IBM has released Granite 3.2, an update to its Granite large language model (LLM) series, designed for business use with smaller, more efficient AI solutions.
”The next era of AI is about efficiency, integration, and real-world impact – where enterprises can achieve powerful outcomes without excessive spending on compute,” said Sriram Raghavan, vice president at IBM Research (AI).
“IBM’s latest Granite developments focus on open solutions and demonstrate another step forward in making AI more accessible, cost-effective, and valuable for modern enterprises,” he added.
The update introduces a new vision language model (VLM) for document understanding. It performs on par or above larger models like Llama 3.2 11B and Pixtral 12B on benchmarks like DocVQA and OCRBench.
It was trained with IBM’s open-source Docling toolkit, processing 85 million PDFs and creating 26 million synthetic question-answer pairs to improve document-heavy workflows.
Granite 3.2 also includes models with chain-of-thought reasoning, improving tasks like following instructions and solving math problems (e.g., AIME2024 and MATH500). This feature can be turned on or off for better efficiency. The 8B model uses advanced techniques to match or outperform larger models.
The update also includes Granite Guardian safety models, which are 30% smaller but still maintain strong performance. These models now feature a tool for verbalising confidence and improving safety monitoring with more detailed risk assessments.
Additionally, IBM has updated its TinyTimeMixers (TTM) models, which now have fewer than 10 million parameters. These are designed for long-term forecasting and are useful in financial analysis, supply chain forecasting, and retail inventory planning.
Granite 3.2 models are available on platforms like Hugging Face and IBM Watsonx.ai under the Apache 2.0 license.
