Pipeline parallelism in llama.cpp may be wasting your VRAM

Pipeline parallelism in llama.cpp distributes model layers across multiple GPUs, with each GPU holding a contiguous slice of layers . However, the Reddit post likely discusses inefficiencies in how pipeline parallelism allocates VRAM across GPUs, potentially causing underutilization or excessive memory overhead compared to alternative multi-GPU approaches like tensor parallelism. For multi-GPU setups, alternatives like vLLM or ExLlamaV2 with tensor parallelism may be more appropriate than llama.cpp's pipeline parallelism approach .

Source: r/LocalLLaMA | 2026-06-08