Library for compressing deep learning models
NVIDIA Model Optimizer is a library that compresses deep learning models using techniques such as quantization, distillation, and pruning. This tool prepares models for use in inference engines like TensorRT-LLM to increase inference speed.
Updates
- September 27, 2026: Stars 4,563 → 4,910, latest release 0.47.0 (September 23, 2026).
What you get
- fast execution with quantization and pruning
- reducing model size
- export compatible with AI ecosystems
Installation
pip install -U nvidia-modelopt[all]If you don't write code
I want to compress and optimize deep learning models using the NVIDIA Model Optimizer library. Could you explain how to install this tool and what steps I need to follow to accelerate models?
Repository: https://github.com/NVIDIA/Model-Optimizer. Follow the official instructions in the README of this repository for setup and execution.
Before starting, check which OS we are on and if the necessary tools (e.g., Python, Node.js, Git, Docker) are installed. Install any missing ones step-by-step according to this system.
Create a new, empty folder to work in. Do not touch any files outside this folder and do not delete anything. Tell me what you are going to do in one sentence before running each command.
Tell me what I should see on the screen at the end of each step. If an error occurs, I will paste the error message to you exactly as it is, and we will fix it together.
Related dictionary terms
Links
TreScout did not build this tool · we found it in GitHub trends and wrote it up. This page describes the repository as of 2026-09-25: The star count and our text belong to that day, the repository may have changed since. Check the repository link for the current state. The introductory text was prepared with AI from the repository's own documentation, and this page was machine-translated from the Turkish original · the Turkish version prevails.