# Hugging Face — Memory-efficient Diffusion Transformers with Quanto and Diffusers

- Company: Hugging Face (huggingface.co)
- Announced: 2024-07-30T00:00:00+00:00
- Category: developer-tool-release
- Subject: Platform
- Models affected: PixArt-Sigma, Stable Diffusion 3, Aura Flow
- Source: https://huggingface.co/blog/quanto-diffusers
- Record: https://forck.live/items/1846-memory-efficient-diffusion-transformers-with-quanto-and-diffusers

Hugging Face announces that its Quanto quantization toolkit can be used with Diffusers to reduce GPU memory consumption for Transformer-based diffusion pipelines, including PixArt-Sigma, Stable Diffusion 3, and Aura Flow, with minimal quality loss.

## Evidence

Verbatim from https://huggingface.co/blog/quanto-diffusers:

> In this post, we show how to improve the memory efficiency of Transformer-based diffusion pipelines by leveraging Quanto's quantization utilities from the Diffusers library.

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