Cosmos Predict

Cosmos Predict complements Cosmos perception and reasoning by modeling the future state of a scene. From a short history of images or video—optionally paired with control inputs—it generates action-conditioned rollouts of likely next frames, 2D/3D object trajectories, and higher-level events, along with step-wise confidence scores. The result is a practical “what-if” engine that lets systems compare plans, anticipate outcomes, and choose safer actions.

In practice it’s used for robotics motion planning, grasp and placement forecasting, recovery strategies after failure, and for autonomous driving and industrial vision where anticipating hazards, timing hand-offs, or stress-testing scenarios is critical. Teams also employ it to synthesize sequential data that can pretrain or fine-tune downstream policies.

Cosmos Predict slots beside existing detectors, trackers, and a policy module such as Cosmos Reason or your own planner. It streams predictions for low-latency control loops, integrates with tool or function calling inside agent stacks, and deploys efficiently on NVIDIA GPUs with TensorRT-LLM or NIM, with quantization options to balance speed and fidelity.

Forecasts are probabilistic rather than guarantees, so long-horizon rollouts can drift, and shifts in sensors, lighting, or scene distribution may require adaptation or additional fine-tuning.