Implemented a huge list of fixes

• Lazy page-ID tensor resolution after quantization

• Storage-alias-aware VRAM accounting

• Correct affine INT4 partial-group quantization

• KV sequence continuity checks

• Free-page geometry invalidation

• Canonical LM-head bias and final-softcap handling

• Certified shortlist logic with exact fallback

• Gemma-style attention scaling/softcap fixes

• Removal of hot-path CUDA scalar tensor allocations

• Device normalization for “cuda”, “cuda:N”, and torch.device

• Profile separation has been reconnected and different profiles select different kernels.

• Paged KV storage exists through SlabbedKVCache.

• A prior paged-attention slowdown was caused by GPU synchronization from .item() calls in SlabbedKVCache.append(), not by paged addressing itself.

• Logical page ownership is now tracked CPU-side to avoid those synchronizations.

• Paged attention has measured approximately:

  • Materialized: 55.1 tok/s
  • Paged: 57.5 tok/s
    on a relevant smaller models