Have you ever wanted an AI coding assistant inside VS Code without paying for GitHub Copilot or other monthly subscriptions? The good news is—you can. Using Qwen 3 and Ollama, you can run a powerful coding model directly on your computer and use it inside VS Code. No API costs. No cloud dependency. Your code stays on your machine. 📺 Watch the Complete Video Tutorial 🎥 YouTube Video: How to Use Qwen 3 with VS Code (FREE) | Complete Setup with Ollama What You'll Learn By the end of this tutorial you'll know how to: Install Ollama Download Qwen 3 Connect Qwen 3 with VS Code Configure OpenCode Generate your first AI code Fix common setup issues Use local AI effectively What is Qwen 3? Qwen 3 is Alibaba's latest family of open-source large language models. It performs well for: Code Generation Debugging Code Explanation Refactoring General Programming Tasks Since it can run locally using Ollama, you don't need to rely on cloud APIs for everyday coding assistance. What is Ollama? Ollama lets you run Large Language Models directly on your computer. Benefits include: Privacy No API Charges Offline Support Fast Local Responses Easy Model Management Step 1 — Install Ollama Download Ollama from: https://ollama.com Verify installation: ollama --version Step 2 — Download Qwen 3 Run: ollama pull qwen3.6:latest Verify: ollama list You should now see the Qwen 3 model installed locally. Step 4 — Connect Qwen 3 with VS Code Configure OpenCode to use your Ollama server. Typical endpoint: http://localhost:11434 or http://localhost:11434/v1 depending on your configuration. Step 5 — Generate Your First Code Instead of asking: Build an entire React application Start with something simple. Example: Create a reusable React Button component using functional components and CSS Modules. Small prompts generally produce better results with local models. Common Mistakes ❌ Asking for an entire application Instead: Break the project into smaller components. ❌ Choosing the wrong model Use a coding-capable Qwen model whenever possible. ❌ Expecting cloud-model behavior Local models work best when you: Keep prompts focused Iterate gradually Review generated code My Experience After experimenting with Qwen 3, I realized that the biggest limitation wasn't the model itself—it was my prompting strategy. Once I started building projects step by step instead of expecting an entire application in one response, the quality improved significantly. What's Next? This article is Part 1 of the series. In Part 2 we'll build a complete GitHub Profile Finder using: React GitHub API Qwen 3 VS Code Ollama …all with step-by-step prompts. Resources Ollama https://ollama.com Qwen Models https://ollama.com/library/qwen3 VS Code https://code.visualstudio.com/ Conclusion Running Qwen 3 locally inside VS Code is a great option if you want a private, free AI coding assistant. Whether you're learning React, JavaScript, or working on professional software projects, local AI models have become capable enough to be part of your daily development workflow. 🎥 Prefer Watching? If you found this article helpful, consider following TheCodeStreet for more tutorials on: AI .NET C# Ollama Qwen AI Agents Semantic Kernel VS Code Software Development Happy Coding! 🚀

ollama --version

ollama pull qwen3.6:latest

ollama list

http://localhost:11434

http://localhost:11434/v1

Create a reusable React Button component using functional components and CSS Modules.