A support chatbot should not choose an LLM API from a leaderboard screenshot. The useful choice is the API and runtime policy that keep answer quality above your review threshold while meeting the response-time budget and retaining only the conversation data you can defend.

Short answer: define two paths before comparing providers: a fast conversational path for ordinary support turns and a slower review path for code changes that need structured findings. Measure both with the same redacted ticket set. Route by task, cap the context, validate the output, and delete transcript material on a schedule. The best API is the one that passes those tests for your traffic and failure policy, not the one with the most impressive general benchmark.

This matters in customer support because a plausible answer is an operational failure if it invents a fix, leaks a customer secret, or delays an agent waiting on a streaming response.…