llama.cpp is designed for partial offloading, the most important part of the model will be loaded into the GPU and the rest on system ram. I run 500B+ models such as DeepSeek/KimiK2.5/GLM-5 without having that much GPU vram.
I have lots of trouble figuring out what the limits are of a system with x amount of vram and y amounts of ram. How do you determine this?
You can spill to RAM in which case you at least want enough for a single active expert but really that's going to tank performance. If you're only "a bit" short of the full model the difference might not be all that large.
These things are memory bandwidth limited so if you check out RAM, VRAM, and PCIe bandwidth what I wrote above should make sense.
Also you should just ask your friendly local LLM these sorts of questions.