Trained Gaussian-splat scenes no longer need retraining to shrink: post-hoc entropy coding reaches 6.0x on 13 scenes at a 0.03 dB quality change
Trained anchor-based Gaussian-splat scenes stay too large for phones and headsets, and existing post-hoc converters saturate early. This scheme treats a trained model as a read-only artifact, fits a per-scene hash-grid entropy context with per-channel Laplace distributions, and codes attributes into a Morton-ordered, progressively decodable bitstream. Across 13 scenes on three benchmarks, the post-hoc mode averages 6.0x compression at a -0.03 dB quality change and runs unchanged on third-party checkpoints.