IBM used a curated dataset of 13 trillion tokens to train the Granite 4.1 family. These models utilize a dense transformer architecture optimized for enterprise tasks. The release focuses on data quality over sheer parameter count. Developers can now implement these models for high-precision RAG workflows without the overhead of larger, less efficient LLMs.