NVIDIA Cosmos-H-Dreams: Bringing Real-Time Generative Simulation to Surgical Robotics

Surgical robotics is moving quickly from teleoperation toward increasingly capable vision-language-action policies. But evaluating and training these systems remains difficult. Physical robotic platforms are expensive to operate, experiments are slow to reproduce, and failures can damage instruments or biological material. Conventional simulators provide a safer alternative, but surgical scenes are exceptionally difficult to model: deformable tissue, fine instrument interactions, specular surfaces, sutures, needles, smoke, and occlusions all matter.

World foundation models offer a different path. Instead of manually authoring every object and physical interaction, they learn visual dynamics directly from synchronized video and robot kinematics. NVIDIA's Cosmos-H-Surgical-Simulator demonstrated this approach by generating future surgical video from an initial scene and a sequence of robot actions. It enabled faster-than-physical evaluation and synthetic data generation across the Open-H-Embodiment ecosystem.

Today, we are introducing the next step: Cosmos-H-Dreams , a real-time, action-conditioned generative simulator for surgical robotics. Cosmos-H-Dreams distills the capabilities of Cosmos-H-Surgical-Simulator into a causal, few-step student model and serves it through FlashDreams , NVIDIA's accelerated streaming-inference library. Running on a single NVIDIA RTX PRO 6000 GPU, the result is an interactive environment that a person or a learned policy can control in a closed loop.

To improve stability during long rollouts, the training process progressively increases the teacher's temporal horizon. We start training on a 12-frame horizon and progressively increase this number until 72 frames. At each horizon bump, we initialize the warmed-up model with pretrained weights.

The immediate next step is to evaluate more than visual quality. A useful surgical simulator must respond correctly to actions, preserve instrument and scene structure over long rollouts, and support conclusions that transfer to the physical robot. This motivates a new family of closed-loop benchmarks: tool-tip reach and pose accuracy, gripper-cycle fidelity, idle stability, counterfactual action diversity, long-horizon drift, and agreement between simulated and real policy outcomes.

Further ahead, real-time simulation enables a series of downstream applications such as latency-aware telesurgery, where the world model helps maintain a more stable display; or interactive surgical rehearsal, procedure planning, and intraoperative decision support. Cosmos-H-Dreams is a research and development platform, not a diagnostic system, a replacement for intraoperative imaging, or a controller for a physical surgical robot. Yet it provides a foundation for exploring these possibilities safely.

Cosmos-H-Surgical-Simulator is an action-conditioned world foundation model built on NVIDIA Cosmos-Predict2.5-2B and post-trained on the Open-H-Embodiment dataset. Given a surgical context frame and a future robot trajectory, it generates video showing the likely visual consequences of those actions. This makes it useful for offline policy evaluation and synthetic data generation. A recorded or policy-generated trajectory can be sent to the model, the corresponding rollout can be generated, and the result can be inspected or scored without repeatedly executing the motion on a physical robot.

Cosmos-H-Dreams moves the model into the real-time regime. Starting from the multi-embodiment surgical priors learned by Cosmos-H-Surgical-Simulator, we specialize the model for da Vinci Research Kit (dVRK) tabletop suturing and distill it into a causal student that generates the scene autoregressively. The released model receives an initial RGB frame and a live stream of robot kinematics, then produces the next chunk of frames before continuing with the following action block.

We have also demonstrated the versatility of Cosmos-H-Dreams by collaborating with CMR Surgical and Cambridge Consultants to integrate it with the Versius surgeon controller, enabling real-time operation on the Versius platform.