  In recent years, talking head generation has become a focal point for
researchers. Considerable effort is being made to refine lip-sync motion,
capture expressive facial expressions, generate natural head poses, and achieve
high video quality. However, no single model has yet achieved equivalence
across all these metrics. This paper aims to animate a 3D face using Jamba, a
hybrid Transformers-Mamba model. Mamba, a pioneering Structured State Space
Model (SSM) architecture, was designed to address the constraints of the
conventional Transformer architecture. Nevertheless, it has several drawbacks.
Jamba merges the advantages of both Transformer and Mamba approaches, providing
a holistic solution. Based on the foundational Jamba block, we present
JambaTalk to enhance motion variety and speed through multimodal integration.
Extensive experiments reveal that our method achieves performance comparable or
superior to state-of-the-art models.
