Beyond Next-Token Prediction: A Performance Characterization of Diffusion versus Autoregressive Language Models

In 30 Sekunden

Was passiert ist

Apple researchers compared diffusion language models to autoregressive models, finding diffusion models achieve higher arithmetic intensity but struggle with longer contexts.

Warum es zählt

Engineers optimizing inference performance need to understand when parallel decoding helps versus when sequential generation remains superior for their workloads.

Achtung

Diffusion models require reducing sampling steps to match autoregressive latency, and autoregressive models still outperform on batched inference throughput.