Granite3.2 2B Instruct - Details

Granite3.2 2B Instruct, developed by IBM Granite, is a large language model with 2B parameters. It operates under the Apache License 2.0 and is designed to enhance reasoning capabilities while maintaining controllability and improving multimodal understanding.

Granite3.2 2B Instruct is a 2-billion-parameter model designed to enhance reasoning capabilities while maintaining controllability. Built on Granite-3.1-2B-Instruct, it leverages open-source datasets and internally generated synthetic data for training. The model supports multilingual dialog, long-document summarization, and code-related tasks. It operates under the Apache License 2.0, ensuring permissive usage. Developed by IBM Granite, it emphasizes improved multimodal understanding and structured thinking processes.

Granite3.2 2B Instruct has 2B parameters, placing it in the small to mid-scale range of open-source LLMs, which typically balances efficiency and performance for tasks requiring moderate complexity. Its 4K context length falls into the short-context category, making it well-suited for concise tasks but less effective for handling extremely long documents. The 2B parameter size ensures faster inference and lower resource demands, ideal for applications prioritizing speed and simplicity, while the 4K context length limits its ability to process extended texts compared to models with longer contexts.

• Parameter Size: 2B
• Context Length: 4K

Granite3.2 2B Instruct is a versatile model with 2B parameters and 4K context length, designed for general instruction-following tasks, AI assistants for business applications, and multilingual dialog systems. Its multilingual capabilities support languages like Chinese, Italian, Korean, Spanish, French, Portuguese, Czech, English, Dutch, Arabic, Japanese, and German, making it a possible tool for cross-lingual interactions. Possible uses could include automating routine tasks, enhancing customer service through dialog systems, or supporting business workflows with structured guidance. However, these possible applications require thorough testing to ensure alignment with specific needs. The model’s design emphasizes controllability and reasoning, which might make it possible to adapt to scenarios requiring nuanced understanding or task-specific customization. Still, further investigation is necessary to confirm its effectiveness in real-world settings.

• general instruction-following tasks
• AI assistants for business applications
• multilingual dialog systems

Granite3.2 2B Instruct is a 2B-parameter model with a 4K context length and multilingual support, making it a possible candidate for applications requiring structured reasoning and cross-lingual adaptability. Possible uses could include automating repetitive tasks through instruction-following workflows, enhancing business operations with AI-driven assistants, or supporting multilingual dialog systems for global communication. Its design also could enable tailored solutions for educational tools or content creation, though these possible applications require careful validation. The model’s focus on controllability and reasoning might make it suitable for scenarios needing nuanced interaction, but each possible use case must be thoroughly evaluated to ensure alignment with specific requirements.

• general instruction-following tasks
• AI assistants for business applications
• multilingual dialog systems
• content creation or educational tools

Granite3.2 2B Instruct’s medium q4 version, optimized for a balance between precision and performance, likely requires a GPU with at least 8GB VRAM and 32GB system memory to run efficiently. This configuration ensures smoother inference while maintaining reasonable accuracy. The fp16, q4, and q8 quantized versions offer varying trade-offs between speed, memory usage, and output quality, allowing users to select the most suitable option based on their hardware capabilities.

• fp16, q4, q8

Granite3.2 2B Instruct is a 2B-parameter large language model developed by IBM Granite, designed to enhance reasoning capabilities while maintaining controllability and improving multimodal understanding. It operates under the Apache License 2.0, making it accessible for various applications, and supports multilingual dialog, long-document summarization, and code-related tasks.

Huggingface Model Page
Ollama Model Page