jamesarslan

jamesarslan / local-ai-coding-setup

Public

Complete local AI coding pipeline: Qwen3.5-35B-A3B + llama-server + TurboQuant + OpenCode + Context7 MCP + Chrome DevTools. 188 t/s on RTX 5090, zero cloud APIs.

10
3
100% credibility
Found Mar 29, 2026 at 10 stars -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
Shell
AI Summary

A guide with simple starters to set up a high-performance local AI assistant for coding tasks on powerful graphics-equipped computers.

How It Works

1
🔍 Discover Local AI Coding Helper

You stumble upon a friendly guide promising super-fast AI help for coding right on your powerful computer, no internet needed.

2
✅ Check Your Setup

You confirm your computer has a strong graphics card and the right software basics to run it smoothly.

3
📥 Download the AI Brain

You grab the ready-to-use AI model file from a trusted sharing site.

4
🛠️ Run Easy Setup Starters

With simple one-click actions, you prepare your personal AI engine optimized for speed and power.

5
Pick Your Speed Mode
🚀
Regular Mode

Balanced speed for everyday coding chats and edits.

🔥
Turbo Mode

Extra compression for handling huge projects without slowing down.

6
💬 Connect and Chat

Link it to browser chats, messaging bots, or smart coding agents, and watch your ideas turn into code instantly.

🎉 Code Like a Pro Locally

Now you have lightning-fast AI coding assistance entirely on your machine, editing files, running commands, and creating projects effortlessly.

Sign up to see the full architecture

5 more

Sign Up Free

Star Growth

See how this repo grew from 10 to 10 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is local-ai-coding-setup?

This Shell-based repo delivers a complete GitHub guide to a fully local AI coding pipeline, letting you run Qwen3.5-35B-A3B on NVIDIA GPUs like the RTX 5090 without cloud APIs. Download the complete GitHub repo, build the inference server, grab the model from Hugging Face, and launch tools like OpenCode for agentic editing, bash execution, and browser automation via Chrome DevTools. Users get 188 tokens/s generation and 131K context support out of the box, all via simple CLI commands.

Why is it gaining traction?

It crushes benchmarks with TurboQuant's 3.5x KV cache compression, freeing VRAM for longer contexts on 24GB+ GPUs—far beyond standard Ollama setups—while matching or beating quality. The complete local AI coding setup includes tuned parameters for coding tasks, Docker for Open WebUI chats, and Telegram bots, slashing setup time from hours to minutes. Developers dig the no-fluff tutorial that exposes pitfalls like wrong default temps in other runners.

Who should use this?

Backend engineers building complex apps who need local agents for file edits and doc searches without API bills. AI tinkerers with RTX 40/50-series cards testing Qwen models on massive contexts. Solo devs ditching cloud latency for offline coding marathons.

Verdict

Solid starter for local AI coding setups if you have the GPU—docs are thorough, benchmarks transparent—but with 10 stars and 1.0% credibility, treat it as a promising prototype, not production-ready. Fork and validate your hardware first.

(198 words)

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.