<p>The review aimed to advance both the understanding and practical application of spintronic devices. Through meticulous classification into system-level and device-level approaches, we spotlight design constraints in real-world scenarios. At the system-level domain, exploration extends to broader applications in cache and main memory, addressing issues related to write performance, reliability, and power constraints from a spintronic perspective. Furthermore, the survey meticulously explores device characterization aligned with specific application requirements, aiming to craft spintronic devices uniquely tailored to diverse application needs. It examines trade-offs inherent in various characterization and modeling strategies, providing insights and advancements to the field. Motivated by the impact of spintronic devices in cutting-edge domains like stochastic computing, security, and Artificial Neural Networks, the survey explores spintronics applications’ diverse and evolving landscape. It emphasizes application-centric characterization, dissecting trade-offs to tailor spintronic devices for specific needs and contributing insights that can shape the future of computing. This work offers guidance for technology adoption in specific domains. The work provides nuanced insights to inspire further advancements in spintronics and contribute to the evolution of these transformative technologies.</p>