| --- |
| license: mit |
| language: |
| - en |
| - af |
| - am |
| - ar |
| - as |
| - az |
| - ba |
| - be |
| - bg |
| - bn |
| - bo |
| - br |
| - bs |
| - ca |
| - cs |
| - cy |
| - da |
| - de |
| - el |
| - eu |
| - fa |
| - fi |
| - fo |
| - fr |
| - gl |
| - gu |
| - ha |
| - he |
| - hi |
| - hr |
| - ht |
| - hu |
| - hy |
| - id |
| - is |
| - it |
| - ja |
| - jv |
| - ka |
| - kk |
| - km |
| - kn |
| - ko |
| - la |
| - lb |
| - ln |
| - lo |
| - lt |
| - lv |
| - mg |
| - mk |
| - ml |
| - mn |
| - mr |
| - ms |
| - mt |
| - my |
| - ne |
| - nl |
| - nn |
| - 'no' |
| - oc |
| - pa |
| - pl |
| - pt |
| - ro |
| - ru |
| - sa |
| - sd |
| - si |
| - sk |
| - sl |
| - sn |
| - so |
| - sq |
| - sr |
| - su |
| - sv |
| - sw |
| - ta |
| - te |
| - tg |
| - th |
| - tk |
| - tl |
| - tr |
| - tt |
| - uk |
| - ur |
| - uz |
| - vi |
| - yi |
| - yo |
| - zh |
| tags: |
| - whisper |
| - core-ml |
| - apple |
| - Apple-Silicon |
| --- |
| # Whisper.cpp Core ML Models for Apple Silicon |
|
|
| This repository provides **prebuilt Core ML models for Whisper.cpp**, optimized for **Apple Silicon (M1, M2, M3, M4, M5)** devices. |
| These models enable **hardware-accelerated speech-to-text** using Apple’s Neural Engine via Core ML. |
|
|
| The repository is designed for **easy plug-and-play usage** with Whisper.cpp using a **prebuilt CLI binary**. |
|
|
| --- |
|
|
| ## 📦 Repository Contents |
|
|
| Each model directory contains **everything required** to run Whisper.cpp with Core ML acceleration: |
|
|
| - **`ggml-*.bin`** – Whisper model weights used by `whisper.cpp` |
| - **`*-encoder.mlmodelc/`** – Compiled Core ML encoder bundle |
|
|
| ⚠️ **Important:** The `.mlmodelc` directories must remain intact. Do **not** modify, rename, or move their contents. |
|
|
| --- |
|
|
| ## 📁 Folder Structure |
|
|
| ``` |
| . |
| ├── tiny/ |
| ├── tiny.en/ |
| ├── base/ |
| ├── base.en/ |
| ├── small/ |
| ├── small.en/ |
| ├── medium/ |
| ├── medium.en/ |
| ├── large-v1/ |
| ├── large-v2/ |
| └── large-v3/ |
| ``` |
|
|
| Each folder corresponds to a Whisper model variant and contains the matching `.bin` and `.mlmodelc` files. |
|
|
| --- |
|
|
| ## 🚀 Model Variants Overview |
|
|
| The table below summarizes the trade-offs between **speed**, **accuracy**, and **memory usage**. |
|
|
| | Folder | Model Size | Speed | Accuracy | Notes | |
| |--------------|-----------|--------------|------------------|-------| |
| | `tiny` | Very Small | ⚡ Fastest | ⭐ Lowest | Best for real-time, low-resource use | |
| | `tiny.en` | Very Small | ⚡ Fastest | ⭐ Lowest | English-only | |
| | `base` | Small | ⚡ Fast | ⭐⭐ Balanced | Good default choice | |
| | `base.en` | Small | ⚡ Fast | ⭐⭐ Balanced | English-only | |
| | `small` | Medium | ⚡ Medium | ⭐⭐⭐ Better | Improved transcription quality | |
| | `small.en` | Medium | ⚡ Medium | ⭐⭐⭐ Better | English-only | |
| | `medium` | Large | 🐢 Slower | ⭐⭐⭐⭐ High | High accuracy, higher memory usage | |
| | `medium.en` | Large | 🐢 Slower | ⭐⭐⭐⭐ High | English-only | |
| | `large-v1` | Very Large | 🐢 Slow | ⭐⭐⭐⭐⭐ Best | Maximum accuracy | |
| | `large-v2` | Very Large | 🐢 Slow | ⭐⭐⭐⭐⭐ Best | Improved multilingual performance | |
| | `large-v3` | Very Large | 🐢 Slow | ⭐⭐⭐⭐⭐ Best | Latest and most accurate | |
|
|
| --- |
|
|
| ## 🛠 Usage Instructions |
|
|
| ### 1. Download the Prebuilt `whisper-cli` Binary |
|
|
| Download the Core ML–enabled `whisper-cli` binary directly from GitHub Releases: |
|
|
| ``` |
| https://github.com/aarush67/whisper-cli-for-core-ml/releases/download/v1.0.0/whisper-cli |
| ``` |
|
|
| Recommended directory structure: |
|
|
| ``` |
| . |
| ├── bin/ |
| │ └── whisper-cli |
| ├── medium.en/ |
| │ ├── ggml-medium.en.bin |
| │ └── medium.en-encoder.mlmodelc/ |
| ``` |
|
|
| --- |
|
|
| ### 2. Make the Binary Executable |
|
|
| ```bash |
| chmod +x bin/whisper-cli |
| ``` |
|
|
| --- |
|
|
| ### 3. Run Whisper with a Core ML Model |
|
|
| Place the `.bin` file and the matching `.mlmodelc` folder in the same directory. |
|
|
| #### Example (English-only transcription) |
|
|
| ```bash |
| ./bin/whisper-cli -m ggml-medium.en.bin -f sample.wav |
| ``` |
|
|
| Whisper.cpp will automatically detect and use the Core ML encoder when available. |
|
|
| --- |
|
|
| ## 🧠 Best Practices & Notes |
|
|
| - ✅ **Keep `.bin` and `.mlmodelc` files together** from the same model variant |
| - ❌ Do **not** rename, edit, or partially copy `.mlmodelc` directories |
| - 🧹 `.pt` cache files (if generated) are temporary and **safe to delete** |
| - 💾 Larger models require significantly more RAM and disk space |
| - ⚡ Best performance is achieved on Apple Silicon devices with a Neural Engine |
|
|
| --- |
|
|
| ## 📜 License |
|
|
| - **Repository structure & metadata:** MIT License |
| - **Model weights & Core ML artifacts:** Governed by the original |
| **Whisper.cpp / OpenAI Whisper licenses** |
|
|
| Please review upstream licenses before commercial or large-scale use. |
|
|
| --- |
|
|
| ## 🙏 Credits |
|
|
| - **OpenAI Whisper** – Original speech recognition models |
| - **whisper.cpp** by Georgi Gerganov – High-performance C/C++ implementation |
| - **Apple Core ML** – Hardware acceleration on Apple Silicon |
|
|
| --- |
|
|
| ## ⭐ Support |
|
|
| If this repository is useful to you: |
| - ⭐ Star the repository |
| - 🔗 Support the upstream Whisper.cpp project |
