I Replaced OpenAI's API and Cut My Inference Bill by 94%

I was paying OpenAI ~$380/month for a RAG pipeline doing ~50K requests/day. Most of them were straightforward: summarize this, extract that, classify this ticket. GPT-4o is great. But $2.50 per million input tokens for classification tasks? That's a tax on laziness. I switched to an OpenAI-compatible API running open-weight models. Same openai Python SDK. Same code. Same response format. The bill dropped to ~$22/month. Here's exactly what I did. The Problem: OpenAI Pricing for "Boring" Tasks My pipeline had three jobs: Task Model Requests/day Avg tokens/req Ticket classification GPT-4o 30,000 800 Document summarization GPT-4o 15,000 2,000 Entity extraction GPT-4o-mini 5,000 500 Monthly cost with OpenAI: ~$380 (mostly input tokens). The thing is — these tasks don't need GPT-4o. A good 32B parameter model handles classification and extraction just as well. I tested it. The Switch: 3 Lines of Code from openai import OpenAI # Before (OpenAI) # client = OpenAI(api_key="sk-...") # After (Vol