Both Google Gemini and ChatGPT strive for build determinism, particularly when users set the `temperature` parameter to `0`. This crucial setting instructs the models to choose the most probable token at each step, significantly reducing randomness in their outputs. However, achieving absolute, consistent determinism remains a substantial challenge across different API calls or over extended periods due to various factors including model updates and version changes, underlying hardware and software optimizations, and distributed computing environments. While both platforms now increasingly offer `seed` parameters to further enhance reproducibility for specific outputs, guaranteeing identical results every single time, especially outside tightly controlled environments, is not always feasible. Consequently, users should anticipate high reproducibility rather than perfect determinism, carefully leveraging both temperature and seed settings to maximize consistency in their development and testing pipelines. More details: https://pictoscope.com/link/click/?l=https://4mama.com.ua/