How to Run DeepSeek R1 Locally in VS Code (Privacy Mode Unlocked)

Running DeepSeek R1 locally in VS Code for privacy and offline coding

⚡ Quick Guide: The 3-Step Setup

  • The Backend: We will use Ollama to run the DeepSeek model on your hardware.
  • The Frontend: We will use the Continue extension for VS Code to talk to Ollama.
  • The Result: A 100% offline, air-gapped coding assistant that never sends your proprietary code to the cloud.
  • Prerequisites: at least 16GB RAM (for decent speed) and a modern GPU recommended.

Sending proprietary code to the cloud is a security nightmare.

If you are working on sensitive fintech data or stealth-mode startup IP, you cannot simply paste your functions into ChatGPT.

The solution? Run the AI locally.

DeepSeek R1 has made this accessible to everyone. By running "Open Weights" on your own machine, you get GPT-4 level logic without the data leakage risks.

This guide is the technical "Part 2" of our extensive comparison on The Best Free AI Coding Assistants for VS Code (2026). If you haven't chosen a model yet, start there.

But if you are ready to build the ultimate private coding setup, follow these steps.

Step 1: Install Ollama (The Brain)

First, we need an engine to run the AI model.

Ollama is the industry standard for 2026. It simplifies the complex process of managing LLMs into a single command-line tool.

  1. Download Ollama from the official site (available for Mac, Windows, and Linux).
  2. Install it and open your terminal (Command Prompt).
  3. Type the following command to download DeepSeek R1:

ollama run deepseek-coder:6.7b

Note: We recommend the 6.7B parameter version for most laptops.
If you have a powerful rig (RTX 4090 or Mac M3 Max), try the larger deepseek-coder:33b for superior reasoning.

Step 2: Install "Continue" (The Bridge)

Next, we need to connect that AI brain to your text editor.

Do not use the official proprietary extensions for this. They often try to default back to cloud APIs.

Instead, we use Continue, an open-source extension specifically designed for local LLMs.

Continue acts as a sidebar chat and an autocomplete provider, just like Copilot, but it lets you choose the model.

Step 3: Connect & Configure

Now, let's wire them together.

  1. Open the Continue sidebar in VS Code.
  2. Click the Settings (gear icon) to open config.json.
  3. Add "Ollama" as a provider. Your config should look like this:
{
  "models": [
    {
      "title": "DeepSeek R1 (Local)",
      "provider": "ollama",
      "model": "deepseek-coder:6.7b"
    }
  ],
  "tabAutocompleteModel": {
    "title": "DeepSeek Autocomplete",
    "provider": "ollama",
    "model": "deepseek-coder:6.7b"
  }
}

Save the file.

That’s it. You can now highlight code, press Cmd+L (or Ctrl+L), and ask DeepSeek to refactor it.

The response is generated entirely on your GPU. You could unplug your ethernet cable, and it would still work.

The "Authenticity" Warning

Running locally solves the Privacy problem, but it doesn't solve the Detection problem.

Just because you generated the code offline doesn't mean it looks human.

Universities and corporate compliance teams are using increasingly sophisticated scanners to flag AI-written code. If you are submitting this code for a class or a rigorous code review, you need to know if it screams "AI."

Before you push to production, check our guide on Can Turnitin Detect AI Code? to understand the risks of AI watermarking.

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Frequently Asked Questions (FAQ)

1. What are the minimum system requirements for DeepSeek R1?

For the 6.7B model, you need at least 8GB of VRAM (GPU memory) or 16GB of unified memory (Mac). If you try to run it on a standard 8GB RAM laptop, it will be painfully slow.

2. Is local DeepSeek slower than the Cloud API?

Yes. Cloud APIs run on massive H100 server clusters. Your local machine is doing the heavy lifting, so you might see a slight delay (latency) before the code appears. However, for many devs, the privacy trade-off is worth the milliseconds.

3. Does this setup work without the internet?

Yes. Once you have downloaded Ollama and the DeepSeek model weights (Step 1), you can go completely offline (Air-Gapped). No data ever leaves your local network.

Conclusion

You now have a coding assistant that rivals GPT-4, runs for free, and keeps your secrets safe.

This setup is the "endgame" for privacy-conscious developers in 2026.

It requires 10 minutes of setup, but it buys you absolute peace of mind.

Sources & References

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