AIMET Installation

Quick Install

The AIMET PyTorch GPU PyPI packages are available for environments that meet the following requirements:

  • 64-bit Intel x86-compatible processor

  • Linux Ubuntu 22.04 LTS [Python 3.10] or Ubuntu 20.04 LTS [Python 3.8]

  • Cuda 12.0

  • Torch 2.2.2

Pip install:

apt-get install liblapacke
python3 -m pip install aimet-torch

Release Packages

For other aimet variants, install the latest version from the .whl files hosted at


# Pytorch 1.13 with CUDA 11.x
python3 -m pip install
# Pytorch 1.13 CPU only
python3 -m pip install


# Tensorflow 2.10 GPU with CUDA 11.x
python3 -m pip install
# Tensorflow 2.10 CPU only
python3 -m pip install


# ONNX 1.14 GPU
python3 -m pip install
# ONNX 1.14 CPU
python3 -m pip install

For previous AIMET releases, browse packages at Each release includes multiple python packages of the following format:

# VARIANT in {torch_gpu, torch_cpu, tf_gpu, tf_cpu, onnx_gpu, onnx_cpu}
# PACKAGE_PREFIX in {aimet_torch, aimet_tensorflow, aimet_onnx}

System Requirements

The AIMET package requires the following host platform setup:

  • 64-bit Intel x86-compatible processor

  • Linux Ubuntu: 22.04 LTS

  • bash command shell

  • For GPU variants:

To use the GPU accelerated training modules an Nvidia CUDA enabled GPU with a minimum Nvidia driver version of 455+ is required. Using the latest driver is always recommended, especially if using a newer GPU. Both CUDA and cuDNN (the more advanced CUDA interface) enabled GPUs are supported.

Advanced Installation Instructions

There are two ways to setup and install AIMET:
  • On your host machine

  • Using our pre-built development Docker images

Please click on the appropriate link for installation instructions: