None of the three inequalities you’ve shown hold in general for Hermitian matrices $A$ and $B$.
To demonstrate this, we can look at the case where $A$ and $B$ are $1\times 1$ real matrices (trivially Hermitian), in which case the induced matrix norm reduces to an absolute value. Writing $A=a$ and $B=b$ for $a,b\in \mathbb{R}$, we have $|||iA - B|||=\sqrt {a^2 + b^2 }$. Then, for these $A,B\in \mathbb{R^{1\times 1}}$, we have that
$$ \mathop{\min } (|||A|||, |||B|||)\leq \mathop {\max } (|||A|||, |||B|||)\leq |||iA - B|||$$
and
$$ abs(|||A||| - |||B|||)\leq |||iA - B|||,$$
where the rightmost inequalities are strict for $ab \ne 0.$
We can also use this special case to generate counterexamples to the proposed inequalities for $A,B\in\mathbb{R^{n\times n}}$ with $n>1$ by (for example) setting $a_{11}=a$ and $b_{11}=b$ for $A$ and $B$ with all the other matrix entries set to $0.$
Without further restrictions on $A$ and $B$, you’re unlikely to find a better general upper bound than $|||iA - B|||\leq |||A||| + |||B|||$.