The llama.cpp project released build b10829, which corrects the gated delta net (GDN) query/key normalization implementation. The change switches the normalization method from using `max` to `rsqrt`, aligning with the definition used by flash-linear-attention.
- GDN q/k normalization now uses `l2norm` as defined by flash-linear-attention: `x * rsqrt(sum(x*x) + eps)`.
- Previously, llama.cpp used `ggml_l2_norm`, which applied a clamp via `max(sqrt(sum(x*x)), eps)` instead of placing epsilon inside the root.
- This fix addresses a misalignment that also affected Hugging Face's transformers library for Qwen3-Next before being corrected in pull request #40842.
- The update ensures consistency with reference implementations where epsilon is included within the square root calculation.
This correction ensures that models using GDN layers, such as those based on flash-linear-attention, behave identically to their reference implementations.