The $G(n,p)$ random graph model creates graphs with $n$ vertices and each possible edge exists independently with probability $p\in (0,1)$.
Much is known about the (expected) size of a largest clique in these graphs, and it has been shown that the expected number of maximal cliques of size $d$ is
$${n\choose d} p^{d \choose 2} (1-p^d)^{n-d}.$$
To find the expected number of maximal cliques, just sum over all values of $d$ to get
$$\mu (G(n,p)) := \sum_{d=1}^n {n\choose d} p^{d \choose 2} (1-p^d)^{n-d}.$$
I'm interested in the asymptotic growth of $\mu (G(n,p))$ as a function $n$. For example, if $p$ is fixed, does $\mu$ grow polynomially in $n$?
A quasi-polynomial bound is not hard to show. Since the expected maximum clique size is roughly $\omega(G(n,p))\approx\frac{2 \log n}{\log(1/p)}$, the number of cliques (not necessarily maximal) is $O( {n \choose \omega(G(n,p))+1}) = O(n^{\omega(G(n,p))+1})=O(n^{\frac{2 \log n}{\log(1/p)}+1})$.