The guide provides a comprehensive framework for benchmarking speech-to-text (STT) APIs, focusing on key metrics like accuracy, speed, and cost to inform production decisions. It highlights the importance of Word Error Rate (WER) among other error rates, latency, and total cost of ownership while emphasizing the need for domain-specific testing to ensure accuracy in real-world scenarios. The document outlines a step-by-step methodology for conducting benchmarks, including assembling production-realistic audio and standardizing scoring to ensure fair comparisons. It further discusses secondary signals crucial for API selection, such as scalability, reliability, and formatting quality, which determine the API's viability in production environments. The 2025 benchmark leaderboard identifies Deepgram Nova-3 as a leading performer, offering significant improvements in accuracy and speed at competitive pricing, with features like runtime keyword prompting and multi-language support that cater to diverse production needs. The guide concludes by suggesting that benchmark data, complemented by real-world validation, is essential for informed technical decisions.