GPT models, with their advanced conversational capabilities, face challenges in local deployment due to high hardware and memory requirements, with larger models needing over 40 GB of GPU memory. A hybrid cloud approach, combining local and cloud resources, offers an efficient solution by balancing workload management, cost, and scalability while adhering to data compliance standards.