Hyperbolic space has emerged as a powerful framework for representing complex networks due to its ability to capture hierarchical and scale-free structures. In this work, we perform a comparative analysis of three representative hyperbolic embedding methods—Poincaré, Lorentz, and D-Mercator—on a real-world dataset: the Autonomous System (AS) Internet topology.