The goal of this work is to give precise bounds on the counting complexity of a family of generalized coloring problems (list homomorphisms) on bounded-treewidth graphs. Given graphs
G, H, and lists
L(
v) ⊆
V(
H) for every
v ∊
V(
G), a
list homomorphism is a function
f :
V(G) →
V(H) that preserves the edges (i.e.,
uv ∊
E(G) implies
f(u)f(v) ∊
E(H)) and respects the lists (i.e.,
f(v) ∊
L(v)). Standard techniques show that if
G is given with a tree decomposition of width
t, then the number of list homomorphisms can be counted in time

. Our main result is determining, for every fixed graph
H, how much the base
|V(
H)
| in the running time can be improved. For a connected graph
H we define irr(
H) in the following way: if
H has a loop or is nonbipartite, then irr(
H) is the maximum size of a set
S ⊆
V(
H) where any two vertices have different neighborhoods; if
H is bipartite, then irr(
H) is the maximum size of such a set that is fully in one of the bipartition classes. For disconnected
H, we define irr(
H) as the maximum of irr(
C) over every connected component
C of
H. It follows from earlier results that if irr(
H) = 1, then the problem of counting list homomorphisms to
H is polynomial-time solvable, and otherwise it is #P-hard. We show that, for every fixed graph
H, the number of list homomorphisms from (
G, L) to
HThereby we give a precise and complete complexity classification featuring matching upper and lower bounds for all target graphs with or without loops.