# Fast LoRA inference for Flux with Diffusers and PEFT

DevFeed: [Fast LoRA inference for Flux with Diffusers and PEFT](<https://devfeed.tech/articles/fast-lora-inference-for-flux-with-diffusers-and-peft-7344.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/lora-fast>)

Author: Sayak Paul; Benjamin Bossan

Published: 2025-07-23T00:00:00Z

Content type: article

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [flux](<https://devfeed.tech/topics/flux.md>), [lora](<https://devfeed.tech/topics/lora.md>), [Inference Performance](<https://devfeed.tech/topics/inference-performance.md>), [Hacktoberfest](<https://devfeed.tech/topics/hacktoberfest.md>), [diffusers](<https://devfeed.tech/topics/diffusers.md>), [Optimization](<https://devfeed.tech/topics/optimization.md>), [peft](<https://devfeed.tech/topics/peft.md>), [quantization](<https://devfeed.tech/topics/quantization.md>), [model architecture](<https://devfeed.tech/topics/model-architecture.md>), [text-to-image](<https://devfeed.tech/topics/text-to-image.md>), [GPU](<https://devfeed.tech/topics/gpu.md>)

Tags: [amd](<https://devfeed.tech/tags/amd.md>), [diffusers](<https://devfeed.tech/tags/diffusers.md>), [diffusion](<https://devfeed.tech/tags/diffusion.md>), [flux](<https://devfeed.tech/tags/flux.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [guide](<https://devfeed.tech/tags/guide.md>), [inference](<https://devfeed.tech/tags/inference.md>), [latency](<https://devfeed.tech/tags/latency.md>), [lora](<https://devfeed.tech/tags/lora.md>), [model-architecture](<https://devfeed.tech/tags/model-architecture.md>), [optimization](<https://devfeed.tech/tags/optimization.md>), [peft](<https://devfeed.tech/tags/peft.md>), [quantization](<https://devfeed.tech/tags/quantization.md>), [text-to-image](<https://devfeed.tech/tags/text-to-image.md>)

## AI overview

This article presents an optimization recipe for faster LoRA inference with the Flux.1-Dev text-to-image model using Diffusers and PEFT. The approach addresses LoRA hotswapping and recompilation issues with Flash Attention 3, FP8 quantization from TorchAO, and hotswapping-ready compilation, achieving about a 2.3x speedup while balancing inference speed and memory use.

## Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.