After weeks of testing different API providers for my side project, I wanted to share some findings that might help others in the same boat. I've been building a document analysis pipeline that processes roughly 10K pages daily - extracting entities, summarizing sections, and generating structured metadata. Initially I was running everything through the usual suspects, but the monthly bill was getting out of hand. Here's what I discovered: not all inference endpoints are created equal, even when they claim to serve the same model. The token throughput variance between providers can be massive, and that directly impacts your cost structure if you're paying per token rather than per request.…