<p>Socially Interactive Agents (SIAs), including physically embodied social robots and virtual agents, are increasingly used in applications involving social interactions, including Motivational Interviewing (MI). This study investigates how physical embodiment and nonverbal behaviors, specifically facial expressions generated by our custom diffusion model, influence user’s perceptions and interaction dynamics within the MI framework. By upgrading the diffusion model from an offline configuration to a real-time architecture, we make live counseling sessions with human participants possible. An experimental design was developed to compare three facial expression generation conditions (model-based, mismatched, and control) and two embodiment modalities (Robot vs. Agent). Verbal behavior was supported by a pre-prompted Mistral Large Language Model (LLM). This design allowed us to evaluates, how aligned facial expressions and physical embodiment influence social presence, attitude perception, social rapport perception, self-disclosure, and the overall quality of MI using objective and subjective measures. Results show that aligned facial expressions or the absence of expressions were perceived more positively than mismatched expressions. We also observe that physical embodiment significantly improves social presence and attitude perception, with the social robot consistently rated higher than the virtual agent. A mediation analysis revealed that social rapport serves as a factor linking attitude perception to the MI quality.</p>