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Whisper-Base-MLX-FP16
aitytech/Whisper-Base-MLX-FP16
Whisper-Base-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 apache-2.0.
This is the OpenAI Whisper Base model converted to MLX format with FP16 precision, optimized for Apple Silicon inference.
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71.8M
144 MB on disk
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Repo makeup
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.safetensors144 MB · 99%
At a glance
- Task
- Automatic Speech Recognition
- Library
- mlx
- License
- apache-2.0
- Model type
- whisper
- Access
- Public
- Created
- Mar 2, 2026
- Updated
- Mar 2, 2026
- SHA
- 1e120d8d
Base models
Model card
From the Hugging Face model README
Whisper Base - MLX FP16
This is the OpenAI Whisper Base model converted to MLX format with FP16 precision, optimized for Apple Silicon inference.
Model Details
| Property | Value |
|---|---|
| Base Model | openai/whisper-base |
| Parameters | ~74M |
| Format | MLX SafeTensors (FP16) |
| Model Size | 137.02 MB |
| Sample Rate | 16,000 Hz |
| Audio Layers | 6 |
| Text Layers | 6 |
| Hidden Size | 512 |
| Attention Heads | 8 |
| Vocabulary Size | 51,865 |
Intended Use
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.
Files
config.json- Model configurationmodel.safetensors- Model weights in SafeTensors format (FP16)multilingual.tiktoken- Tokenizer
Usage
import mlx_whisper
result = mlx_whisper.transcribe(
"audio.mp3",
path_or_hf_repo="aitytech/Whisper-Base-MLX-FP16",
)
print(result["text"])
Original Model
- Paper: Robust Speech Recognition via Large-Scale Weak Supervision
- Authors: OpenAI
- License: Apache-2.0
- Task
- Automatic Speech Recognition
- Library
- mlx
- Type
- whisper
- License
- apache-2.0
- Languages
- en, zh, de, es, ru, ko
- Created
- Mar 2, 2026
- Updated
- Mar 2, 2026