Granite 4.1 LLMs: How They’re Built
Hugging Face Blog
IBM released Granite 4.1, a family of dense language models in three sizes (3B, 8B, and 30B parameters) trained on approximately 15 trillion tokens across a five-phase pipeline that progressively shifts from general web data to curated, high-quality content. The 8B instruct model matches or exceeds the performance of the previous 32B Granite 4.0-H-Small model despite using fewer parameters and a simpler architecture. The models undergo supervised fine-tuning on 4.1 million quality-controlled samples and multi-stage reinforcement learning to improve performance on math, coding, and instruction-following tasks.
