Pax is a framework built on JAX for configuring and running machine learning experiments at scale. It provides advanced parallelization capabilities and has achieved industry-leading model flop utilization rates. The framework is particularly oriented toward training large language models as evidenced by topics like GPT, LLM, and large-language-models, and supports distributed training across Google Cloud TPU infrastructure.