How to Run DeepSeek Locally on Windows 11

If you’ve been exploring AI coding assistants lately, you’ve probably come across DeepSeek — an open-source AI model designed for code understanding, generation, and debugging. While most people use it through the cloud or inside editors like VS Code, you can also run DeepSeek locally on Windows 11 — giving you full privacy, faster responses, and no internet dependency.

In this guide, we’ll walk you through exactly how to set up and run DeepSeek locally on your Windows 11 PC — step by step.

What You’ll Need Before You Start

Before running DeepSeek locally, make sure you have these prerequisites:

• A Windows 11 (64-bit) computer
• At least 8 GB of RAM (16 GB recommended)
• Python 3.10+ installed
• Git installed
• Internet connection (for setup only)
• Optional: A GPU (NVIDIA) with CUDA support for faster inference

Once installed, DeepSeek can run completely offline.

Step 1: Install Python and Git

If you don’t already have Python or Git installed:

Install Python

1. Go to https://www.python.org/downloads/windows/.
2. Click Download Python 3.12 (or latest version).
3. Run the installer and make sure to check:
   ✅ “Add Python to PATH”
4. Complete the installation.

Verify it by opening Command Prompt and typing:

python --version

You should see something like:

Python 3.12.1

Install Git

1. Download from https://git-scm.com/downloads.
2. Run the installer and accept default settings.
3. Verify installation: git --version You should see: git version 2.46.0

Step 2: Install Dependencies (PyTorch and Transformers)

DeepSeek uses machine learning libraries like PyTorch and Transformers to run locally.

Install PyTorch

Run this in Command Prompt or PowerShell:

pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121

If you don’t have a GPU, replace the URL with the CPU-only version:

pip install torch torchvision torchaudio

Install Transformers

pip install transformers

These two libraries handle model loading and inference.

Step 3: Clone the DeepSeek Repository

Now you’ll download the DeepSeek model code from GitHub.

In Command Prompt or PowerShell:

git clone https://github.com/deepseek-ai/deepseek-coder.git

Once cloned, navigate to the project folder:

cd deepseek-coder

Step 4: Download the DeepSeek Model

You’ll need to download one of the available DeepSeek models from Hugging Face.

Visit the official model page: https://huggingface.co/deepseek-ai

Choose a model based on your system specs:

Model	Type	Recommended For
deepseek-coder-1.3b	Lightweight	Laptops, 8GB RAM
deepseek-coder-6.7b	Balanced	Mid-range PCs
deepseek-coder-33b	Full	High-end systems with GPU

Once you’ve picked your model, download it manually or let the Transformers library pull it automatically during runtime.

Step 5: Load and Run DeepSeek Locally

Create a new Python file named run_deepseek.py inside your deepseek-coder folder.
Add the following code:

from transformers import AutoTokenizer, AutoModelForCausalLM

# Load the DeepSeek model
model_name = "deepseek-ai/deepseek-coder-1.3b"

print("Loading model, please wait...")
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

print("Model loaded successfully!")

# Simple interactive prompt
while True:
    prompt = input("\nYou: ")
    if prompt.lower() in ["exit", "quit"]:
        break

    inputs = tokenizer(prompt, return_tensors="pt")
    outputs = model.generate(**inputs, max_length=200)
    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
    print("\nDeepSeek:", response)

Save and run the script using:

python run_deepseek.py

The model will load (the first time might take a few minutes).
Once loaded, you can chat or generate code directly in your terminal — all offline.

Step 6: Ask DeepSeek to Generate or Explain Code

You can now prompt DeepSeek like this:

You: Write a Python function to check if a number is prime.

It will respond:

def is_prime(n):
    if n <= 1:
        return False
    for i in range(2, int(n**0.5) + 1):
        if n % i == 0:
            return False
    return True

Or ask:

You: Explain this function line by line.

DeepSeek will provide a detailed explanation — just like an AI code tutor running on your machine.

Step 7: Run DeepSeek With GPU (Optional)

If your PC has an NVIDIA GPU, you can enable GPU acceleration to make DeepSeek much faster.

Modify this section in your Python file:

model = AutoModelForCausalLM.from_pretrained(model_name).to("cuda")

Then verify that your GPU is being used:

nvidia-smi

This will show your GPU’s utilization while DeepSeek runs.

Step 8: Create a Simple Local Web Interface (Optional)

If you’d prefer a friendlier interface instead of using the terminal, you can create a local web UI using Gradio.

Install Gradio:

pip install gradio

Create a new file named app.py:

import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM

model_name = "deepseek-ai/deepseek-coder-1.3b"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

def deepseek_chat(prompt):
    inputs = tokenizer(prompt, return_tensors="pt")
    outputs = model.generate(**inputs, max_length=200)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

demo = gr.Interface(fn=deepseek_chat, inputs="text", outputs="text", title="DeepSeek Local Chat")
demo.launch()

Run it:

python app.py

Now open your browser and go to:

http://127.0.0.1:7860

You’ll see a local chat interface for DeepSeek — all running locally!

Step 9: Troubleshooting Common Issues

Problem	Fix
CUDA error	Install the correct PyTorch version for your GPU.
Out of memory	Try a smaller model (like deepseek-coder-1.3b).
Slow startup	The model needs to load into RAM or VRAM — be patient.
Tokenizer not found	Check internet connection during the first run; it downloads once.
ModuleNotFoundError	Run pip install transformers torch gradio again.

Once the model downloads, it will run offline from cache — no internet needed afterward.

Wrapping Up

And that’s it! You’ve successfully learned how to run DeepSeek locally on Windows 11. With DeepSeek running on your PC, you now have a private, powerful AI coding assistant that can help you generate, debug, and explain code — all without sending data to the cloud.

Whether you’re coding in Python, JavaScript, or C++, this setup gives you complete control over your workflow.

So fire up your terminal, load DeepSeek, and start building with AI — locally, privately, and on your own terms.