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aitytech/Whisper-Large-V3-Turbo-MLX-FP16
Whisper-Large-V3-Turbo-MLX-FP16 is a automatic speech recognition model from aitytech. Use it when you need speech turned into text. It is set up for mlx. The card lists the license as mit.
This is the OpenAI Whisper Large V3 Turbo model converted to MLX format with FP16 precision, optimized for Apple Silicon inference.
Downloads · 30 days
11
2% of all-time downloads
All-time downloads
516
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807M
1.6 GB on disk
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.safetensors1.6 GB · 100%
How the weights are stored.
F16807M · 100%
From the Hugging Face model README
This is the OpenAI Whisper Large V3 Turbo model converted to MLX format with FP16 precision, optimized for Apple Silicon inference.
Whisper Large V3 Turbo is a distilled version of Whisper Large V3 that uses only 4 decoder layers instead of 32, making it significantly faster while maintaining high accuracy.
| Property | Value |
|---|---|
| Base Model | openai/whisper-large-v3-turbo |
| Parameters | ~809M |
| Format | MLX SafeTensors (FP16) |
| Model Size | 1,539.20 MB |
| Sample Rate | 16,000 Hz |
| Mel Bins | 128 |
| Audio Layers | 32 |
| Text Layers | 4 |
| Hidden Size | 1280 |
| Attention Heads | 20 |
| Vocabulary Size | 51,866 |
This model is optimized for on-device automatic speech recognition (ASR) on Apple Silicon devices (Mac, iPhone, iPad). It is designed for use with the WhisperKit or MLX frameworks.
The Turbo variant offers the best speed/accuracy trade-off for real-time transcription on device.
config.json - Model configurationmodel.safetensors - Model weights in SafeTensors format (FP16)multilingual.tiktoken - Tokenizerimport mlx_whisper
result = mlx_whisper.transcribe(
"audio.mp3",
path_or_hf_repo="aitytech/Whisper-Large-V3-Turbo-MLX-FP16",
)
print(result["text"])