Granite 4.2 LLMs: How They're Built

A technical walkthrough of how we built the Granite 4.2 reasoning model family.

Authors: Granite Team, IBM

TL;DR: Granite 4.2 is our first family of dense, decoder-only reasoning LLMs, released in three sizes: 3B, 8B, and 30B. Each model is pre-trained from scratch on roughly 15T tokens with a five-phase strategy that extends the context window to 512K tokens, supervised fine-tuned on chain-of-thought, reasoning, and agentic-trajectory data, then post-trained with a multi-stage reinforcement learning pipeline. That pipeline includes agentic RL, where the 8B and 30B models learn to act with tools inside real sandboxed environments. Every model has a thinking / non-thinking switch, a low-effort thinking mode that spends a short reasoning budget on easy questions, and native tool calling. All Granite 4.2 models are released under the Apache 2.0 license.

Links:

Granite 4.2 HF Collection