I Stopped Paying $240/Year for AI Code Completion — These 4 Free Tools Do 90% of It

Description and use

The author replaced paid GitHub Copilot with a free local stack (Continue, Tabby, MonkeyCode, Dify), achieving 90 % of Copilot’s functionality, lower latency, and zero cost.

Problem

Developers paying for paid AI coding assistants like GitHub Copilot may be able to replace most of its functionality with free, locally-hosted tools, reducing cost and improving privacy.

Outcome

The free stack achieved ~90% of the functionality of GitHub Copilot, with lower latency and zero cost, while maintaining compliance by keeping all data local.

Workflow

• 1. Install Tabby via Docker: docker run -it --gpus all -p 8080:8080 -v $HOME/.tabby:/data tabbyml/tabby serve --model Qwen2.5-Coder-1.5B --device cuda
• 2. Point VS Code Tabby extension to localhost:8080
• 3. Configure Continue with local Ollama models via ~/.continue/config.yaml
• 4. Use Continue for chat, inline edits, and autocomplete with local models
• 5. Use MonkeyCode web interface for agentic multi-file tasks
• 6. Use Dify with Docker Compose for RAG over internal docs and codebase

Evidence

The free stack covers ~90% of what I used Copilot for, and it's not the 90% you'd expect.

Source

Suggestion latency: ~180ms (Copilot averaged ~300ms for me through their API)

Source

Zero tokens sent anywhere.

Source