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niuniu
niuniu

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I Switched from GitHub Copilot to Continue.dev. It Cost Me $0 and I Kept My Privacy.

I've been paying $10/month for GitHub Copilot for 8 months. Last week I got the renewal email and asked myself a simple question: am I getting $120/year of value?

The honest answer was no. Most of what I use Copilot for — autocomplete on boilerplate, docstrings, simple refactors — a free, local, open-source setup can do just as well. So I switched to Continue.dev + Ollama and canceled my subscription.

Here's what actually happened.

The Cost Comparison Nobody Talks About

GitHub Copilot Continue + Ollama
Price $10/month ($120/year) $0
Code leaves your machine Yes No
Works offline No Yes
Model choice Locked to OpenAI Any local model
Rate limits Yes None

The privacy part matters more than people admit. Every line you type in your editor gets sent to a third party with Copilot. With Continue + a local model, nothing leaves your laptop. For anyone working on proprietary code, that alone is worth the switch.

What I Actually Set Up

I'm running Continue in VS Code with qwen2.5-coder:7b via Ollama on a 3-year-old laptop with 16GB RAM. Setup took 11 minutes:

# 1. Install Ollama
curl -fsSL https://ollama.com/install.sh | sh

# 2. Pull the coding model (4.7GB, one-time download)
ollama pull qwen2.5-coder:7b

# 3. Start the server
ollama serve
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Then in VS Code: install the Continue extension, add this to config.json:

{
  "models": [{
    "title": "Qwen Coder Local",
    "provider": "ollama",
    "model": "qwen2.5-coder:7b"
  }],
  "tabAutocompleteModel": {
    "title": "Qwen Autocomplete",
    "provider": "ollama",
    "model": "qwen2.5-coder:7b"
  }
}
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Done. No API keys, no account, no billing page.

The Honest Downsides

This isn't a paid ad, so here's the real talk after 5 days of daily use:

  • Autocomplete latency is higher. Copilot suggestions appear in ~300ms. Local 7B takes 1-2 seconds. For me, that's acceptable. For someone writing code at 100 WPM, it might not be.
  • Complex reasoning is weaker. Copilot (backed by GPT-4-class models) is better at "refactor this entire module" tasks. The local 7B model handles line-level and function-level completions well but struggles with multi-file reasoning.
  • You need the RAM. 16GB is the realistic minimum. On an 8GB machine, this setup will swap and crawl.

Where the Free Setup Actually Wins

  • Boilerplate and repetitive code. Writing CRUD endpoints, test stubs, config files — the local model is just as good and unlimited.
  • Offline work. I wrote code on a 6-hour train ride with no WiFi. Copilot would have been a brick.
  • Learning. I can see exactly what the model is doing, swap models freely, and tune prompts. With Copilot, it's a black box.
  • Privacy. Non-negotiable for client work.

My Actual Verdict

If your work is mostly greenfield algorithm design or large refactors, keep Copilot. If your day is 70% boilerplate, tests, and standard patterns — the Continue + Ollama combo will save you $120/year with maybe a 10% quality drop on edge cases.

I'm keeping the $0 setup. The 1-2 second latency is a feature, not a bug — it makes me actually read the suggestions instead of tab-tab-tab accepting everything.

For a fully-managed free alternative with no local setup, I've also been testing MonkeyCode alongside Continue. Worth a look if you don't want to run models yourself.

Have you tried running your coding assistant locally? What was your experience — is the latency worth the privacy and cost savings?

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