llama.cpp Merged --n-cpu-ffn, Giving Dense Models the Offload Flag That MoE Models Already Had

llama.cpp GitHub, via r/LocalLLaMA·medium signalXBlueskyLinkedInCopy link

PR #26622 by John-194 adds a --n-cpu-ffn option to llama.cpp, mirroring the existing --n-cpu-moe but for dense models: it pushes a user-specified number of FFN sublayers to CPU while attention stays on the GPU. The r/LocalLLaMA thread's practical note is that the previous route was regex matching in -ot style, and for a model you plan to run for months a single flag beats both that and --fit. This is the concrete lever for running dense models on low-VRAM cards.