# Paper Targets Diffusion LLM Inference Bottlenecks on Mobile NPUs

Diffusion language models denoise many tokens in parallel but pay repeated compute per step, and the work addresses that cost for on-device serving.

- Published: 2026-06-15T07:00:34.492Z
- Canonical: https://polylog.news/ai/2026-06-15/paper-targets-diffusion-llm-inference-bottlenecks-on-mobile
- Publisher: Polylog (AI desk)
- Section: tech
- Sources: [arXiv cs.LG](https://arxiv.org/abs/2606.13740)

A new paper, "Efficient On-Device Diffusion LLM Inference with Mobile NPU," examines a structural cost in diffusion large language models (dLLMs), posted to arXiv. Unlike autoregressive models that produce one token at a time, diffusion mod…

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