Prefill & Decode Separation Trend 2026

Splitting inference into two phases, prefill and decode separation optimizes large language model performance. Prefill processes the prompt in parallel, while decode generates tokens sequentially. By isolating these stages, systems can allocate compute and memory more efficiently, reducing latency and boosting throughput. This architecture benefits AI engineers and enterprises deploying high-traffic chatbots or complex reasoning tasks, enabling faster responses and lower operational costs.