# Unlock Free AI-Powered Coding Assistance with DeepSeek-Coder-V2 and Ollama: Your Local, Lightweight Code Companion

> In today’s fast-paced development world, AI tools are transforming how we write code.

- Author: Abdur Rahman (https://abdur.tech/about/)
- Published: 2025-02-19
- Category: AI
- Tags: ai, llm, tooling
- Canonical: https://abdur.tech/writing/deepseek-coder-v2-with-ollama/

## Introduction

In today’s fast-paced development world, AI tools are transforming how we write code. DeepSeek-Coder-V2, a nice open-source LLM (Large Language Model), paired with Ollama, offers an exceptional local coding assistant — all for free. With Ollama, you can run DeepSeek-Coder-V2 efficiently on your machine, eliminating the need for cloud APIs.

This guide walks you through the process of installing and using DeepSeek-Coder-V2 with Ollama, integrating it with VS Code’s **CodeGPT** extension for AI-driven autocompletion, and comparing its performance with other models available in Ollama.

## Why DeepSeek-Coder-V2 with Ollama is a Game-Changer for Developers

Here’s why this setup should be on your radar:

**Free & Open Source** — No subscription needed. Run it locally without incurring cloud fees.

**Optimized for Code** — Trained on a wide range of programming languages, DeepSeek-Coder-V2 is a solid alternative to proprietary models.

**Lightweight & Efficient** — Despite having 236B parameters in its original form, the Ollama-optimized version is just ~8.9GB, meaning it can run smoothly on most modern machines.

**Seamless Integration with VS Code** — Unlock the power of AI-assisted code autocompletions with the **CodeGPT VS Code extension**, boosting your productivity.

## How to Install and Run DeepSeek-Coder-V2 with Ollama

**Step 1: Install Ollama**

Ollama is an intuitive tool for running language models locally. To get started:

**macOS and Linux:** run the following command in your terminal:

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

**Windows:** download and install Ollama from [ollama.com](https://ollama.com/).

**Step 2: Download DeepSeek-Coder-V2**

Once Ollama is installed, pull the DeepSeek-Coder-V2 model:

```bash
ollama pull deepseek-coder-v2
```

The quantized version is only ~8.9GB, much smaller than its original form.

To test if it’s working, run:

```bash
ollama run deepseek-coder-v2
```

This will start an interactive session where you can ask coding-related queries.

## Integrating DeepSeek-Coder-V2 with VS Code and CodeGPT

VS Code, combined with **CodeGPT**, provides smooth AI-powered code autocompletion.

**Step 1: Install the CodeGPT Extension**

1.  Open **VS Code** and go to the **Extensions** panel (Ctrl + Shift + X).
2.  Search for **CodeGPT** and install it.

[Image: VS Code Extensions Marketplace search for CodeGPT, with the CodeGPT: Chat & AI Agents extension highlighted]

**Step 2: Configure CodeGPT to Use Ollama**

1. Open the CodeGPT menu and select the autocomplete setting.

[Image: CodeGPT Chat panel in VS Code with the autocomplete settings icon highlighted in the toolbar]

2. Select the deepseek-coder-v2 model, save the settings and restart VS Code.

[Image: CodeGPT AI code auto-completion dialog with deepseek-coder-v2 (Ollama) selected from the model list]

**Step 3: Try AI Autocompletion**

Open any code file, start typing a function, and see how DeepSeek-Coder-V2 suggests autocompletions based on the context.

For example, if you write a comment like:

```text
// write a program in Go that prints "Hello, World!"
```

It will generate:

[Image: Editor showing a Go Hello, World program generated from a one-line comment prompt]

## Conclusion

Running DeepSeek-Coder-V2 locally via Ollama is a great way to get AI-assisted coding — free, efficient, and easy to use. Pairing it with VS Code’s **CodeGPT** extension brings even more productivity boosts, all without the hassle of cloud costs.

If you’re searching for a free and powerful alternative to GitHub Copilot, give this setup a try.

**Next Steps**: Test it yourself and share your experience!