AppleAnalysisAI ModelsAugust 7, 2026

Apple study compares diffusion vs autoregressive language models

Read original source →machinelearning.apple.com

Apple ML Research finds diffusion language models (DLMs) achieve higher arithmetic intensity via parallel token generation, but fail to scale with longer contexts unlike autoregressive models (ARMs). Block-wise decoding decouples arithmetic intensity from sequence length to improve DLM scaling; ARMs retain superior throughput in batched inference.

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