IBM used a curated dataset of 15 trillion tokens to train Granite 4.1. The team focused on high-quality synthetic data and rigorous filtering to improve reasoning. This approach reduces hallucinations in enterprise tasks. Developers can now leverage these weights for specialized business applications via Hugging Face, offering a transparent alternative to closed models.