granite-4.2

About

What granite-4.2 is

Granite-4.2-8B [](https://huggingface.co/collections/ibm-granite/granite-42-language-models) [](https://huggingface.co/blog/ibm-granite/granite-4-2) [](https://github.com/ibm-granite/granite-4.2-language-models) [](https://www.apache.org/licenses/LICENSE-2.0) Model Summary Model Overview What is IBM Granite? Granite is a family of open-source large language models developed by IBM, designed for enterprise and research use. Granite models are built to be versatile, safe, and efficient — covering a range of sizes and capabilities from compact edge-deployable models to large-scale reasoning systems. All Granite models are released under the Apache 2.0 license, enabling unrestricted commercial and academic use. The Granite 4.2 generation introduces native reasoning (thinking) capabilities, allowing models to perform step-by-step chain-of-thought reasoning before producing final answers. This significantly improves performance on complex math, coding, multi-step logic, and agentic tool-calling tasks. Description Granite-4.2-8B is the mid-size reasoning model in the Granite 4.2 family. It delivers strong performance on reasoning-intensive tasks by leveraging built-in <think...</think chain-of-thought. It supports flexible thinking modes — full thinking (default), non-thinking, and low-effort — allowing users to balance depth vs. latency on a per-query basis. Key capabilities: - Built-in Reasoning: Native chain-of-thought that significantly improves performance on math, coding, and complex multi-step problems. - Flexible Thinking Modes: Seamlessly switch between full thinking, non-thinking, and low-effort modes within a single model. - Reasoning-Augmented Tool Calling: The model reasons about which tools to invoke and why, producing more accurate function calls. - 512K Context Window: Supports long documents, multi-turn conversations, and complex agentic workflows. - Apache 2.0 Licensed: Fully open for commercial and research use. Model Design Granite-4.2-8B is built on a decoder-only dense transformer architecture with the following core components: Attention: Grouped Query Attention (GQA) with 32 attention heads and 8 KV heads Position Embedding: Rotary Position Embe

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

How it works

How language models work

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys granite-4-2 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (granite-4-2 below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/chat/completions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"granite-4-2","messages":[{"role":"user","content":"Hello"}]}'

Details

Languages, data & research

Licence

Open weights

Sources

Weights & code

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