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Last updated 9 days ago

This guide provides detailed instructions for installing Ollama on various Linux distributions, NixOS, and using Docker containers.

System Requirements

Before installing Ollama, ensure your system meets these minimum requirements:

  • CPU: 64-bit Intel/AMD (x86_64) or ARM64 processor

  • RAM: 8GB minimum (16GB+ recommended for larger models)

  • Storage: 10GB+ free space (varies by model size)

  • Operating System: Linux (kernel 4.15+), macOS 12.0+, or Windows 10/11

  • GPU (optional but recommended):

    • NVIDIA GPU with CUDA 11.4+ support

    • AMD GPU with ROCm 5.4.3+ support

    • Intel Arc GPU with OneAPI support

Linux Installation (Direct Method)

Using the Install Script (Recommended)

For most Linux distributions, the simplest installation method is using the official install script:

This script automatically detects your Linux distribution and installs the appropriate package.

Manual Installation (Debian/Ubuntu)

For Debian-based distributions (Ubuntu, Debian, Linux Mint, etc.):

Manual Installation (Red Hat/Fedora)

For Red Hat-based distributions (RHEL, Fedora, CentOS, etc.):

Manual Installation (Binary Installation)

If packages are not available for your distribution:

NixOS Installation

Ollama is available in the Nixpkgs collection, making it easy to install on NixOS.

Using Nix Package Manager

NixOS Configuration (Configuration.nix)

For a system-wide installation, add Ollama to your configuration.nix:

After updating your configuration, apply the changes:

Using Home Manager

If you're using Home Manager:

Docker Installation

Running Ollama in Docker provides a consistent environment across different systems.

Basic Docker Setup

Pull and run the official Ollama Docker image:

Docker Compose Setup

Create a docker-compose.yml file:

Launch with Docker Compose:

Docker with GPU Support (NVIDIA)

To enable NVIDIA GPU support:

Post-Installation Setup

After installing Ollama, perform these steps to complete the setup:

  1. Start the Ollama service:

  2. Test the installation by running a model:

  3. Verify API access:

Troubleshooting

Common Issues

  1. Permission Denied Errors:

  2. Network Connectivity Issues:

  3. GPU Not Detected:

Next Steps

Now that you have Ollama installed, proceed to:

for optimal performance

for faster inference

For DevOps engineers, check out to see how Ollama can be integrated into your workflows.

curl -fsSL https://ollama.com/install.sh | sh
# Download the latest .deb package
wget https://github.com/ollama/ollama/releases/latest/download/ollama-linux-amd64.deb

# Install the package
sudo dpkg -i ollama-linux-amd64.deb

# Install any missing dependencies
sudo apt-get install -f
# Download the latest .rpm package
wget https://github.com/ollama/ollama/releases/latest/download/ollama-linux-x86_64.rpm

# Install the package
sudo rpm -i ollama-linux-x86_64.rpm
# Download the latest binary
wget https://github.com/ollama/ollama/releases/latest/download/ollama-linux-amd64

# Make it executable
chmod +x ollama-linux-amd64

# Move to a directory in PATH
sudo mv ollama-linux-amd64 /usr/local/bin/ollama
nix-env -iA nixos.ollama
{ config, pkgs, ... }:

{
  # Enable Ollama service
  services.ollama = {
    enable = true;
    acceleration = "cuda"; # Options: none, cuda, rocm, or oneapi
    package = pkgs.ollama;
  };
  
  # Add ollama package to system packages
  environment.systemPackages = with pkgs; [
    ollama
  ];
}
sudo nixos-rebuild switch
{ config, pkgs, ... }:

{
  home.packages = with pkgs; [
    ollama
  ];
}
# Pull the latest Ollama image
docker pull ollama/ollama:latest

# Run Ollama container
docker run -d \
  --name ollama \
  -p 11434:11434 \
  -v ollama:/root/.ollama \
  ollama/ollama
version: '3'

services:
  ollama:
    image: ollama/ollama:latest
    container_name: ollama
    volumes:
      - ollama_data:/root/.ollama
    ports:
      - "11434:11434"
    restart: unless-stopped

volumes:
  ollama_data:
docker-compose up -d
# Install NVIDIA Container Toolkit
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/libnvidia-container/gpgkey | sudo apt-key add -
curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.list | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit

# Run Ollama with GPU support
docker run -d \
  --name ollama \
  --gpus all \
  -p 11434:11434 \
  -v ollama:/root/.ollama \
  ollama/ollama
ollama serve
ollama pull mistral
ollama run mistral
curl http://localhost:11434/api/generate -d '{
  "model": "mistral",
  "prompt": "Hello, how are you?"
}'
sudo chown -R $USER:$USER ~/.ollama
# Verify Ollama service is running
ps aux | grep ollama

# Check if port 11434 is open
sudo lsof -i:11434
# Verify CUDA installation
nvidia-smi

# Check Ollama logs
journalctl -u ollama
  1. 🧠AI & LLM Integration
  2. Overview
  3. Ollama

Installation Guide

PreviousOllamaNextConfiguration
  • System Requirements
  • Linux Installation (Direct Method)
  • Using the Install Script (Recommended)
  • Manual Installation (Debian/Ubuntu)
  • Manual Installation (Red Hat/Fedora)
  • Manual Installation (Binary Installation)
  • NixOS Installation
  • Using Nix Package Manager
  • NixOS Configuration (Configuration.nix)
  • Using Home Manager
  • Docker Installation
  • Basic Docker Setup
  • Docker Compose Setup
  • Docker with GPU Support (NVIDIA)
  • Post-Installation Setup
  • Troubleshooting
  • Common Issues
  • Next Steps
Configure Ollama
Explore available models
Set up GPU acceleration
DevOps Usage Examples