# Local AI Code Completion in VS Code with Qwen2.5-Coder and Ollama > Source: > Published: 2026-08-05 17:40:00+00:00 # Local AI Code Completion in VS Code with Qwen2.5-Coder and Ollama Wire Qwen2.5-Coder through Ollama and Continue for private, offline autocomplete and chat in VS Code. [Rachel Goldstein](https://sourcefeed.dev/u/rachel_goldstein) ## What you'll build A fully local AI coding setup in VS Code: [Qwen2.5-Coder](https://github.com/QwenLM/Qwen2.5-Coder) running under [Ollama](https://ollama.com), wired into the [Continue](https://continue.dev) extension for tab autocomplete and inline chat. Nothing leaves your machine — it works on a plane, and proprietary code never touches a third-party API. ## Prerequisites - macOS, Linux, or Windows with at least 8 GB of RAM (16 GB is comfortable if you want the 7B chat model alongside your editor) - About 6 GB of free disk for the two models - A current [VS Code](https://code.visualstudio.com)install with the`code` CLI on your PATH - Verified against Ollama 0.32.5, Continue extension 2.1.0, and the `qwen2.5-coder` tags on the Ollama library, August 2026 ## 1. Install Ollama Ollama is the local model server everything else talks to. On macOS or Windows, download the installer from [ollama.com/download](https://ollama.com/download) and run it — the app starts a server on `localhost:11434` and keeps it running in the background. On Linux: ``` curl -fsSL https://ollama.com/install.sh | sh ``` The script installs Ollama and registers a systemd service, so the server is already running. Confirm: ``` curl http://localhost:11434 ``` You should get back `Ollama is running` . ## 2. Pull the Qwen2.5-Coder models You want two models for two jobs: a small one for autocomplete, where latency matters more than brains, and a bigger one for chat and edits. ``` ollama pull qwen2.5-coder:1.5b ollama pull qwen2.5-coder:7b ``` The 1.5B is a 986 MB download; the 7B is 4.7 GB. Always pin the size tag — a bare `qwen2.5-coder` resolves to `:latest` , which is the 7B, and that's too slow for autocomplete on most laptops. ## 3. Install the Continue extension Install Continue from the VS Code Marketplace (search "Continue", publisher *Continue*), or from the terminal: ``` code --install-extension Continue.continue ``` On first launch Continue creates its config file and adds a chat icon to the sidebar — you can skip any sign-in it offers, since local models need no account. ## 4. Point Continue at your local models Continue reads `~/.continue/config.yaml` (`%USERPROFILE%\.continue\config.yaml` on Windows). Open it directly in your editor, or from Continue's chat sidebar (`Cmd/Ctrl+L` ): click the agent selector above the input and hit the gear icon next to your local config. Replace the `models` section so the file looks like this: ``` name: Local Assistant version: 1.0.0 schema: v1 models: - name: Qwen2.5-Coder 7B provider: ollama model: qwen2.5-coder:7b roles: - chat - edit - apply - name: Qwen2.5-Coder 1.5B provider: ollama model: qwen2.5-coder:1.5b roles: - autocomplete ``` Save the file — Continue reloads automatically, no restart needed. It assumes Ollama's default address; you'd only add an `apiBase` if Ollama runs on another machine or port. Finally, make sure VS Code's `editor.inlineSuggest.enabled` setting is on (it is by default), and disable GitHub Copilot if you have it installed, so two extensions aren't fighting over the same ghost text. ## Verify it works First check both models are in place: ``` ollama list NAME ID SIZE MODIFIED qwen2.5-coder:7b 2b0496514337 4.7 GB 2 minutes ago qwen2.5-coder:1.5b d7372fb82b10 986 MB 4 minutes ago ``` (Your `ID` values will differ.) Then in VS Code, create `test.py` and type `def fibonacci(` — pause, and gray ghost text should appear with a suggested completion. Press `Tab` to accept it. The very first completion takes a few seconds while Ollama loads the model into memory; after that it's near-instant. Running `ollama ps` in a terminal should now show `qwen2.5-coder:1.5b` loaded. For chat, press `Cmd/Ctrl+L` , pick *Qwen2.5-Coder 7B* in the model dropdown, and ask it to explain the file. Final proof: turn off Wi-Fi and do it all again — everything still works. ## Troubleshooting ** Error: listen tcp 127.0.0.1:11434: bind: address already in use** — you ran `ollama serve` while the server was already running (the desktop app and the Linux systemd service start it for you). Don't run `serve` manually; just use `ollama pull` and friends.**A Continue error ending in not found, try pulling it first** — your config names a tag that isn't downloaded. Continue never pulls models itself. Run `ollama list` and make the `model:` values match the listed tags exactly, size suffix included.**Ghost text never appears** — autocomplete may be paused: click the *Continue* item in VS Code's status bar and re-enable it. Then confirm `editor.inlineSuggest.enabled` is `true` and that Copilot's inline suggestions are off. **Completions show up but take seconds** — the autocomplete role is on a model that's too big, or you're low on RAM. Keep autocomplete on the 1.5B; on older hardware drop to `qwen2.5-coder:0.5b` , and use `ollama ps` to see what's actually loaded. ## Next steps If you've got the hardware (24 GB+ RAM or a decent GPU), swap the chat role to `qwen2.5-coder:14b` or `:32b` — same config shape, better answers. Add codebase-aware chat by pulling `nomic-embed-text` and giving it the `embed` role, which powers Continue's `@Codebase` context. And when completions feel too eager or too sluggish, tune `debounceDelay` and `maxPromptTokens` — the [autocomplete deep dive](https://docs.continue.dev/customize/deep-dives/autocomplete) covers both. ## Sources & further reading - [Continue Autocomplete Setup and Configuration Guide](https://docs.continue.dev/customize/deep-dives/autocomplete)— docs.continue.dev - [How to Configure Continue](https://docs.continue.dev/customize/deep-dives/configuration)— docs.continue.dev - [config.yaml Reference](https://docs.continue.dev/reference)— docs.continue.dev - [qwen2.5-coder model library page](https://ollama.com/library/qwen2.5-coder)— ollama.com - [Download Ollama](https://ollama.com/download)— ollama.com - [Ollama Releases](https://github.com/ollama/ollama/releases)— github.com [Rachel Goldstein](https://sourcefeed.dev/u/rachel_goldstein)· Dev Tools Editor Rachel has been embedded in the developer tooling ecosystem for nearly eight years, covering everything from IDE wars and package-manager drama to the quiet rise of AI-assisted coding. She has a soft spot for open-source maintainers and an unhealthy number of terminal emulators installed on a single laptop. ## Discussion 0 No comments yet Be the first to weigh in.