Photo by Digital Buggu on Pexels

The debate over the best approach for AI workflow automation is heating up, pitting private, locally-run large language models (LLMs) against their cloud-based counterparts. Platforms like Ollama offer local processing, raising key considerations around data privacy and control. Meanwhile, cloud giants like OpenAI and Google (with Gemini) provide scalable infrastructure and pre-trained models. The AI community is actively weighing the tradeoffs, focusing on speed, cost-effectiveness, and the adaptability of each approach for seamless integration with existing automation tools. This discussion, highlighted in a recent Reddit thread ([https://old.reddit.com/r/artificial/comments/1n7cukx/private_llms_vs_cloud_which_do_you_prefer_for_ai/]), underscores the evolving landscape of AI adoption in practical applications.