Running Deepseek R1 on my Laptop CPU (No GPU).

 Note: Everything Written Here is from LLMs (OpenAI and Deepseek)

Introduction to DeepSeek

DeepSeek is a powerful AI tool designed for natural language processing and deep learning tasks, often relying on GPUs to accelerate computation. However, not everyone has access to high-performance GPUs, and DeepSeek's adaptability allows it to be deployed on CPU-only systems. In this blog post, I'll demonstrate how to run DeepSeek on a self-hosted server, specifically an 11th Gen Intel i5 laptop CPU. We'll leverage Ollama for model optimization and Docker for containerized deployment, ensuring an efficient and streamlined setup. Whether you're exploring AI for personal projects or lightweight applications, this guide will help you make the most of your hardware resources.


Installing Docker on Linux, macOS, and Windows

Docker is a powerful tool for containerization, making it easy to run and deploy applications in isolated environments. Here's how to install Docker on the three major operating systems.


1. Installing Docker on Linux

For Ubuntu, Debian, and similar distributions:

Step 1: Update your system

sudo apt update
sudo apt upgrade -y

Step 2: Install required dependencies

sudo apt install -y ca-certificates curl gnupg

Step 3: Add Docker’s official GPG key and repository

sudo install -m 0755 -d /etc/apt/keyrings
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /etc/apt/keyrings/docker.gpg


echo "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null

Step 4: Install Docker

sudo apt update
sudo apt install -y docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin

Step 5: Start Docker and enable it on boot

sudo systemctl start docker
sudo systemctl enable docker

Step 6: Verify installation

docker --version

2. Installing Docker on macOS

Step 1: Download Docker Desktop

    Visit the Docker Desktop for macOS page.
    Download the appropriate installer for Intel or Apple Silicon (M1/M2) chips.

Step 2: Install Docker

    Open the downloaded .dmg file.
    Drag the Docker icon into the Applications folder.

Step 3: Start Docker

    Launch Docker from the Applications folder.
    Follow the on-screen instructions to complete the setup.

Step 4: Verify installation

Open a terminal and run:
docker --version

3. Installing Docker on Windows

Step 1: Download Docker Desktop

    Visit the Docker Desktop for Windows page.
    Download the installer.

Step 2: Install Docker

    Run the downloaded .exe file.
    Follow the installation wizard.
    During the installation, ensure the option Enable WSL 2 features is selected (required for Windows 10/11).

Step 3: Start Docker

    Launch Docker Desktop from the Start Menu.
    Sign in with your Docker Hub account or create one.

Step 4: Verify installation

Open PowerShell or Command Prompt and run:
docker --version

Post-Installation Tips

    Add Your User to the Docker Group (Linux):


sudo usermod -aG docker $USER

 
Log out and back in to apply changes.
Test Docker Installation: Run a test container:


docker run hello-world

 
Install Docker Compose (if not included):
docker compose version

 And After that Install a frontend for the LLM for  Chatbox.ai or open-webui


Open-WEBUI
 
 

Installing Ollama


Ollama is a tool for running large language models (LLMs) locally. It simplifies model management and allows running advanced AI models on your hardware.
1. Installing Ollama on macOS

Ollama currently supports macOS natively. Here's how to install it:

    Install Ollama via Homebrew:


brew install ollama/tap/ollama

Start the Ollama service:

ollama serve

Verify Installation: Run the following command to confirm: 
 
ollama --version

2. Installing Ollama on Windows or Linux


Ollama doesn't yet natively support Windows or Linux, but you can run it on these platforms via macOS virtualization or containerization solutions like Docker. Stay updated by visiting the Ollama official site.
Downloading and Running Different DeepSeek LLMs

Once Ollama is installed, you can easily install and run models like DeepSeek.
1. Install a Model

To install a model, use the ollama pull command. For example, to install the DeepSeek models:

ollama run deepseek-rxxxx

2. List Available Models


To see all installed models:

ollama list

3. Run a Model

To use a specific model:

ollama run deepseek-rxxxx

4. Managing Models
Delete a Model:

If you need to remove a model to free up space:

ollama rm deepseek-rxxx

5. Testing and Using DeepSeek LLMs

You can interact with the DeepSeek models through the terminal. For example:

ollama run deepseek-rxxx

Then, type your input query to test the model's capabilities.
DeepSeek Models Available

DeepSeek provides multiple models optimized for various tasks. Common versions include:
1.5B version (smallest):
ollama run deepseek-r1:1.5b

8B version:
ollama run deepseek-r1:8b

14B version:
ollama run deepseek-r1:14b

32B version:
ollama run deepseek-r1:32b

70B version (biggest/smartest):
ollama run deepseek-r1:70b

This is the command to run and install a model from Ollama

ollama run deepseek-r1:8b




In conclusion, running DeepSeek on an 11th Gen Intel i5 laptop CPU proves to be a practical solution for lightweight AI workloads. With the 8B model, the system achieves a processing speed of 1.5–2 words per second, making it perfectly suitable for small-scale applications. While it utilizes around 80–90% of the CPU during operation, the performance is stable and reliable, demonstrating that even modest hardware can power advanced language models effectively when optimized with tools like Ollama and Docker.
 

Read this for the comparison of the Models available.

https://huggingface.co/deepseek-ai/DeepSeek-V3


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