Sora-2

Sora 2 is designed as a flagship multimedia generation system that prioritizes physical consistency and narrative control. By moving beyond the surreal, glitch-prone outputs of earlier iterations, the architecture focuses on modeling complex dynamics such as buoyancy, rigidity, and the natural movement of fabrics. The design intent is to transform video generation from a simple visual task into a sophisticated world simulation, enabling the creation of multi-shot sequences and cinematic scenes that maintain structural integrity over extended durations.

The model lineage is rooted in the scaling of pre-training compute, building upon the foundational behaviors of object permanence observed in earlier research. The development team has prioritized mastering both pre-training and post-training on large-scale video data, a domain they characterize as being in its infancy compared to language models. While the supplied evidence does not detail specific parameter counts or the exact post-training methods like SFT or GRPO, it highlights a deliberate shift toward training models that possess a deep, inherent understanding of physical world interactions.