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The choice between a self-hosted LLM and a public API is one of the most critical architectural decisions teams face when building AI products. Both options provide access to language models that can power chatbots, analysis tools, automation systems, and internal assistants. But in production environments, the difference goes far beyond the possibility of generating answers. The choice affects cost structure, latency, data control, security, maintenance complexity, team skil

Machine Learning model deployment is a complex process that requires the completion of a long queue of steps. In the case of the...