How I Built a Completely Free Local AI Stack — Inspired by a 60-Second YouTube Short
The author built a fully local AI stack using free tools inspired by a brief YouTube Short, leveraging Ollama to run AI models locally without relying on paid API services. By redirecting Claude Code to communicate with a local Ollama server, the system operates entirely on personal hardware with no data sent to external servers. The setup uses models like Gemma4, chosen for its compatibility with the author's GPU and multimodal capabilities.
- ▪The system uses Ollama as a local API server and model manager to run AI models without cloud dependencies.
- ▪Claude Code can be configured to interact with Ollama locally, bypassing Anthropic's paid API.
- ▪The author selected Gemma4 due to its ~12GB size, multimodal functionality, and efficient performance on their GPU with 11GB VRAM.
- ▪Ollama supports standard API formats, allowing integration with tools like Open WebUI and VS Code extensions.
- ▪Running AI locally requires sufficient hardware resources, particularly VRAM, to ensure fast inference speeds.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3372066) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Pranay ravi Posted on May 17 How I Built a Completely Free Local AI Stack — Inspired by a 60-Second YouTube Short #ai #llm #showdev #tutorial How I Built a Completely Free Local AI Stack — Inspired by a 60-Second YouTube Short By Pranaychandra Ravi It started with a YouTube Short. Someone on my feed casually demonstrated connecting a local AI model to Claude Code and I stopped mid-scroll. No API key. No subscription. No code leaving their machine. I had to know how it worked.
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