Quantum simulations of the Lipkin-Meshkov-Glick model are being benchmarked against large tensor networks, a classical method, to assess their performance in solving real-world problems. The Density Matrix Renormalization Group algorithm is used to compute ground state energies of the LMG model, providing a comparative benchmark against noisy intermediate-scale quantum algorithms. This research aims to evaluate the effectiveness of quantum computing in solving complex problems, particularly in scenarios where classical methods are competitive. The LMG model is a suitable test case due to its complex quantum behavior, making it an ideal candidate for benchmarking quantum simulations. The results of this study will help determine the viability of quantum computing in various applications, including cryptography, where quantum developments are challenging existing assumptions1. This matters to practitioners because it sheds light on the current capabilities and limitations of quantum computing, informing decisions on its adoption and development for real-world problem-solving.