Easy head math: parameter count times parameter size plus 20-40% for inference slop space. Anywhere from 8-40GB of vram required depending on quantization levels being used.
They did quantization aware training for fp8 so you won't get any benefits from using more than 12GB of RAM for the parameters. What you might be using more RAM is the much bigger context window.
