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

#ai #opensource #coding #tips

I paid for GitHub Copilot for two years. Last month I cancelled, replaced it with a fully free, mostly-local AI coding setup, and tracked my acceptance rate and latency for 3 weeks. Conclusion up front: the free stack covers ~90% of what I used Copilot for, and it's not the 90% you'd expect.

The 4 Tools (All Free, All Tested Daily)

Tool What it replaces Runs where Cost
Continue Copilot Chat + inline edits Your editor, any model $0
Tabby Copilot autocomplete Self-hosted server $0
MonkeyCode Agentic multi-file tasks Web Free tier
Dify Custom AI workflows/RAG over your codebase Self-hosted $0

Tabby: The Copilot Autocomplete Clone Nobody Talks About

Self-hosted code completion, one Docker command:

docker run -it --gpus all -p 8080:8080 \
  -v $HOME/.tabby:/data \
  tabbyml/tabby serve --model Qwen2.5-Coder-1.5B --device cuda
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Then point the VS Code extension at localhost:8080. With the 1.5B model on my GPU:

  • Suggestion latency: ~180ms (Copilot averaged ~300ms for me through their API)
  • Acceptance rate over 3 weeks: 31% (my Copilot historical: ~34%)

A 3-point acceptance gap, at 3x lower latency, at $0. The 1.5B model is noticeably weaker on rare APIs, but for boilerplate, tests, and repetitive patterns — which is 80% of what autocomplete actually completes — it's a wash.

Continue: Chat That Doesn't Hold Your Code Hostage

Continue is an open-source VS Code/JetBrains extension that wires any model (local Ollama, free API, whatever) into chat, inline edit, and @-mention context:

# ~/.continue/config.yaml
models:
  - name: Local Qwen
    provider: ollama
    model: qwen2.5-coder:7b
  - name: Autocomplete
    provider: ollama
    model: qwen2.5-coder:1.5b
    roles: [autocomplete]
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Highlight a function, Ctrl+I, "add error handling and write tests" — runs against the local 7B model. Zero tokens sent anywhere. For my day-job codebase, that's not a nicety, it's compliance.

MonkeyCode: Where the Free Stack Gets Agentic

Autocomplete and single-file edits are solved. The gap vs paid tools is agentic, multi-file work ("add this feature across these 6 files"). MonkeyCode is the free tool I found that actually does this reasonably — it's what I reach for when a task is too big for an inline edit but too small to justify a frontier-model subscription. Try it: https://ly.cyberserval.tech/iIETXiF

Dify: The Unglamorous One

Dify isn't a coding assistant — it's an open-source LLM app builder. I use it for one thing: RAG over our internal docs + codebase, wired to the local Ollama model. "How does our auth refresh flow work?" → answers with file references. Took an afternoon to set up with Docker Compose. Replaces the "ask a senior dev" tax for new hires.

The Honest 10% Gap

What the free stack still loses at:

  1. Hard architectural refactors — local 7B models lose the plot over 10+ files. Paid frontier models still win here, decisively.
  2. Zero-setup convenience — I spent a weekend on this. Copilot is 5 minutes. Your call what a weekend is worth vs $240/year forever.
  3. Rare/niche framework knowledge — small local models hallucinate obscure APIs more.

The controversial take: Copilot's moat in 2026 isn't quality — it's that devs won't spend one weekend to save $240/year, every year. The free tools crossed "good enough" a year ago and most people haven't noticed.

Full setup guides and more free-tool breakdowns: https://ly.cyberserval.tech/iIETXiF

Have you actually tried replacing Copilot with a local setup? What broke for you — or what's the excuse holding you back?

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