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--- |
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license: mit |
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language: |
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- en |
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- 'no' |
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tags: |
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- whisper |
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- core-ml |
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- apple |
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- Apple-Silicon |
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--- |
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# Whisper.cpp Core ML Models for Apple Silicon |
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This repository provides **prebuilt Core ML models for Whisper.cpp**, optimized for **Apple Silicon (M1, M2, M3, M4, M5)** devices. |
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These models enable **hardware-accelerated speech-to-text** using Apple’s Neural Engine via Core ML. |
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The repository is designed for **easy plug-and-play usage** with Whisper.cpp using a **prebuilt CLI binary**. |
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--- |
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## 📦 Repository Contents |
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Each model directory contains **everything required** to run Whisper.cpp with Core ML acceleration: |
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- **`ggml-*.bin`** – Whisper model weights used by `whisper.cpp` |
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- **`*-encoder.mlmodelc/`** – Compiled Core ML encoder bundle |
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⚠️ **Important:** The `.mlmodelc` directories must remain intact. Do **not** modify, rename, or move their contents. |
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--- |
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## 📁 Folder Structure |
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``` |
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. |
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├── tiny/ |
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├── tiny.en/ |
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├── base/ |
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├── base.en/ |
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├── small/ |
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├── small.en/ |
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├── medium/ |
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├── medium.en/ |
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├── large-v1/ |
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├── large-v2/ |
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└── large-v3/ |
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``` |
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Each folder corresponds to a Whisper model variant and contains the matching `.bin` and `.mlmodelc` files. |
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--- |
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## 🚀 Model Variants Overview |
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The table below summarizes the trade-offs between **speed**, **accuracy**, and **memory usage**. |
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| Folder | Model Size | Speed | Accuracy | Notes | |
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|--------------|-----------|--------------|------------------|-------| |
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| `tiny` | Very Small | ⚡ Fastest | ⭐ Lowest | Best for real-time, low-resource use | |
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| `tiny.en` | Very Small | ⚡ Fastest | ⭐ Lowest | English-only | |
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| `base` | Small | ⚡ Fast | ⭐⭐ Balanced | Good default choice | |
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| `base.en` | Small | ⚡ Fast | ⭐⭐ Balanced | English-only | |
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| `small` | Medium | ⚡ Medium | ⭐⭐⭐ Better | Improved transcription quality | |
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| `small.en` | Medium | ⚡ Medium | ⭐⭐⭐ Better | English-only | |
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| `medium` | Large | 🐢 Slower | ⭐⭐⭐⭐ High | High accuracy, higher memory usage | |
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| `medium.en` | Large | 🐢 Slower | ⭐⭐⭐⭐ High | English-only | |
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| `large-v1` | Very Large | 🐢 Slow | ⭐⭐⭐⭐⭐ Best | Maximum accuracy | |
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| `large-v2` | Very Large | 🐢 Slow | ⭐⭐⭐⭐⭐ Best | Improved multilingual performance | |
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| `large-v3` | Very Large | 🐢 Slow | ⭐⭐⭐⭐⭐ Best | Latest and most accurate | |
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--- |
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## 🛠 Usage Instructions |
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### 1. Download the Prebuilt `whisper-cli` Binary |
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Download the Core ML–enabled `whisper-cli` binary directly from GitHub Releases: |
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``` |
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https://github.com/aarush67/whisper-cli-for-core-ml/releases/download/v1.0.0/whisper-cli |
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``` |
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Recommended directory structure: |
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``` |
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. |
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├── bin/ |
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│ └── whisper-cli |
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├── medium.en/ |
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│ ├── ggml-medium.en.bin |
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│ └── medium.en-encoder.mlmodelc/ |
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``` |
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--- |
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### 2. Make the Binary Executable |
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```bash |
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chmod +x bin/whisper-cli |
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``` |
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--- |
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### 3. Run Whisper with a Core ML Model |
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Place the `.bin` file and the matching `.mlmodelc` folder in the same directory. |
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#### Example (English-only transcription) |
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```bash |
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./bin/whisper-cli -m ggml-medium.en.bin -f sample.wav |
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``` |
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Whisper.cpp will automatically detect and use the Core ML encoder when available. |
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--- |
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## 🧠 Best Practices & Notes |
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- ✅ **Keep `.bin` and `.mlmodelc` files together** from the same model variant |
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- ❌ Do **not** rename, edit, or partially copy `.mlmodelc` directories |
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- 🧹 `.pt` cache files (if generated) are temporary and **safe to delete** |
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- 💾 Larger models require significantly more RAM and disk space |
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- ⚡ Best performance is achieved on Apple Silicon devices with a Neural Engine |
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--- |
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## 📜 License |
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- **Repository structure & metadata:** MIT License |
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- **Model weights & Core ML artifacts:** Governed by the original |
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**Whisper.cpp / OpenAI Whisper licenses** |
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Please review upstream licenses before commercial or large-scale use. |
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--- |
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## 🙏 Credits |
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- **OpenAI Whisper** – Original speech recognition models |
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- **whisper.cpp** by Georgi Gerganov – High-performance C/C++ implementation |
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- **Apple Core ML** – Hardware acceleration on Apple Silicon |
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--- |
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## ⭐ Support |
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If this repository is useful to you: |
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- ⭐ Star the repository |
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- 🔗 Support the upstream Whisper.cpp project |
