LLM Inference Engineering Techniques Reshape AI Performance Tradeoffs and Push Efficiency Boundaries
LLM inference engineering is reshaping AI performance by splitting techniques into two categories: tradeoff managers like batch sizing and quantization that balance latency against throughput, and frontier-pushers like speculative decoding and kernel optimization that deliver compounding, systemwide efficiency gains applicable to both speed and scale simultaneously.