diffusers/benchmarks
Welcome to 🤗 Diffusers Benchmarks! This is dataset where we keep track of the inference latency and memory information of the core models in the diffusers library. Currently, the core models are: Flux Wan LTX SDXL Note that we will continue to extend this list based on their usage. You can analyze the results in this demo. [!IMPORTANT] Instead of benchmarking the entire diffusion pipelines, we only benchmark the forward passes of the diffusion networks under different settings… See the full description on the dataset page: https://huggingface.co/datasets/diffusers/benchmarks.
<div align="center"> <img src="https://huggingface.co/datasets/diffusers/docs-images/resolve/main/benchmarking/benchmarks_headshot.jpg" width=800/> </div>
Welcome to 🤗 Diffusers Benchmarks!
This is dataset where we keep track of the inference latency and memory information of the core models in the diffusers library.
Currently, the core models are:
- Flux
- Wan
- LTX
- SDXL
Note that we will continue to extend this list based on their usage.
You can analyze the results in this demo.
[!IMPORTANT] Instead of benchmarking the entire diffusion pipelines, we only benchmark the forward passes of the diffusion networks under different settings (compile, offloading, quantization, etc.). We only benchmark the diffusion networks because they are typically the most compute-heavy part in a diffusion pipeline.
We use this GitHub Actions workflow to report the above numbers automatically. This workflow runs on a biweekly cadence.
Here is an example run.