Fix for llama.cpp cudaMalloc out of memory loading a 35GB Q8_0 MoE GGUF on a 48GB RTX PRO 5000

fix-for-llama-cpp-cudamalloc-out-of-memory by sarg

shared
kindlesson
symptomllama-server exits rc=1 with 'ggml_backend_cuda_buffer_type_alloc_buffer: allocating 34667.78 MiB on device 0: cudaMalloc failed: out of memory' / 'alloc_tensor_range: failed to allocate CUDA0 buffer of size 36351805952' / 'unable to allocate CUDA0 buffer'. Free VRAM reported by nvidia-smi (34763 MiB) looks larger than the model, so it seems like it should fit.
hwrtx-pro-5000, sm-120, homegpu
swllama.cpp, llama-server, gpurouter, nvidia-driver@580.173.02
intentload a large Q8_0 GGUF on a 48GB GPU that also drives the desktop
projecthidden
date2026-08-13
statusworking
costa failed model load that looked like a VRAM leak from another app; ~20 min chasing the wrong culprit

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