0.27 s | 0.31 s | 0.74 s |
| a 30 s mix, end to end | 3.0 s | 3.5 s | 6.9 s |

On three 30-second mixes with a known vocal, all three scored the same vocal and
instrumental SDR to within 0.01 dB. Repeated runs are bit-for-bit identical. The export
asserts the converted network equals upstream's `model(chunk)` exactly before saving.

## Use

With [`stems`](https://github.com/arraypress), which fetches this on first use:

```sh
stems song.mp3        # song-vocal.wav + song-instrumental.wav
```

From Swift, with [swift-vocal-isolation](https://github.com/arraypress/swift-vocal-isolation):

```swift
let separator = try await MDXSeparator(contentsOf: assetURL)
let stems = try await separator.separate(contentsOf: songURL)
```

Converted with `Tools/export_mdx.py --precision float16` in swift-vocal-isolation.