How do you design cost-performance tradeoffs in LLM inference systems?

Cost-performance tradeoffs are managed using model tiering, caching, token limits, and adaptive routing.

LLMOps systems must balance cost (token usage, GPU time) and performance (latency, accuracy). This is achieved using multiple model tiers, semantic caching, early exit strategies, and dynamic routing. Systems also enforce token budgets per request and per user to prevent runaway costs.