How I Built a Multi-LLM Routing System That Saves $55K/Year

As a developer building AI-powered products, I hit a wall: LLM API costs were destroying my budget. A single GPT-4 call costs $0.03-0.06, and at scale, that adds up to $4,500+/month. So I built a smart routing system that uses 262 providers — and pays $0 for 95% of requests. The Problem Most developers default to one LLM provider (OpenAI, Anthropic, etc.) and eat the cost. But there are dozens of free and near-free alternatives that handle 95% of use cases just fine: DeepSeek — Excellent for coding and Chinese, completely free Groq — Blazing fast inference, free tier generous OpenRouter — 28+ free models including gpt-oss-120b (120B params!) NVIDIA NIM — 185 free models with GPU acceleration SambaNova/Cerebras — Speed-optimized free tiers Architecture Request → Classifier → Complexity Router → Provider Chain ├── Simple → Groq (fastest) ├── Coding → DeepSeek (best for code) ├── Quality → gpt-oss-120b (free 120B) └── Fallback → next provider in chain Simple Router in JavaScript async fun