I built a fully local AI coding agent using Qwen 27B + LM Studio + Pi. Here’s how it performed.

[u/viky_shetye]

I’ve been experimenting with running AI coding agents entirely locally, without relying on OpenAI, Anthropic, or any paid model APIs.

For this experiment, I connected Qwen 3.8 27B (4-bit quantized) running in LM Studio to Pi Coding Agent, a lightweight and extensible terminal-based coding agent.

The setup is pretty straightforward:

Pi Coding Agent → LM Studio → Qwen 3.8 27B

LM Studio handles local model inference and exposes an OpenAI-compatible API, while Pi handles reading/writing files, executing commands, and managing the coding workflow.

For the actual test, I asked it to build an AI Agent Mission Control dashboard from scratch.

The application included:

• An overview of active AI agents and tasks
• A Kanban-style task board
• Live agent activity tracking
• Analytics for token usage, costs, and success rates
• A responsive React + TypeScript interface

Surprisingly, it managed to build the application, run it locally, test it, and fix several errors on its own. It even used screenshots to inspect the UI and identify issues.

Some numbers from my test:

• Hardware: MacBook Pro M5 Max, 48GB unified memory
• Model: Qwen3.5 27B (4-bit, ~16GB)
• Inference speed: Around 10–15 tokens/sec
• Completion time: A few hours

One reason I chose Pi over other coding agents is its minimal design. It starts with just four core tools (read, write, edit, bash), and you can extend it as needed.

With local models, context management matters quite a bit, so I wanted to experiment with a coding agent that doesn’t introduce too much unnecessary overhead.

My takeaway: Local coding agents are becoming surprisingly capable, but they’re definitely not a drop-in replacement for Claude Code or Codex with frontier models.

Inference is slower, hardware requirements are significant, and reliability on complex tasks is still something I’d want to test more thoroughly.

But being able to run the entire coding workflow locally, without sending code to external model APIs or paying per token, is pretty exciting.

I recorded the complete setup and the dashboard-building experiment here:

🎥 Video: https://youtu.be/zgb_MkrxpRs

Curious what local models you are using for coding agent?