CoreML Speech Models
Collection
Speech AI models for Apple Neural Engine via CoreML. iOS/macOS ready. ASR, TTS, VAD, diarization. • 35 items • Updated • 4
Compiled CoreML bundle for OpenAI Whisper large-v3-turbo, staged for Apple-platform ASR in speech-swift.
Part of the soniqo.audio speech toolkit. This is the Apple CoreML bundle used by the native WhisperASR runtime in
speech-swift. Browse Apple bundles in the CoreML Speech Models collection.
| Base model | openai/whisper-large-v3-turbo |
| Bundle source | argmaxinc CoreML bundle |
| Format | Compiled CoreML .mlmodelc |
| Runtime | speech-swift WhisperASR / CoreML |
| Total artifact size | 1562.56 MiB |
| Conversion | Precompiled upstream CoreML bundle, staged for soniqo runtimes |
The bundle splits Whisper into CoreML programs for mel extraction, audio encoding, context prefill, and token decoding. speech-swift loads these programs through its native WhisperASR runtime for Apple Silicon and iOS/macOS deployment.
| File | Size | Description |
|---|---|---|
AudioEncoder.mlmodelc/analytics/coremldata.bin |
0.0 MB | Audio encoder CoreML program |
AudioEncoder.mlmodelc/coremldata.bin |
0.0 MB | Audio encoder CoreML program |
AudioEncoder.mlmodelc/metadata.json |
0.0 MB | Audio encoder CoreML program |
AudioEncoder.mlmodelc/model.mil |
6.84 MB | Audio encoder CoreML program |
AudioEncoder.mlmodelc/model.mlmodel |
0.42 MB | Audio encoder CoreML program |
AudioEncoder.mlmodelc/weights/weight.bin |
1214.96 MB | Audio encoder CoreML program |
MelSpectrogram.mlmodelc/analytics/coremldata.bin |
0.0 MB | Mel spectrogram CoreML program |
MelSpectrogram.mlmodelc/coremldata.bin |
0.0 MB | Mel spectrogram CoreML program |
MelSpectrogram.mlmodelc/metadata.json |
0.0 MB | Mel spectrogram CoreML program |
MelSpectrogram.mlmodelc/model.mil |
0.01 MB | Mel spectrogram CoreML program |
MelSpectrogram.mlmodelc/weights/weight.bin |
0.36 MB | Mel spectrogram CoreML program |
TextDecoder.mlmodelc/analytics/coremldata.bin |
0.0 MB | Token decoder CoreML program |
TextDecoder.mlmodelc/coremldata.bin |
0.0 MB | Token decoder CoreML program |
TextDecoder.mlmodelc/metadata.json |
0.0 MB | Token decoder CoreML program |
TextDecoder.mlmodelc/model.mil |
0.13 MB | Token decoder CoreML program |
TextDecoder.mlmodelc/model.mlmodel |
0.11 MB | Token decoder CoreML program |
TextDecoder.mlmodelc/weights/weight.bin |
328.0 MB | Token decoder CoreML program |
TextDecoderContextPrefill.mlmodelc/analytics/coremldata.bin |
0.0 MB | Token decoder CoreML program |
TextDecoderContextPrefill.mlmodelc/coremldata.bin |
0.0 MB | Token decoder CoreML program |
TextDecoderContextPrefill.mlmodelc/metadata.json |
0.0 MB | Token decoder CoreML program |
TextDecoderContextPrefill.mlmodelc/model.mil |
0.0 MB | Token decoder CoreML program |
TextDecoderContextPrefill.mlmodelc/weights/weight.bin |
11.72 MB | Token decoder CoreML program |
config.json |
0.0 MB | Whisper / generation configuration |
generation_config.json |
0.0 MB | Whisper / generation configuration |
M5 Pro, speech-swift native WhisperASR benchmark, full local FLEURS test split:
| Dataset | WER | CER | Mean RTF | Overall throughput |
|---|---|---|---|---|
fleurs-en_us |
5.55% | 2.72% | 0.065 | 16.7x |
fleurs-fr_fr |
6.28% | 2.70% | 0.075 | 14.0x |
fleurs-ar_eg |
16.60% | 5.63% | 0.082 | 12.8x |
Used by speech-swift through the native WhisperASR runtime:
speech transcribe /path/to/audio.wav \
--engine whisper \
--model aufklarer/Whisper-Large-v3-Turbo-CoreML \
--language en
Base model
openai/whisper-large-v3