16 + 128 = 144 GB: does “four-hands” inference between laptop and GX10 make sense? The idea I have two machines that do LLM inference: the laptop, with a GPU that has 16 GB of VRAM: fast, hungry for bandwidth (ballpark: 700–1000 GB/s depending on the chip), but with little space; the GX10 (Grace Blackwell GB10 SoC), with 128 GB of unified memory: lots of space, but LPDDR5x bandwidth of about 273 GB/s. Today it runs llama.cpp serving Qwen locally. The temptation is obvious: what if we merged the two memories into a single ~140 GB “super GPU”? The GX10 fits 100+ GB quantized models; the laptop doesn’t. But is the sum of capacities really worth the sum of performances? ...