GitHub Copilot is $10/month. My company wouldn't approve the expense, and I wasn't comfortable sending proprietary code to Microsoft's cloud. Then I found Tabby — open-source, self-hosted, and free.
Why Tabby Over Copilot
| GitHub Copilot | Tabby (self-hosted) | |
|---|---|---|
| Price | $10/mo ($120/yr) | $0 |
| Code privacy | ❌ Sent to cloud | ✅ Local only |
| Model choice | Locked to OpenAI | Any GGUF (StarCoder, CodeLlama, DeepSeek) |
| Offline use | ❌ | ✅ |
| Team features | Yes | Yes (with auth) |
The 5-Minute Setup
# Docker (easiest)
docker run -it --gpus all -p 8080:8080 \
-v $HOME/.tabby:/data \
tabbyml/tabby serve --model StarCoder-1B --device cuda
# Or bare metal
curl -sSfL https://github.com/TabbyML/tabby/releases/latest/download/tabby-x86_64-unknown-linux-musl.tar.gz | tar -xz
./tabby serve --model StarCoder-1B
VS Code extension: install "Tabby" from marketplace, point to http://localhost:8080.
My Actual Usage
I run Tabby on a $300 used GTX 3060. StarCoder-1B is 80% as good as Copilot for boilerplate, and 100% better for privacy. Completion latency is ~200ms vs Copilot's ~50ms — noticeable but not blocking.
For heavier lifting (refactoring, test generation), I switch to a local 7B model. The ability to swap models based on task complexity is something Copilot can't do.
The Tradeoff
Tabby's autocomplete is not as polished as Copilot's. It misses more edge cases, and the VS Code extension has occasional hiccups. But for $120/year savings and full code privacy? Worth it.
I configured my Tabby + local model stack with MonkeyCode: https://ly.cyberserval.tech/iIETXiF
Anyone else self-hosting their coding assistant? What model are you running?
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