Position: The Physics-Physical Reasoning Interplay is Key for Future Embodied World Models

World modeling represents a critical frontier towards autonomous AI agents capable of capturing environmental dynamics for intelligent decision-making. While current progress scales on massive data corpora, we argue that future world models require combining physics reasoning (understanding the fundamental laws of nature) with physical reasoning (applying these laws to predict observable behaviors and outcomes of intervention). In this paper, we outline the promise and reality as to how frontier models perform in both physics and physical reasoning, then propose a new pathway for future world models and embodied intelligence to internalize the laws of physics to internalize the mechanism of surrounding physical world just like how humans learn to interact with the world in a universally generalizable manner, thereby establishing the foundation for autonomous, efficient and reliable embodied intelligence.