# IPEX-LLM Installation: CPU ## Quick Installation Install IPEX-LLM for CPU supports using pip through: - For **Linux users**: ```bash pip install --pre --upgrade ipex-llm[all] --extra-index-url https://download.pytorch.org/whl/cpu ``` - For **Windows users**: ```cmd pip install --pre --upgrade ipex-llm[all] ``` Please refer to [Environment Setup](#environment-setup) for more information. > [!NOTE] > `all` option will trigger installation of all the dependencies for common LLM application development. > [!IMPORTANT] > `ipex-llm` is tested with Python 3.9, 3.10 and 3.11; Python 3.11 is recommended for best practices. ## Recommended Requirements Here list the recommended hardware and OS for smooth IPEX-LLM optimization experiences on CPU: * Hardware * PCs equipped with 12th Gen Intel® Core™ processor or higher, and at least 16GB RAM * Servers equipped with Intel® Xeon® processors, at least 32G RAM. * Operating System * Ubuntu 20.04 or later * CentOS 7 or later * Windows 10/11, with or without WSL ## Environment Setup For optimal performance with LLM models using IPEX-LLM optimizations on Intel CPUs, here are some best practices for setting up environment: First we recommend using [Conda](https://conda-forge.org/download/) to create a python 3.11 enviroment: - For **Linux users**: ```bash conda create -n llm python=3.11 conda activate llm pip install --pre --upgrade ipex-llm[all] --extra-index-url https://download.pytorch.org/whl/cpu ``` - For ```cmd conda create -n llm python=3.11 conda activate llm pip install --pre --upgrade ipex-llm[all] ``` Then for running a LLM model with IPEX-LLM optimizations (taking an `example.py` an example): - For **running on Client**: It is recommended to run directly with full utilization of all CPU cores: ```bash python example.py ``` - For **running on Server**: It is recommended to run with all the physical cores of a single socket: ```bash # e.g. for a server with 48 cores per socket export OMP_NUM_THREADS=48 numactl -C 0-47 -m 0 python example.py ```