Granite-3.2-8B-Instruct-Preview
| Property | Value |
|---|---|
| Developer | IBM Granite Team |
| Release Date | February 7th, 2025 |
| License | Apache 2.0 |
| Model Size | 8B parameters |
| Documentation | Granite Docs |
What is granite-3.2-8b-instruct-preview?
Granite-3.2-8B-Instruct-Preview is an advanced language model developed by IBM that builds upon its predecessor, Granite-3.1-8B-Instruct. This model stands out for its enhanced reasoning capabilities and controllable thinking feature, making it particularly suitable for complex tasks requiring careful analysis. The model supports 12 languages and has been trained using a combination of permissively licensed open-source datasets and internally generated synthetic data specifically designed for reasoning tasks.
Implementation Details
The model is trained on IBM's Blue Vela supercomputing cluster using NVIDIA H100 GPUs, enabling efficient large-scale training. It implements a novel approach to controllable thinking through its API, allowing developers to toggle the thinking capability based on task requirements. The model shows significant improvements in benchmark performance, particularly in reasoning tasks like ArenaHard (55.23%) and Alpaca-Eval-2 (61.16%).
- Long-context processing capabilities
- Controllable thinking mechanism
- Multi-lingual support across 12 languages
- Built on advanced GPU infrastructure
Core Capabilities
- Enhanced reasoning and thinking processes
- Text summarization and classification
- Question-answering and information extraction
- Retrieval Augmented Generation (RAG)
- Code-related tasks and function calling
- Long document processing and summarization
- Multi-lingual dialogue support
Frequently Asked Questions
Q: What makes this model unique?
The model's distinguishing feature is its controllable thinking capability, allowing developers to explicitly enable or disable the reasoning process based on task requirements. This, combined with its strong performance on reasoning benchmarks and support for multiple languages, makes it particularly versatile for various applications.
Q: What are the recommended use cases?
The model is well-suited for business applications requiring complex reasoning, long-context processing, and multilingual support. Specific use cases include document analysis, meeting summarization, complex question-answering, and code-related tasks. It's particularly effective when integrated into AI assistants requiring thoughtful, structured responses.
