Artificial intelligence model selection compares available models against the needs of an application or request. Relevant factors include task capability, tool support, accuracy, safety, context capacity, price, speed, availability and provider constraints.
There is rarely one best model across every dimension. Selection can happen during system design or dynamically for each request, and the result should be verified against representative workloads rather than assumed from reputation alone.
