Llama 3.2 represents a yet another advancement in open source large language models. Building upon its predecessors, Llama 3.2 offers enhanced performance and versatility. It is available in multiple parameter sizes, ranging from 1 billion to 405 billion, allowing for scalability across various applications.
The model has been trained on an extensive dataset of approximately 15 trillion tokens, sourced from publicly available materials, which contributes to its robust language understanding and generation capabilities. Notably, Llama 3.2 incorporates architectural improvements such as the SwiGLU activation function, rotary positional embeddings (RoPE), and RMSNorm, which collectively enhance its efficiency and accuracy. It also features an expanded context window of 256k tokens, enabling the model to process and generate content over significantly larger spans of text—ideal for tasks such as legal analysis, research synthesis, and storytelling.
Furthermore, Llama 3.2 can answer questions about images, reason over complex visual data, analyze charts, and interpret maps, making it a powerful tool for multimodal applications. Lastly, Meta AI has released Llama 3.2 under a community license, permitting certain commercial uses and encouraging broader adoption within the research and development community.