LLMTest

LLMTest solves the problem everyone building AI apps eventually faces: your prompts suck and you're burning money on expensive models when cheaper ones would work fine. Actually, most teams just pick whatever model their CEO saw on Twitter and hope for the best. LLMTest says nah—we'll figure out what's actually working and swap in better options while you sleep.

Here's the deal: they benchmark across 340+ models in the build phase so you ship with the best one from day one—no guessing, no hoping. Then once you're live, Autopilot kicks in. It watches your real traffic, tests shorter and cheaper prompt variants against your actual users every week, and if something wins with 95% confidence, it goes live. Two independent judges (Claude Sonnet and GPT-4o) have to agree. Wilson lower bound needs to clear 50% or you need 4 wins with zero losses. This isn't some rando A/B test—this is serious optimization that could save you tens of thousands monthly.

Oh, and automatic failover when APIs go down. New models get tested daily. Gemini 2.5 Pro dropped? They'll benchmark it against your flows and if it's cheaper and equally good, they'll suggest the switch. One click, or auto-deploy if you want. Monday morning you get a diff email showing what changed and what you saved. Five gates every change has to clear. Safe by default.

They're going after the "$50 billion getting wasted on inefficient LLM calls" problem. Everyone's obsessing over which model is trending—LLMTest just wants to make sure you're not throwing money at GPT-4 when Sonnet 4o does the job for half the cost.