# Granite 4.2 LLMs: How They're Built

DevFeed: [Granite 4.2 LLMs: How They're Built](<https://devfeed.tech/articles/granite-4-2-llms-how-they-re-built-7257.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/ibm-granite/granite-4-2>)

Author: Yousaf Shah; Swanand Kadhe; Riddhiman Moulick; Ashish Sunil Agrawal; Santosh Borse

Published: 2026-08-25T15:14:14Z

Content type: article

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [Language models](<https://devfeed.tech/topics/language-models.md>), [AI Chat](<https://devfeed.tech/topics/ai-chat.md>), [AI-assisted coding](<https://devfeed.tech/topics/ai-assisted-coding.md>), [releases](<https://devfeed.tech/topics/releases.md>)

Tags: [agentic](<https://devfeed.tech/tags/agentic.md>), [agents](<https://devfeed.tech/tags/agents.md>), [apache](<https://devfeed.tech/tags/apache.md>), [chain-of-thought](<https://devfeed.tech/tags/chain-of-thought.md>), [code](<https://devfeed.tech/tags/code.md>), [fine-tuning](<https://devfeed.tech/tags/fine-tuning.md>), [grouped-query-attention](<https://devfeed.tech/tags/grouped-query-attention.md>), [ibm](<https://devfeed.tech/tags/ibm.md>), [llms](<https://devfeed.tech/tags/llms.md>), [models](<https://devfeed.tech/tags/models.md>), [post-training](<https://devfeed.tech/tags/post-training.md>), [reasoning](<https://devfeed.tech/tags/reasoning.md>), [reinforcement-learning](<https://devfeed.tech/tags/reinforcement-learning.md>), [sglang](<https://devfeed.tech/tags/sglang.md>), [tool](<https://devfeed.tech/tags/tool.md>), [training](<https://devfeed.tech/tags/training.md>), [transformer-architecture](<https://devfeed.tech/tags/transformer-architecture.md>), [vllm](<https://devfeed.tech/tags/vllm.md>)

## AI overview

Granite 4.2 is a family of 3B, 8B, and 30B dense decoder-only reasoning language models. The article covers their training pipeline, thinking modes, native tool calling, and agentic reinforcement learning for the 8B and 30B models.

## Source excerpt

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. These models are post-trained from Granite-4.1 base models. Granite-4.1 base models were 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...