Anything that can't use mobile GPU (or DSP/TPU for quantized inference) is pretty useless IMO, because it's just not energy efficient enough to be practical in a battery powered device, even if it's fast enough.
Once pytorch is updated to use XNNPACK (being worked on right now) I think it should be fine to use. That plus QNNPACK makes inference quite low on power usage in my (admittedly limited, just integrated XNNPACK) experience.
As a rule, CPU burns at least 5x the energy per FLOP. So no, CPU is not a viable option on mobile if you need to do inference constantly. For "every now and then" cases, sure.