I Tested Free Open-Source AI vs My $200/Month Stack

Can free open-source AI tools really replace a $200/month paid AI stack? We ran the same 1,500-word task through both pipelines: a paid cloud stack (Zapier/Make + a frontier API model, ~$45–70/month) and a $0 self-hosted stack (n8n on Docker + Ollama running local open models like Llama and Mistral). Three scored rounds — setup, output quality, speed & reliability — and an honest final verdict on who should cancel what. ⏱ CHAPTERS 0:00 The $200/Month AI Problem 1:37 The Test: One Task, Two Stacks 3:10 Round 1 — Setup & Privacy 5:32 Round 2 — Output Quality 7:12 Round 3 — Speed, Reliability & Cost 9:22 The Verdict: Who Should Cancel? 10:53 Subscribe / Outro 🔧 TOOLS IN THIS VIDEO n8n (self-hosted automation) Ollama (local models) 📌 THE VERDICT CARDS Stay on paid tools if: your team is non-technical, or your hardware can't run local models. Switch to open source if: subscriptions eat your margins, your data is sensitive, or you want full control. Starting out? Try the hybrid: local n8n + local models first, pay-as-you-go only when you need it. What does your AI stack look like right now — paid, local, or hybrid? Tell me in the comments. #OpenSourceAI #n8n #Ollama