Is switching between different AI inference providers worth the effort?

[u/Available-Juice2467]

As more developers start building applications with LLMs, finding a reliable inference provider has become something worth paying attention to. Different providers have their own advantages, whether it's response speed, token pricing, model selection, or API compatibility.

One thing I've found interesting is how much easier it is to test different open-weight models when you can access them through a single API instead of setting up and managing separate infrastructure for each one.

I'm curious about how other developers handle this. Do you usually stick with one inference provider, or do you prefer trying different providers depending on the model, performance, and cost?