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Installing Nvidia GPU Driver on Ubuntu: A Step-by-Step Guide

Last updated on May 19,2025 |

under

Linux, Operating System, Linux

by Nicholas Khoo

Introduction

Nvidia GPUs power many of today’s advanced computing tasks, from graphic design to AI and machine learning.

To get the most out of your Nvidia GPU, it’s essential to install the correct drivers.

This guide will walk you through installing Nvidia GPU drivers on Ubuntu, step-by-step.

We’ll also cover optional tools, such as the CUDA Toolkit and Nvidia Container Toolkit, which can unlock additional features and capabilities.

Follow along to set up your Nvidia GPU quickly and easily!

Tested on Nvidia RTX 30xx , RTX 40xx , RTX 50xx and H200NVL series

Official References :

Ubuntu – Nvidia GPU Driver :
https://docs.nvidia.com/datacenter/tesla/driver-installation-guide/ubuntu.html

Nvidia CUDA Toolkit :
https://developer.nvidia.com/cuda-downloads

Nvidia Container Toolkit :
https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html

🚀 GPU Software Components Overview

Component	Required?	Purpose	When You Need It
NVIDIA Driver	✅ Yes	Enables the system to detect and communicate with the NVIDIA GPU.	Always required for the GPU to function.
CUDA Toolkit	⚙️ Optional	Provides tools and libraries for GPU-accelerated apps (like AI/ML).	Needed only if your app depends on CUDA or you’re developing.
Container Toolkit	⚙️ Optional	Allows Docker containers to access the GPU hardware.	Needed only if you’re using containers with GPU workloads.

Prerequisites

Ubuntu operating system installed
Administrative (sudo) privileges
Compatible Nvidia GPU hardware
Internet connectivity for package downloads

Installation Procedure

Step 1: System Update

Begin by updating the package list to ensure you have access to the latest software versions:

sudo apt update
sudo apt upgrade -y

Step 2: Linux Headers Installation

Install the necessary Linux headers required for driver compilation:

sudo apt install -y linux-headers-$(uname -r)

Step 3: Download and install Nvidia Repository Keyring according to your Ubuntu version

if [ -f /etc/os-release ]; then
    . /etc/os-release
    case "${VERSION_ID}" in
        20*) repo_ver="ubuntu2004" ;;
        22*) repo_ver="ubuntu2204" ;;
        24*) repo_ver="ubuntu2404" ;;
    esac
    wget https://developer.download.nvidia.com/compute/cuda/repos/${repo_ver}/x86_64/cuda-keyring_1.1-1_all.deb
    sudo dpkg -i cuda-keyring_1.1-1_all.deb
else
    echo "Error: /etc/os-release not found. Cannot determine OS."
fi

Optional Step: Use IP ServerOne’s Nvidia Mirror

sudo tee /etc/apt/sources.list.d/cuda-$(. /etc/os-release; echo ubuntu${VERSION_ID//./})-x86_64.list <<< "deb [signed-by=/usr/share/keyrings/cuda-archive-keyring.gpg] https://developer.download.nvidia.com/compute/cuda/repos/$(. /etc/os-release; echo ubuntu${VERSION_ID//./})/x86_64/ /"

Step 4: Nvidia Driver and CUDA Toolkit Installation

sudo apt update
sudo apt -V install -y libnvidia-compute nvidia-dkms-open

Step 5: System Reboot

Reboot your system to load the GPU Driver:

sudo reboot

Step 6: GPU Driver Verification

To make sure everything is working as it should, run:

sudo nvidia-smi

If you see your GPU info pop up, you’re all set! 🎉

Optional : Installing Nvidia CUDA Toolkit

Running a CUDA application requires the system with at least one CUDA capable GPU and a driver that is compatible with the CUDA Toolkit.

Step 1: Download and install Nvidia Repository Keyring according to your Ubuntu version

Ensure that you have installed Nvidia GPU Driver following the steps above

Step 2 : Install Nvidia CUDA Toolkit

sudo apt update
sudo apt -y install cuda-toolkit

Step 3 : Add CUDA Toolkit into PATH variable

sudo tee -a /etc/bash.bashrc <<< 'export PATH=${PATH}:/usr/local/cuda/bin'
export PATH=${PATH}:/usr/local/cuda/bin

Step 4 : CUDA Toolkit verification

sudo nvcc --version

If you see NVIDIA (R) Cuda compiler driver info pop up, you’re all set! 🎉

Optional : Installing Nvidia Container Toolkit

The NVIDIA Container Toolkit is a collection of libraries and utilities enabling users to build and run GPU-accelerated containers.
Required if you want to use GPU within Docker

Step 1 : Configure the production repository

curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \
  && curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \
    sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
    sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list

Step 2 : Update the packages list from the repository

sudo apt update

Step 3 : Install the NVIDIA Container Toolkit packages

sudo apt install -y nvidia-container-toolkit
sudo nvidia-ctk runtime configure --runtime=docker

Step 4 : Restart Docker

sudo systemctl restart docker

Step 5 : Nvidia Container Toolkit verification

sudo docker run --pull=always --rm --gpus all ubuntu nvidia-smi