Core ML conversion of myshell-ai/OpenVoice for on-device inference on iPhone, iPad and Mac. Converted with coremltools; the packages are stateless, so all sequencing and buffering lives in your Swift code.


Task	audio to audio
Upstream	myshell-ai/OpenVoice
Packages	2
Download size	58 MB
Minimum iOS	17.0
Peak RAM	~500 MB

Files

File	Size	Compute units	SHA-256
`OpenVoice_SpeakerEncoder.mlpackage.zip`	1 MB	`cpuAndGPU`	`c3f2a96aaf5ecb5c…`
`OpenVoice_VoiceConverter.mlpackage.zip`	57 MB	`cpuAndGPU`	`ef3ce8a2d1564aef…`
Total	58 MB

compute_units is not a suggestion -- it is the configuration the conversion was verified against. Moving a package to a different compute unit can silently change the numerics (FP16 attention overflow) or crash on the GPU.

Download

bash

hf download mlboydaisuke/coreml-zoo --include "openvoice/*" --local-dir ./openvoice
unzip './openvoice/openvoice/*.zip' -d ./openvoice

Use in Swift

swift

import CoreML

let config = MLModelConfiguration()
config.computeUnits = .cpuAndGPU   // as converted — see the table above

// Unzip the .mlpackage, drop it into your Xcode target and Xcode compiles it
// at build time:
let model = try OpenVoice_SpeakerEncoder(configuration: config)

// ...or compile a downloaded .mlpackage at runtime:
let compiled = try await MLModel.compileModel(at: mlpackageURL)
let model = try MLModel(contentsOf: compiled, configuration: config)

This model is split into 2 Core ML packages that are driven in sequence from Swift. Load them one at a time, copy the outputs out of the MLMultiArray buffers and release each model before loading the next — two large Core ML models resident at once will OOM on an iPhone.

Demo

Sample app — sample_apps/OpenVoiceDemo, a standalone SwiftUI project.
Models Zoo — this model is downloadable and runnable inside the Models Zoo app on the App Store, no build required.

Conversion

Script: convert_openvoice.py
Pitfalls hit during conversion (FP16 overflow, ANE buffer limits, stride handling): docs/coreml_conversion_notes.md
Model index: CoreML-Models

License

The conversion inherits the upstream license: MIT.

Credits

Upstream authors: myshell-ai/OpenVoice, 2023
Core ML conversion: john-rocky (Daisuke Majima)

More models in this format: Core ML Model Zoo — 46 models, each with the recipe that produced it.

Want a different model on-device? Open a request — free, open weights only; the export and its measured numbers get published publicly.

mlboydaisuke/OpenVoice-V2-CoreML

OpenVoice V2 — Core ML