---
license: apache-2.0
---
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<h1> lyraDiff: An Out-of-the-box Acceleration Engine for Diffusion and DiT Models</h1>

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`lyraDiff` introduces a **recompilation-free** inference engine for Diffusion and DiT models, achieving **state-of-the-art speed**, **extensive model support**, and **pixel-level image consistency**.

## Highlights
- **State-of-the-art Inference Speed**: `lyraDiff` utilizes multiple techniques to achieve up to **6.1x** speedup of the model inference, including **Quantization**, **Fused GEMM Kernels**, **Flash Attention**, and **NHWC & Fused GroupNorm**.
- **Memory Efficiency**: `lyraDiff` utilizes buffer-based DRAM reuse strategy and multiple types of quantizations (FP8/INT8/INT4) to save **10-40%** of DRAM usage.
- **Extensive Model Support**: `lyraDiff` supports a wide range of top Generative/SR models such as **SD1.5, SDXL, FLUX, S3Diff, etc.**, and those most commonly used plugins such as **LoRA, ControlNet and Ip-Adapter**.
- **Zero Compilation Deployment**: Unlike **TensorRT** or **AITemplate**, which takes minutes to compile, `lyraDiff` eliminates runtime recompilation overhead even with model inputs of dynamic shapes.
- **Image Gen Consistency**: The outputs of `lyraDiff` are aligned with the ones of [HF diffusers](https://github.com/huggingface/diffusers) at the pixel level, even under LoRA switch in quantization mode.
- **Fast Plugin Hot-swap**: `lyraDiff` provides **Super Fast Model Hot-swap for ControlNet and LoRA** which can hugely benefit a real-time image gen service.

## Usage

![image/png](https://cdn-uploads.huggingface.co/production/uploads/6461b412846a6c8c8305319d/41_dvtx232Kzu8MkY6qEx.png)

`lyraDiff-Flux.1-dev` is converted from the standard [FLUX.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev) model weights using this [script](https://github.com/TMElyralab/lyraDiff/blob/main/lyradiff/convert_model_scripts/quantize.py) to be compatiable with [lyraDiff](https://github.com/TMElyralab/lyraDiff), and contains both `FP8` and `FP16` version of converted Flux.1-dev

We provide a reference implementation of lyraDiff version of Flux.1-dev, as well as sampling code, in a dedicated [github repository](https://github.com/TMElyralab/lyraDiff).

## Citation
``` bibtex
@Misc{lyraDiff_2025,
  author =       {Yibo Lu, Sa Xiao, Kangjian Wu, Bin Wu, Mian Peng, Haoxiong Su, Qiwen Mao, Wenjiang Zhou},
  title =        {lyraDiff: An Out-of-the-box Acceleration Engine for Diffusion and DiT Models},
  howpublished = {\url{https://github.com/TMElyralab/lyraDiff}},
  year =         {2025}
}
```

## License
`lyraDiff-Flux.1-dev` falls under the [`FLUX.1 [dev]` Non-Commercial License](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md).