ABot-PhysWorld is a 14B Diffusion Transformer model designed for interactive world modeling in robotics that generates visually realistic, physically plausible, and action-controllable videos. The model addresses common physical implausibility issues like object penetration and anti-gravity motion by using a novel DPO-based post-training framework with decoupled discriminators trained on a curated dataset of three million physics-aware manipulation clips. A parallel context block enables precise spatial action injection for cross-embodiment robot control. To evaluate generalization, the system introduces EZSbench, the first training-independent embodied zero-shot benchmark combining real and synthetic unseen robot-task-scene combinations.