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The rapid advancement of quantum computing poses a fundamental threat to classical public-key cryptographic systems, necessitating the transition to post-quantum cryp-tography (PQC). While significant progress has been made in the standardization of quantum-resistant algorithms, their practical deployment in heterogeneous environ-ments—particularly resource-constrained Internet of Things (IoT) devices—remains a critical challenge. This study presents a comprehensive experimental evaluation of four NIST-standardized PQC algorithms: CRYSTALS-Kyber (ML-KEM), CRYS-TALS-Dilithium (ML-DSA), FALCON, and SPHINCS+. The analysis is conducted across two distinctly different hardware platforms: a high-performance x86-64 system (AMD Ryzen 7 5700U) and a resource-constrained embedded microcontroller (ESP32-WROOM). Implementations were developed in C, Go, and Python to assess the influence of programming environments on algorithmic efficiency. The evaluation focuses on key performance indicators, including computational la-tency, memory consumption, communication overhead, and temporal determinism, based on extensive benchmarking over 1,000 iterations. Experimental results demon-strate significant trade-offs between security level, execution performance, and re-source utilization. Lattice-based schemes such as Kyber and Falcon exhibit superior ef-ficiency and scalability on embedded platforms, while Dilithium encounters stability limitations due to memory constraints. In contrast, SPHINCS+ provides strong security guarantees and architectural robustness at the cost of higher computational overhead. The findings highlight the critical role of hardware-specific optimizations and soft-ware design choices in enabling practical PQC deployment. This work provides ac-tionable insights for selecting and tuning post-quantum algorithms in real-world sce-narios, supporting the secure migration of IoT and distributed systems toward quan-tum-resilient infrastructures.