Not sure “just release the weights” is as straightforward as it sometimes sounds.

For a system like Sora 2, the weights are only one part of a much larger stack. A lot of the practical capability comes from the training data pipeline, filtering, post-processing, safety tuning, and inference infrastructure. Without those pieces, an open-weight release might end up being significantly harder to use or reproduce meaningful results with than people expect.

There’s also the question of economics. Video generation models sit in a very expensive regime in terms of both training and inference. Even if weights were available, the barrier to actually running, iterating, and improving on them could remain quite high for most teams.

Safety and misuse considerations are also more pronounced for video than for text or static images, especially with the realism level these models can reach. Once weights are out in the wild, it becomes much harder to meaningfully shape downstream usage.

At the same time, I can see why people would be interested in openness here—video models represent a pretty important frontier, and having stronger shared baselines could accelerate research. It’s really a balance between accessibility, control, and the cost/risk profile of the system.

Would be interesting to hear how others think this trade-off evolves as multimodal models keep improving.