Human brain has very likely 10^15 synapses so these models are still behind at least 3 orders of magnitude. To put in perspective, if you want to simulate “network” of human brain, you probably need an entire data center worth of GPUs.
That is assuming you restrict yourself to a radical simplified model of each neuron. The actual biochemical processes going on in a single synaptic density go way beyond something that could be represented by a scalar weight that assemble into a linear transformation. Instead we are talking about 10^15 dynamical systems. This then still neglects most of the time /spatial extended nature of neurons, the fact that calcium stores in the endoplasmatic reticulum play a role etc. Some of this might be only relevant to learning, but non-linear dendritic processing is believed to be relevant for example for inference aswell.