Four changes that shrink the diffusion LM compute gap from 16x
volokuleshov · x · 2026-10-16
The author explains the 16x figure came from scoring a full-sequence decoder-only masked model with its ELBO. Swapping in exact likelihood (DUEL), max-confidence samplers, block diffusion at practical block sizes (4-32), and an encoder-decoder (E2D2) each shrinks the compute gap vs autoregressive models.
Related event: Cornell-Amazon Study Cuts Diffusion LM Compute Gap from 16x to 3-8x(5 posts)→
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