  We present foundation language models developed to power Apple Intelligence
features, including a ~3 billion parameter model designed to run efficiently on
devices and a large server-based language model designed for Private Cloud
Compute. These models are designed to perform a wide range of tasks
efficiently, accurately, and responsibly. This report describes the model
architecture, the data used to train the model, the training process, how the
models are optimized for inference, and the evaluation results. We highlight
our focus on Responsible AI and how the principles are applied throughout the
model development.
