Cut your AI API costs by 30–80%. LLMLite automatically routes each prompt to the cheapest capable model. One endpoint, instant savings, free tier included.

Hey Product Hunt! 👋 I’m incredibly excited to launch LLMLite today. I built this because I kept running into two massive headaches while shipping AI apps. First is the cost trap—paying top-dollar frontier model prices for basic prompts that a smaller, lightweight model could handle for pennies is incredibly painful. Second is the downtime nightmare—whenever a major API provider drops or hits a lag spike, your entire app breaks for your users instantly. Balancing my time as a student prepping for engineering exams while trying to build digital projects made me realize I needed a way to automate this optimization without spending hours setting up complex routing logic every single time. 🧠 How it works LLMLite is a lightweight gateway that sits right between your application and your LLMs. You send every prompt to a single endpoint, and the system handles the rest in milliseconds: It classifies the intent (simple, complex, or code) automatically. It routes the request to the most cost-effective model that can handle it flawlessly. It triggers instant, transparent failovers if a primary provider goes down. You end up saving anywhere from 30% to 80% on your overall API bill with zero manual model selection and zero drop in execution quality. 🛠️ Under the hood The whole pipeline is running cleanly on Next.js, Supabase, and Paddle. We actually spent the last few days completely hammering the live webhook backend to ensure token analytics and account updates sync up perfectly in real-time. Drop-in integration takes less than two minutes because the request shape mirrors what you’re already using in production. 🎁 The Offer There is a fully functional Free Tier with 100K tokens per month to test it out risk-free—absolutely no credit card required. I’ll be at my desk all day monitoring the live server logs and hanging out right here in the comments. I would love your brutally honest feedback: What routing features, analytics, or specific model fallbacks do you want to see us build next? Thanks so much for checking it out! Let's build something cool. 🚀

How does the routing actually decide which model can handle a given prompt without sacrificing output quality? Curious how you benchmark "capability" across providers since each one behaves a bit differently.

Switched one of my side project bots over this morning and saw the bill drop almost in half by lunch. The router picked a smaller model for my simpler prompts without me having to think about it.

Plugged it into a side project and the routing just works, picked cheaper models for the easy stuff without me noticing any quality drop on harder ones. Genuinely cut my monthly bill in half.

Routed a few test prompts through it and the cost drop on the reasoning tasks was honestly bigger than I expected, like a 60% difference without the answers getting worse.

Switched one of my side project bots over this morning and saw the bill drop almost in half by lunch. The router picked a smaller model for my simpler prompts without me having to think about it.

Plugged it into a side project and the routing just works, picked cheaper models for the easy stuff without me noticing any quality drop on harder ones. Genuinely cut my monthly bill in half.

Routed a few test prompts through it and the cost drop on the reasoning tasks was honestly bigger than I expected, like a 60% difference without the answers getting worse.

LLMLite

One API endpoint to route prompts, cut costs & downtime

One API endpoint to route prompts, cut costs & downtime