Without benchmarking LLMs, you're likely overpaying 5-10x

A non-technical founder was spending $1,500 monthly on GPT-5 API calls until benchmarking his prompts against 100+ models revealed he could achieve comparable quality at 5-10x lower cost. The process involved collecting customer support examples, defining expected outputs, running prompts across multiple models, and using an LLM judge to score responses while measuring cost and latency. This approach saved over $1,000 monthly and led to the creation of Evalry, a tool that benchmarks prompts against 300+ models to help businesses avoid overpaying for AI services.