GoKawiilBaseten explains how inference engineers trade off latency, throughput and cost for LLMs
A technical breakdown describes the 'efficient frontier' concept in LLM inference, distinguishing techniques that shift performance along a fixed tradeoff curve—like sacrificing latency for throughput or intelligence for speed—from techniques that expand the frontier itself, creating more overall efficiency. Examples cited include quantization, distillation, pruning, and reasoning-level adjustments, applied in the context of running large agentic coding models such as GLM-5.3 or Kimi K3 with KV cache reuse.