llama.cpp/docs/install/macos.md

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---
title: MacOS Install with Metal GPU
---
**(1) Make sure you have xcode installed... at least the command line parts**
```
# check the path of your xcode install
xcode-select -p
# xcode installed returns
# /Applications/Xcode-beta.app/Contents/Developer
# if xcode is missing then install it... it takes ages;
xcode-select --install
```
**(2) Install the conda version for MacOS that supports Metal GPU**
```
wget https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-MacOSX-arm64.sh
bash Miniforge3-MacOSX-arm64.sh
```
**(3) Make a conda environment**
```
conda create -n llama python=3.9.16
conda activate llama
```
**(4) Install the LATEST llama-cpp-python.. which, as of just today, happily supports MacOS Metal GPU**
*(you needed xcode installed in order pip to build/compile the C++ code)*
```
pip uninstall llama-cpp-python -y
CMAKE_ARGS="-DLLAMA_METAL=on" FORCE_CMAKE=1 pip install -U llama-cpp-python --no-cache-dir
pip install 'llama-cpp-python[server]'
# you should now have llama-cpp-python v0.1.62 installed
llama-cpp-python         0.1.62     
```
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**(4) Download a v3 ggml model**
- **ggmlv3**
- file name ends with **q4_0.bin** - indicating it is 4bit quantized, with quantisation method 0
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https://huggingface.co/TheBloke/open-llama-7b-open-instruct-GGML
**(6) run the llama-cpp-python API server with MacOS Metal GPU support**
```
# config your ggml model path
# make sure it is ggml v3
# make sure it is q4_0
export MODEL=[path to your llama.cpp ggml models]]/[ggml-model-name]]q4_0.bin
python3 -m llama_cpp.server --model $MODEL --n_gpu_layers 1
```
***Note:** If you omit the `--n_gpu_layers 1` then CPU will be used*