Model Sizes and Efficiency: Llama 3.2 offers smaller models (1B and 3B), which are optimized for use on edge devices like mobile phones through techniques like pruning and knowledge distillation. These lightweight models are designed to balance performance with efficiency for on-device applications. Llama 3.1, in comparison, has larger models (up to 405B parameters), which are powerful but require much more computational resources for deployment.

Context Length: Both versions support up to 128,000 tokens of context, allowing for extensive input processing, but Llama 3.2 further optimizes this across both its text and multimodal models.