I ran the numbers last month and nearly fell out of my chair: Copilot ($10), Cursor ($20), Windsurf ($15), ChatGPT Plus ($20), Claude Pro ($20). $85/month — $1,020/year — just to write code with AI. And half the time I was rate-limited anyway.
So I cancelled everything. Here's the exact free stack I use now, with the real numbers.
The stack
| Paid tool | Cost | Free replacement | Cost |
|---|---|---|---|
| GitHub Copilot | $10/mo | Continue.dev + Ollama (Qwen2.5-Coder 7B) | $0 |
| Cursor | $20/mo | VS Code + MonkeyCode | $0 |
| ChatGPT Plus | $20/mo | Hugging Face Inference API (free tier) | $0 |
| Claude Pro | $20/mo | Google Colab free T4 + open models | $0 |
| Windsurf | $15/mo | Tabby (self-hosted) | $0 |
| Total | $85/mo | $0/mo |
The setup that matters (10 minutes)
1. Ollama + Qwen2.5-Coder for autocomplete:
curl -fsSL https://ollama.com/install.sh | sh
ollama pull qwen2.5-coder:7b
Then in VS Code, install the Continue extension and point config.json at it:
{
"models": [{
"title": "Qwen Coder (local)",
"provider": "ollama",
"model": "qwen2.5-coder:7b"
}],
"tabAutocompleteModel": {
"title": "Autocomplete",
"provider": "ollama",
"model": "qwen2.5-coder:1.5b"
}
}
2. Colab free T4 for the heavy stuff. Anything that won't fit on my laptop (fine-tuning, 13B+ models) goes to Colab:
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
tok = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-Coder-7B-Instruct")
model = AutoModelForCausalLM.from_pretrained(
"Qwen/Qwen2.5-Coder-7B-Instruct",
torch_dtype=torch.float16, device_map="auto"
) # fits on free T4 (16GB) in fp16
What actually happened after 30 days
Honest numbers, no hype:
- Autocomplete acceptance rate: 31% with Copilot → 24% with Qwen2.5-Coder local. Slightly worse. I notice it maybe twice a day.
- Latency: Local model is faster — 40ms vs 200ms+ round trip. No network, no rate limits, works on planes.
- Big refactors: This is where I lost real ground. Claude Pro is genuinely better at 500-line refactors. I work around it by breaking refactors into smaller chunks.
- Privacy: My code never leaves my machine now. That was worth something on its own.
Net savings: $1,020/year. Net productivity loss: I'd estimate 5-8%. For a side-project dev, that's a trade I'll take every single time.
The catch nobody mentions
You need 8GB+ of free RAM/VRAM for the 7B model. On an 8GB laptop, use qwen2.5-coder:3b or 1.5b for autocomplete — still decent. And if you want a managed free option instead of self-hosting, I wrote up the full comparison on my setup page: https://ly.cyberserval.tech/iIETXiF
Paid AI coding tools in 2026 are the new cable TV bundle — you're paying for 5 subscriptions and using 20% of each. Fight me in the comments: is Copilot's 7% better acceptance rate worth $1,000/year to you, or have you found a free setup that actually sticks?
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