Running large language models locally is no longer limited to researchers or cloud-native teams. With Ollama, anyone can install and run powerful AI models directly on their own machine—securely, privately, and without recurring API costs.

This tech concept, walks beginners through system requirements, step-by-step installation on macOS, Linux, and Windows, common mistakes, and how to verify that Ollama works correctly.

For over two decades, I’ve led transformative technology initiatives that deliver scalable outcomes and elevate organizations. I turn complex challenges into strategic opportunities that drive sustained digital growth. If you’re looking to transition from cloud-dependent AI to a local-first approach and experiment with professional rigor, this is the path. 

What Is Ollama and Why Installation Matters

Ollama is a lightweight runtime that allows you to download, manage, and run large language models (LLMs) locally. Once installed, you can pull models like LLaMA, Mistral, Qwen, Phi, and others, then interact with them through the terminal or APIs.

A correct installation ensures:

• Stable model execution
• Optimal CPU or GPU usage
• Smooth local AI development without friction

System Requirements (Explained Simply)

Before installing Ollama, make sure your system meets these basic requirements.

Minimum Requirements (CPU Only)

• Operating System
  • macOS 14+ (Apple Silicon or Intel)
  • Ubuntu 20.04+, Debian-based Linux
  • Windows 10 or 11 (64-bit)
• RAM: 8 GB (16 GB recommended)
• Storage: 10–20 GB free space (models consume disk space)
• CPU: Modern 64-bit processor

Recommended Requirements (For Better Performance)

• RAM: 16–32 GB
• GPU:
  • Apple Silicon (M1/M2/M3) uses Metal automatically
  • NVIDIA GPU with CUDA on Linux or Windows
• SSD storage for faster model loading

Ollama automatically detects available hardware and optimizes execution without manual configuration.

Installing Ollama on macOS

Step 1: Download the Installer

Download the official macOS installer from the Ollama website (Requires macOS 14 Sonoma or later).

Step 2: Run the Installer

• Follow the on-screen setup steps
• Ollama installs as a background service
• No manual environment setup required

Step 3: Open terminal

Verify installation:

ollama --version

Installing Ollama on Linux (Ubuntu / Debian)

Step 1: Install Using the Official Script

Run the following command in your terminal:

curl -fsSL https://ollama.com/install.sh | sh

This script installs Ollama and sets up the system service.

Step 2: Start and Enable the Service

Most systems start Ollama automatically. If not:

sudo systemctl start ollama
sudo systemctl enable ollama

Step 3: Verify Installation

ollama --version

Installing Ollama on Windows

Step 1: Download the Installer

Download the official Windows installer from the Ollama website.

Step 2: Run the Installer

• Follow the on-screen setup steps
• Ollama installs as a background service
• No manual environment setup required

Step 3: Open Command Prompt or PowerShell

Verify installation:

ollama --version

Windows users with NVIDIA GPUs should ensure CUDA drivers are installed for GPU acceleration.

Note: you can also use WSL to install ollama's Ubuntu / Debian versions

Step-by-Step: Running Your First Local Model

Once Ollama is installed, the workflow is identical across all platforms.

Step 1: Pull a Model

ollama pull llama2

This downloads the model to your local system.

Step 2: Run the Model

ollama run llama2 "Explain blockchain in simple terms"

The response is generated locally without sending any data to the cloud.

How to Verify That Ollama Is Working Correctly

Use these checks to confirm a successful setup.

Check Ollama Version

ollama --version

List Installed Models

ollama list

Run a Test Prompt

ollama run mistral "Write a short explanation of machine learning"

Confirm GPU Usage (Optional)

For NVIDIA GPUs:

nvidia-smi

If the model runs and responds, your installation works correctly.

Common Beginner Errors and How to Fix Them

Error 1: command not found: ollama

Cause: Ollama not installed correctly or PATH not set
Fix:

• Restart the terminal
• Reinstall Ollama
• On Windows, ensure installation completed successfully

Error 2: Model Downloads Are Slow or Fail

Cause: Network interruptions or limited disk space
Fix:

• Ensure stable internet connection
• Check available disk space
• Retry the ollama pull command

Error 3: High Memory Usage or Crashes

Cause: Model too large for system RAM
Fix:

• Use smaller models (e.g., 7B instead of 13B)
• Close other applications
• Upgrade RAM if possible

Error 4: GPU Not Being Used

Cause: Missing or outdated GPU drivers
Fix:

• Update NVIDIA drivers and CUDA
• Restart the system
• Verify GPU availability using nvidia-smi

Best Practices for Beginners

• Start with smaller models to learn workflows
• Monitor RAM and disk usage
• Keep Ollama updated for performance improvements
• Store models on fast SSD storage
• Use local AI for sensitive or proprietary data

My Tech Advice: Installing Ollama is the first step toward local-first AI development. With a simple setup process across macOS, Linux, and Windows, Ollama removes cloud dependencies and gives developers full control over data, costs, and performance.

Once installed, you can build AI-powered applications, experiment with open models, and deploy private AI workflows—all from your own machine. Local AI is no longer the future. With Ollama, it’s already here.

Ready to build your own AI tech ? Try the above tech concept, or contact me for a tech advice!

#AskDushyant

Note: The names and information mentioned are based on my personal experience; however, they do not represent any formal statement. The example and pseudo code is for illustration only. You must modify and experiment with the concept to meet your specific needs.

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