QuickCompare just dropped on Product Hunt. Here is why you need to stop trusting rigged public benchmarks and start evaluating LLMs on your own garbage data.
Let's be real, most AI devs right now suffer from a common disease: we either blindly pick the most expensive, massive model to play it safe, or we look at some rigged public benchmarks, code it up, and cry when the monthly API bill hits our inbox.
Trismik just threw their new product, QuickCompare, onto Product Hunt and quickly bagged over 170 upvotes. The TL;DR for you lazy scrollers: it's a tool where you dump your own data, and it pits 50+ LLMs against each other to see which one is the cheapest, fastest, and smartest for your specific use case.
Forget generic public benchmarks (we all know they are essentially a glorified, manipulated leaderboard anyway). QuickCompare gives you a clear side-by-side comparison of Quality, Cost, and Latency. They also baked in an AI assistant named Ziggy to handle the tedious prompt setups and LLM-as-Judge configurations so you don't have to write manual scripts like a caveman.
Skimming through the comment section, the community vibe is highly practical:
Public leaderboards are reality TV for tech bros—fun to watch, but useless for your actual business logic. Just because a model is #1 on a leaderboard doesn't mean it'll parse your company's messy JSON logs better than a much cheaper, open-source alternative.
QuickCompare is hitting a very real nerve: Inference optimization. The survival lesson here? Stop trusting benchmarks. Test on your own data. If a cheaper model gets the job done without chewing up your RAM and your wallet, that's your winner.
By the way, there's a promo code PH10FC floating in the comments for an extra $10 in credits. If you're building with LLMs, go bleed their servers dry and test it out.
