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Futuremark/FLUX.1-schnell-onnx

By Futuremark · ↓ 0 · ♥ 0 · Updated 2025-05-21

What's in this repo

This page lists the files in Futuremark/FLUX.1-schnell-onnx, including model.onnx and more.

  • 7 ONNX models (.onnx files)
  • 15 files, including 7 .onnx, 5 .onnx_data, 1 .md, 1 .jpeg
  • Last updated 2025-05-21

ONNX files

File Size Download
clip.opt/model.onnx — Download
t5-fp8.opt/model.onnx — Download
t5.opt/model.onnx — Download
transformer.opt/bf16/model.onnx — Download
transformer.opt/fp4/model.onnx — Download
transformer.opt/fp8/model.onnx — Download
vae.opt/model.onnx — Download

How to use

These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.

README

Mirror of https://huggingface.co/black-forest-labs/FLUX.1-schnell-onnx commit 7ad1eace4e708f71d82902ce08389444134cdf0d

FLUX.1 [schnell] Grid

FLUX.1 [schnell] is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions. For more information, please read our blog post.

This repository holds ONNX exports of FLUX.1 [schnell] in BF16, FP8, and FP4 precision. The main repository of this model can be found here.

Usage

We provide a reference implementation of FLUX.1 [schnell], as well as sampling code, in a dedicated github repository. Developers and creatives looking to build on top of FLUX.1 [schnell] are encouraged to use this as a starting point.

Model info

onnx text-to-image image-generation flux license:apache-2.0 region:us
↓ 0 ♥ 0

Created: 2025-05-21

Updated: 2025-05-21

View on Hugging Face

Files (15)

.gitattributes
README.md
clip.opt/model.onnx ONNX
schnell_grid.jpeg
t5-fp8.opt/backbone.onnx_data
t5-fp8.opt/model.onnx ONNX
t5.opt/backbone.onnx_data
t5.opt/model.onnx ONNX
transformer.opt/bf16/backbone.onnx_data
transformer.opt/bf16/model.onnx ONNX
transformer.opt/fp4/backbone.onnx_data
transformer.opt/fp4/model.onnx ONNX
transformer.opt/fp8/backbone.onnx_data
transformer.opt/fp8/model.onnx ONNX
vae.opt/model.onnx ONNX

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