IBM utilized a curated dataset of 10 trillion tokens to train Granite 4.1. The models employ a mixture-of-experts architecture to optimize inference efficiency. This technical breakdown reveals how the team balanced synthetic and organic data for better reasoning. Developers can now better predict model behavior across various enterprise-grade coding tasks.