Granite 4.2 8B
Release in the IBM Granite family · version 4.2 (8B)
Maintained by IBM (Granite Team)1
Granite 4.2 8B is an 8-billion-parameter dense decoder-only language model from IBM with built-in reasoning, selectable thinking, non-thinking, and low-effort modes, and tool calling. It supports a 128K-token context natively; the model card documents extension to 512K.1
- Model hub: Model card (external site: huggingface.co)
- Repository: Granite 4.2 language models repository (external site: github.com)
- Release notes: Technical blog (external site: huggingface.co)
- License: Apache License 2.0 (repository) (external site: github.com)
Availability and license
Overall availability
Weights are downloadable from Hugging Face without a gating agreement; Apache 2.0 terms apply.1
Availability is separate from permission: read the license before using or redistributing.
The Apache 2.0 license is stated in the model card metadata and summary table. IBM's machine-readable training-data disclosures are published separately under CDLA Permissive v2.13
Model-disclosure tier
The model parameters for this release can be downloaded by the public. License terms may still restrict use, redistribution, or commercial use.
Public materials checklist
| Item | Status | Notes and evidence |
|---|---|---|
| WeightsCan the general public download the model parameters for this release? | Public | Safetensors weights in bfloat16 are published in the Hugging Face repository.1 |
| Inference codeIs code for running the model published? | Public | The model card documents running the model with Hugging Face Transformers, vLLM, and SGLang, and the repository includes a chat template and a reasoning-parser plugin.1 |
| Training codeIs the code used to train the model published? | Unknown | The model card names NVIDIA's NeMo RL and NeMo Gym for reinforcement learning. This review did not find IBM's own training code or configurations for this release. |
| Training-data informationPublic = the training data itself can be obtained. Partial = composition or sources are documented without full access. | Partial | IBM's disclosure file lists pre-training and post-training datasets by category, with URLs for most of them. Several entries are internal, acquired, or synthetic datasets that are not publicly obtainable.4 |
| Training recipeAre the training configuration and procedure documented in enough detail to follow? | Partial | The technical blog documents the post-training procedure, including the SFT data mixture and configuration (learning rate, batch size, warm-up, epochs) and per-stage GRPO reinforcement-learning and RLHF settings. Pre-training of the Granite 4.1 base model is referred to a separate Granite 4.1 blog that this review did not assess, and no training code or configuration files were found.15 |
| Evaluation materialsPublic = evaluation code or prompts that let others re-run the evaluations are published. Partial = results only. | Partial | The model card publishes a results table and states that evaluations use a framework based on NVIDIA's NeMo Evaluator SDK. This review did not find IBM's evaluation configurations or prompts.1 |
What it is useful for
The model card lists reasoning, code generation, tool calling, agentic workflows, and multilingual dialog in 12 tested languages.1
Run and use notes
- The model card documents serving with vLLM (v0.20 or later for the bundled granite_thinking_parser) and with SGLang (v0.5.18 or later), and loading with Hugging Face Transformers. It recommends temperature 1.0 and top_p 0.95 for all modes.1
- IBM also publishes quantized variants of this model in the ibm-granite Hugging Face organization, including GGUF, FP8, MXFP4, NVFP4, and MLX builds.6
Organization context
Provenance and derivatives
Post-trained by IBM from its own Granite 4.1 8B Base model, using supervised fine-tuning, reinforcement learning, and RLHF.15
- Derived from: Granite 4.1 8B Base (external site: huggingface.co) — IBM base model; pre-trained from scratch per the Granite 4.2 technical blog.
Other releases in the IBM Granite family
- Granite 4.2 30BModel-disclosure tier (USASI rubric v0.1): Open-weight
- Granite 4.2 3BModel-disclosure tier (USASI rubric v0.1): Open-weight
In the news
IBM releases Granite 4.2 language models in 3B, 8B, and 30B sizes under Apache 2.0
IBM released Granite 4.2 on August 25, 2026: dense, decoder-only language models with built-in reasoning in 3B, 8B, and 30B sizes, post-trained from IBM's own Granite 4.1 base models. The weights are published on Hugging Face under the Apache 2.0 license. The catalog has a release record for each size under the Granite family.
U.S. eligibility
Sources
This listing is not an endorsement, a safety assessment, or a federal approval.