# Understanding LoRA Rank Trade-offs in Diffusion Model Fine-Tuning

> *Machine translation (AI-generated content)*

**Published:** September 12, 2026
**Author:** Iman Khazrak, Narges Nejad, Mostafa M. Rezaee, Robert C. Green II
**Source:** arXiv — cs.AI
**Language:** en-US
**HTML:** https://aiqazaqstan.com/en/articles/understanding-lora-rank-trade-offs-in-diffusion-model-fine-tuning

arXiv:2609.10656v1 Announce Type: new Abstract: Selecting LoRA rank for diffusion fine-tuning requires balancing quality and compute cost. We present a controlled study on CIFAR-10 using a DDPM U-Net with ranks {2,4,8,16,32}, fixed optimization settings, and a reproducible…

> From the original source: **arXiv — cs.AI**
> [Read full article at arXiv — cs.AI](https://arxiv.org/abs/2609.10656)

**Tags:** #arXiv

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