Without Benchmarking LLMs, You're Likely Overpaying 5-10x
Summary
Karl Lorey argues that benchmarking LLMs is essential to avoid overpaying for API usage, showing how a non-technical founder cut a 1,500 USD/month bill by testing 100+ models. He outlines a practical workflow to benchmark prompts, uses an LLM judge to score results, and introduces Evalry as a tool to automate this process, emphasizing quality, cost, and latency trade-offs.