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Check out Valohai Conduit for tracking LLM inference cost in testing and production! Link in comments!

Most teams pick one LLM provider and stay there. The same workload can cost 12x more depending on which one runs it. Which provider you pick is your call. We just help you find the cheapest one for each workload, whether it's OpenAI, Anthropic, or self-hosted. Module 6 of our free LLM course covers model routing, prompt caching, and the math behind why your AI bill is bigger than it needs to be. By Valohai.

You change a prompt, run three quick tests, they pass, you ship. Then a customer hits a regression the tests didn't cover. Three quick tests aren't an evaluation. An evaluation suite runs the prompt against hundreds of realistic cases, the kind of cases customers actually send. The regression shows up there, before they see it. Module 5 of our free LLM course builds the suite from scratch. By Valohai.

That +2% LLM improvement might be noise. When you evaluate multiple LLM models, small metric changes can look meaningful, until you compare them properly 😅 Valohai LLM runs structured evaluations and shows model performance side by side. So you know what’s real before you ship. Test it free with your own data.

Not every LLM performs best everywhere. Some models excel in one category. Others perform better in another. Valohai LLM lets you compare LLM models across evaluation categories in a structured, notebook-style view. Understand where each model performs best, with your own data.

Your LLM evaluation results shouldn’t disappear. You test multiple models. You get a better score. Later, you’re trying to remember which run produced it. Valohai LLM keeps every LLM evaluation structured, searchable, and comparable in one place. Bring your own data. Start free.