Large language models are evolving before our eyes. In a few short years, they’ve gone from powering reactive chatbots to anchoring autonomous agents that can reason through problems, plan, execute, and self-correct when needed. LLMs are increasingly expected to complete tasks, not just generate responses. This can-do attitude is baked into IBM’s latest Granite language and speech models. Today, IBM is releasing its updated Granite 4.2 languages models. Available in 3B, 8B, and 30B parameter sizes, Granite 4.2 is purpose-built for the agentic workflows that today’s enterprise use cases require. These language models include “thinking” capabilities, native step-by-step reasoning that helps them plan before they act, weigh trade-offs before deciding on a path, and catch mistakes before they can play out in real life. In enterprise workflows, tasks can be ambiguous and involve many steps to complete. An AI model must be able to follow complex instructions, retrieve the correct information, choose the right tools, act in the right sequence, and verify the result. Reasoning helps Granite 4.2 navigate this process more reliably. Granite 4.2’s strong tool-calling and reasoning capabilities allow it to evaluate which applications to use and in what order rather than executing blindly. Software engineering agents built on Granite 4.2 can navigate codebases, handle multi-step development tasks, and operate seamlessly in terminal environments. Granite 4.2 is built for deployment across cloud, on-premises, and edge environments. Its dense architecture supports broad compatibility, and its multiple sizes give teams flexibility. Smaller models can handle high-throughput agentic tasks efficiently. Larger models can be reserved for deeper reasoning and more complex coding workflows. Because Granite 4.2 is released under an Apache 2.0 license, organizations can download, fine-tune, and put it into production without licensing restrictions.