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- --flash-attn on|off|auto (mtmd's flash_attn_type): flash attention keeps K and V in FP16. On the NVFP4 fork the vision tower's output was 11.2% off with it on the GPU; FP32 attention (CPU) 0.1%. - On the CPU a CUDA build keeps the GPU unseen (CUDA_VISIBLE_DEVICES=-1 before the runtime starts): it otherwise opened a context there, 0.4-0.7 GB of VRAM the expert cache loses. - On the CPU without --threads: one thread per core (mtmd's default is 4); no warm-up encode (~6 s of start). - serve/server.py: relative exe/mmproj/model paths in the vision config are the config's cwd's, as the engine's are.