{
  "id": 138926,
  "title": "How to Use Qwen 3 with VS Code (FREE) | Complete Setup with Ollama",
  "url": "https://urgent.news/2026/08/04/how-to-use-qwen-3-with-vs-code-free-complete-setup-with-ollama",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-08-04T17:31:59.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/thecodestreet/how-to-use-qwen-3-with-vs-code-free-complete-setup-with-ollama-29f8"
  },
  "original_language": "en",
  "account": "Utilizing Qwen 3 alongside Visual Studio Code, free of charge, is now a realistic possibility. This is achieved through the integration of Qwen 3 and Ollama, enabling the execution of a potent coding model directly on your personal computer without incurring any API fees or reliance on cloud services. Consequently, all coding activities retain their privacy and security within your local environment. This tutorial will guide you through the process of setting up Qwen 3 with VS Code, utilizing Ollama as your intermediary. By the conclusion of this guide, you will have acquired knowledge on: Installing Ollama, acquiring Qwen 3, integrating Qwen 3 into VS Code, configuring OpenCode, generating your initial AI-generated code, troubleshooting common setup challenges, and effectively leveraging local AI capabilities. Qwen 3, the most recent series of open-source large language models developed by Alibaba, demonstrates remarkable proficiency in various programming tasks such as code generation, debugging, code explanation, refactoring, and general programming undertakings. Its remarkable capability to operate locally through Ollama eliminates the necessity for reliance on cloud APIs for everyday coding aid. Ollama, in essence, empowers the execution of Large Language Models on individual computers, thereby offering: Enhanced privacy, devoid of any API charges, offline functionality with swift local responses, and streamlined model management. To commence the installation of Ollama, download the software from the official website at https://ollama.com. Confirm the installation by executing the command \"ollama --version\". Subsequently, download Qwen 3 with the command \"ollama pull qwen3.6:latest\". Verify the successful installation of Qwen 3 by listing the available models with \"ollama list\". Upon completion, Qwen 3 will appear in the list of installed models. To establish connectivity between Qwen 3 and VS Code, configure OpenCode to utilize your Ollama server. The typical endpoint for communication is either \"http://localhost:11434\" or \"http://localhost:11434/v1\", contingent upon your specific configuration. Subsequently, generate your inaugural piece of code. Rather than requesting the creation of an entire React application, commence with a more straightforward task. For instance, crafting a reusable React Button component utilizing functional components and CSS Modules. Short and precise prompts generally yield superior results when working with local models. Common pitfalls include: Overly broad prompts, such as asking for the development of an entire application; opting for a model that lacks coding capabilities; and expecting functionality similar to cloud-based models from a local setup. My personal experience with Qwen 3 underscored that the most significant limitation stemmed not from the model itself, but rather from my approach to prompting. By adopting a step-by-step strategy for project development, rather than expecting the generation of a fully functional application in a single response, the quality of the generated code substantially improved. The journey doesn't end here. This tutorial serves as Part 1 in a series, where the subsequent part will involve constructing a comprehensive GitHub Profile Finder application utilizing React, GitHub API, Qwen 3, VS Code, and Ollama, all guided by detailed prompts. For further insights into AI, .NET, C#, Ollama, Qwen AI, Semantic Kernel, VS Code, and Software Development, consider following TheCodeStreet.",
  "summary": "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…",
  "key_points": [
    "Install Ollama from official website",
    "Download Qwen 3 via \"ollama pull qwen3.6:latest\"",
    "Configure OpenCode for Ollama server communication"
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}