NMDA-type ionotropic glutamate receptors are critically involved in excitatory neurotransmission and their dysfunction is implicated in many brain disorders. Allosteric modulators with selectivity for specific NMDA receptor subtypes are therefore attractive as therapeutic agents, and sustained drug discovery efforts have resulted in a wide range of new allosteric modulators. However, evaluation of allosteric NMDA receptor modulators is limited by the lack of operational ligand-receptor models to describe modulator binding dissociation constants (KB) and effects on agonist binding affinity (α) and efficacy (β). Here, we describe a pharmacological equilibrium model that encapsulates activation and modulation of NMDA receptors, and we apply this model to afford deeper understanding of GluN2A-selective negative allosteric modulators (NAMs), TCN-201, MPX-004, and MPX-007. We exploit slow NAM unbinding to examine receptors at hemi-equilibrium when fully occupied by agonists and modulators to demonstrate that TCN-201 display weaker binding and negative modulation of glycine binding affinity (KB = 42 nM, α = 0.0032) compared to MPX-004 (KB = 9.3 nM, α = 0.0018) and MPX-007 (KB = 1.1 nM, α = 0.00053). MPX-004 increases agonist efficacy (β = 1.19), whereas TCN-201 (β = 0.76) and MPX-007 (β = 0.82) reduce agonist efficacy. These values describing allosteric modulation of diheteromeric GluN1/2A receptors with two modulator binding sites are unchanged in triheteromeric GluN1/2A/2B receptors with a single binding site. This evaluation of NMDA receptor modulation reveals differences between ligand analogs that shape their utility as pharmacological tool compounds and facilitates the design of new modulators with therapeutic potential. Significance Statement Detailed understanding of allosteric NMDA receptor modulation requires pharmacological methods to quantify modulator binding affinity and the strengths of modulation of agonist binding and efficacy. We describe a generic ligand-receptor model for allosteric NMDA receptor modulation and use this model for the characterization of GluN2A-selective NAMs. The model enables quantitative evaluation of a broad range of NMDA receptor modulators and provides opportunities to optimize these modulators by embellishing the interpretation of their structure-activity relationships.