Transferability of Scale-Contraction Across Formats, Group Sizes, and Multimodal Models

Determine whether the scale-contraction strategy used by H-Scale for NVFP4 quantization with group size 16 transfers effectively to other quantization formats, different group sizes, and multimodal models.

Background

The study evaluates H-Scale only for NVFP4 weight-only quantization with group size 16 and text-only LLMs. H-Scale’s scale-contraction strategy selects smaller neighboring hardware-valid per-group scales when they reduce the Hessian-weighted reconstruction objective, but the paper does not establish whether this behavior generalizes beyond the evaluated NVFP4 configuration. The authors explicitly leave open its transferability to other quantization formats, group sizes, and multimodal architectures.

References

Our study is limited to NVFP4 with $g=16$ and text-only LLMs. Whether the same scale-contraction strategy transfers to other formats, group sizes, or multimodal models is left open.

— H-Scale: Hessian-Guided Scale Refinement for NVFP4 Sub-Byte LLM Inference  (2608.28113 - Yu et al., 28 Aug 2026) in Section 6, “Conclusion, Limitations, and Future Work”