Intel® Neural Compressor

An open-source Python library supporting popular model compression techniques on all mainstream deep learning frameworks (TensorFlow, PyTorch, ONNX Runtime, and MXNet)

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Intel® Neural Compressor aims to provide popular model compression techniques such as quantization, pruning (sparsity), distillation, and neural architecture search on mainstream frameworks such as TensorFlow, PyTorch, ONNX Runtime, and MXNet, as well as Intel extensions such as Intel Extension for TensorFlow and Intel Extension for PyTorch. In particular, the tool provides the key features, typical examples, and open collaborations as below:

The performance and accuracy results of typical models are available here. You may also want to visit the Intel® Neural Compressor online document website for more details.


Install from pypi

pip install neural-compressor

More installation methods can be found at Installation Guide. Please check out our FAQ for more details.

Getting Started

Quantization with Python API

# Install Intel Neural Compressor and TensorFlow
pip install neural-compressor 
pip install tensorflow
# Prepare fp32 model
from neural_compressor.config import PostTrainingQuantConfig
from import DataLoader
from import Datasets

dataset = Datasets('tensorflow')['dummy'](shape=(1, 224, 224, 3))
dataloader = DataLoader(framework='tensorflow', dataset=dataset)

from neural_compressor.quantization import fit
q_model = fit(

More quick samples can be found in Get Started Page.


Architecture Workflow APIs GUI
Notebook Examples Intel oneAPI AI Analytics Toolkit
Python-based APIs
Quantization Advanced Mixed Precision Pruning (Sparsity) Distillation
Orchestration Benchmarking Distributed Compression Model Export
Neural Coder (Zero-code Optimization)
Launcher JupyterLab Extension Visual Studio Code Extension Supported Matrix
Advanced Topics
Adaptor Strategy Distillation for Quantization SmoothQuant

Selected Publications/Events

Additional Content

Research Collaborations

Welcome to raise any interesting research ideas on model compression techniques and feel free to reach us ( Look forward to our collaborations on Intel Neural Compressor!