The study compares the inference times of HuggingFace and MonsterDeploy, with MonsterDeploy achieving 50x faster inference than HuggingFace. The primary goal is to evaluate the inference performance using the Meta-Llama-3.1-8B text-generation model on both platforms. Deployment through MonsterAPI significantly outperforms deployment from HuggingFace, offering up to 50x faster inference due to techniques like Dynamic Batching, Quantization, and Model Compilation. Various optimization techniques such as Flash Attention 2 for Memory Management and CUDA Optimization for NVIDIA GPUs are explored to boost AI model efficiency. The study concludes that optimizing inference time is crucial for businesses relying on AI, enhancing user experience while reducing costs and improving performance.