The study compares the inference times of Hugging Face and MonsterDeploy by deploying a model through both platforms. The results show that deployment on MonsterAPI leads to a significant reduction in inference time, with an average time per call being 2.23 seconds, which is 50 times faster than the average time per call on Hugging Face. The study identifies various techniques to boost AI model efficiency, including dynamic batching, model compilation, quantization, Flash Attention 2 for memory management, and CUDA optimization for NVIDIA GPUs. These techniques can significantly reduce inference time, making it crucial for businesses relying on AI to optimize their models.