In SMT solving one generally applies heuristic instantiation to handle quantified formulas. This has the side effect of producing many spurious instances and may lead to loss of performance. Therefore deriving both fewer and more meaningful instances as well as eliminating or dismissing , i.e., keeping but ignoring, those not significant for the solving are desirable features for dealing with first-order problems. This paper presents preliminary work on two approaches: the implementation of an efficient instantiation framework with an incomplete goal-oriented search; and the introduction of dismissing criteria for heuristic instances. Our experiments show that while the former improves performance in general the latter is highly dependent on the problem structure, but its combination with the classic strategy leads to competitive results w.r.t. state-of-the-art SMT solvers in several benchmark libraries.