3D Gaussian Splatting (3DGS) is a powerful representation for real-time neural reconstruction and rendering. While existing 3DGS systems rely on rasterization for efficiency, recent work explores ray tracing to enable secondary lighting, highly distorted cameras, and depth-of-field effects. However, compared with rasterization, ray-traced 3DGS introduces three major challenges: (1) the highly non-uniform spatial distribution of massive numbers of Gaussian primitives creates severe load imbalance; (2) neighboring pixels often generate rays with highly similar traversal paths, leading to substantial redundant traversal overhead; and (3) supporting both Gaussian and triangle primitives yields heterogeneous intersection workloads that are not well matched to existing GPU architectures. We present H2-Ray, a hybrid and hierarchical ray tracing architecture for efficient 3D Gaussian rendering. H2-Ray introduces three techniques. Load-Balanced Spatial BVH (LB-SBVH) partitions the scene into uniform grids and uses density-aware representations to convert an imbalanced global workload into balanced local traversal units. Ray-Cluster Path Reuse (RCPR) lets a proxy ray share traversal state with neighboring rays to amortize redundant traversal. The Unified Intersection Engine (UIE) supports mixed Gaussian and triangle intersections through a mode-multiplexed datapath that shares 40% of its floating-point units across both primitive types. Across 8 scenes, H2-Ray achieves a geometric-mean speedup of 3.77x and a maximum speedup of 9.26x over RaySplats on the NVIDIA RTX A5000, combining a cycle-accurate model of the modified RT Core with measured CUDA timings.

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