# diffusion-transformers

Published articles for diffusion-transformers.

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## Bringing Nunchaku 4-bit Diffusion Inference to Diffusers

DevFeed: [Bringing Nunchaku 4-bit Diffusion Inference to Diffusers](<https://devfeed.tech/articles/bringing-nunchaku-4-bit-diffusion-inference-to-diffusers-7368.md>)

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

Author: Pham Hong Vinh; Sayak Paul

Published: 2026-07-23T00:00:00Z

Content type: article

Language: en

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

Topics: [diffusers](<https://devfeed.tech/topics/diffusers.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [quantization](<https://devfeed.tech/topics/quantization.md>), [diffusion-transformers](<https://devfeed.tech/topics/diffusion-transformers.md>), [NVFP4](<https://devfeed.tech/topics/nvfp4.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [NCCL](<https://devfeed.tech/topics/nccl.md>)

Tags: [diffusers](<https://devfeed.tech/tags/diffusers.md>), [diffusion](<https://devfeed.tech/tags/diffusion.md>), [diffusion-transformers](<https://devfeed.tech/tags/diffusion-transformers.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [guide](<https://devfeed.tech/tags/guide.md>), [hardware](<https://devfeed.tech/tags/hardware.md>), [inference](<https://devfeed.tech/tags/inference.md>), [kernels](<https://devfeed.tech/tags/kernels.md>), [memory](<https://devfeed.tech/tags/memory.md>), [nvfp4](<https://devfeed.tech/tags/nvfp4.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [quantization](<https://devfeed.tech/tags/quantization.md>), [speed](<https://devfeed.tech/tags/speed.md>)

### AI overview

This article explains how Nunchaku brings 4-bit diffusion inference to Hugging Face Diffusers. It describes SVDQuant's W4A4 approach, integration of pre-quantized checkpoints without local CUDA compilation, and hardware requirements for NVFP4 and INT4 variants.

### Source excerpt

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

## Exploring Quantization Backends in Diffusers

DevFeed: [Exploring Quantization Backends in Diffusers](<https://devfeed.tech/articles/exploring-quantization-backends-in-diffusers-7170.md>)

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

Author: Derek Liu; Marc Sun; Sayak Paul

Published: 2025-05-21T00:00:00Z

Content type: article

Language: en

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

Topics: [AI, ML & Data Engineering](<https://devfeed.tech/topics/ai-ml-data-engineering.md>)

Tags: [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [backends](<https://devfeed.tech/tags/backends.md>), [benchmarks](<https://devfeed.tech/tags/benchmarks.md>), [black-forest-labs](<https://devfeed.tech/tags/black-forest-labs.md>), [diffusers](<https://devfeed.tech/tags/diffusers.md>), [diffusion](<https://devfeed.tech/tags/diffusion.md>), [diffusion-transformers](<https://devfeed.tech/tags/diffusion-transformers.md>), [embeddings](<https://devfeed.tech/tags/embeddings.md>), [flux](<https://devfeed.tech/tags/flux.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [guide](<https://devfeed.tech/tags/guide.md>), [hugging-face](<https://devfeed.tech/tags/hugging-face.md>), [images](<https://devfeed.tech/tags/images.md>), [memory](<https://devfeed.tech/tags/memory.md>), [quantization](<https://devfeed.tech/tags/quantization.md>)

### AI overview

The article examines quantization backends in Hugging Face Diffusers using the FLUX.1-dev image-generation pipeline. It compares high-precision and 4-bit or 8-bit variants, explains pipeline components and memory use, and discusses backends including bitsandbytes, GGUF, torchao, Quanto, and FP8.

### Source excerpt

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

## Memory-efficient Diffusion Transformers with Quanto and Diffusers

DevFeed: [Memory-efficient Diffusion Transformers with Quanto and Diffusers](<https://devfeed.tech/articles/memory-efficient-diffusion-transformers-with-quanto-and-diffusers-7450.md>)

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

Author: Sayak Paul; David Corvoysier

Published: 2024-07-30T00:00:00Z

Content type: tutorial

Language: en

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

Topics: [diffusers](<https://devfeed.tech/topics/diffusers.md>), [diffusion-transformers](<https://devfeed.tech/topics/diffusion-transformers.md>), [quantization](<https://devfeed.tech/topics/quantization.md>), [optimum](<https://devfeed.tech/topics/optimum.md>), [PyTorch](<https://devfeed.tech/topics/pytorch.md>), [stable-diffusion](<https://devfeed.tech/topics/stable-diffusion.md>), [text-to-image](<https://devfeed.tech/topics/text-to-image.md>), [benchmarking](<https://devfeed.tech/topics/benchmarking.md>)

Tags: [benchmarking](<https://devfeed.tech/tags/benchmarking.md>), [diffusers](<https://devfeed.tech/tags/diffusers.md>), [diffusion-transformers](<https://devfeed.tech/tags/diffusion-transformers.md>), [efficiency](<https://devfeed.tech/tags/efficiency.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [guide](<https://devfeed.tech/tags/guide.md>), [optimum](<https://devfeed.tech/tags/optimum.md>), [pytorch](<https://devfeed.tech/tags/pytorch.md>), [quality](<https://devfeed.tech/tags/quality.md>), [quantization](<https://devfeed.tech/tags/quantization.md>), [sd3](<https://devfeed.tech/tags/sd3.md>), [text-to-image](<https://devfeed.tech/tags/text-to-image.md>)

### AI overview

This tutorial explains how to reduce the memory requirements of Transformer-based diffusion pipelines using Quanto quantization utilities from the Diffusers library. It benchmarks FP8 quantization on PixArt-Sigma, Stable Diffusion 3, and Aura Flow, reporting memory savings with slightly higher latency and little quality degradation.

### Source excerpt

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