We consider the dynamic dictionary problem for multisets. Given an upper bound $n$ on the total cardinality of the multiset (i.e., including multiplicities) at any point in time, the goal is to design a data structure that supports multiplicity queries and allows insertions and deletions to the multiset (i.e., the dynamic setting). The data structure must be space-efficient (the space is $1+o(1)$ times the information-theoretic lower bound) and support all operations in constant time with high probability. In this paper, we present the first dynamic dictionary for multisets that achieves these performance guarantees. This answers an open problem of Arbitman, Naor and Segev (FOCS 2010). The previously best-known construction of Pagh, Pagh and Rao (SODA 2005) supports membership in constant time, multiplicity queries in $O(\log n)$ time in the worst case, and insertions and deletions in constant expected amortized time. The main technical component of our solution is a strategy for efficiently storing variable-length binary counters using weighted balls-into-bins experiments in which balls have logarithmic weights. We also obtain a counting filter that approximates multiplicity queries with a one sided error, using the reduction of Carter et al. (STOC 1978). Counting filters have received significant attention over the years due to their applicability in practice.We present the first counting filter with constant time operations.