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FLUX.1 Schnell

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.

KindUNetBase modelFLUXVersionPublisher@lzyvegetableUnratedgrade

Model source

Kind
UNet
File size
160 MB–22.1 GB
Base model
FLUX
Version
vRevision cb2d0f9
Updated
Oct 3, 2026
Publisher
@lzyvegetable
Downloads
1.2K
Tasks
Text to image
Source
Hugging Face

Source description

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.

Key Features

  1. Cutting-edge output quality and competitive prompt following, matching the performance of closed source alternatives.
  2. Trained using latent adversarial diffusion distillation, FLUX.1 [schnell] can generate high-quality images in only 1 to 4 steps.
  3. Released under the apache-2.0 licence, the model can be used for personal, scientific, and commercial purposes.

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.

API Endpoints

The FLUX.1 models are also available via API from the following sources

ComfyUI

FLUX.1 [schnell] is also available in Comfy UI for local inference with a node-based workflow.

Diffusers

To use FLUX.1 [schnell] with the 🧨 diffusers python library, first install or upgrade diffusers

pip install -U diffusers

Then you can use FluxPipeline to run the model

import torch
from diffusers import FluxPipeline

pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16)
pipe.enable_model_cpu_offload() #save some VRAM by offloading the model to CPU. Remove this if you have enough GPU power

prompt = "A cat holding a sign that says hello world"
image = pipe(
    prompt,
    guidance_scale=0.0,
    num_inference_steps=4,
    max_sequence_length=256,
    generator=torch.Generator("cpu").manual_seed(0)
).images[0]
image.save("flux-schnell.png")

To learn more check out the diffusers documentation


Limitations

  • This model is not intended or able to provide factual information.
  • As a statistical model this checkpoint might amplify existing societal biases.
  • The model may fail to generate output that matches the prompts.
  • Prompt following is heavily influenced by the prompting-style.

Out-of-Scope Use

The model and its derivatives may not be used

  • In any way that violates any applicable national, federal, state, local or international law or regulation.
  • For the purpose of exploiting, harming or attempting to exploit or harm minors in any way; including but not limited to the solicitation, creation, acquisition, or dissemination of child exploitative content.
  • To generate or disseminate verifiably false information and/or content with the purpose of harming others.
  • To generate or disseminate personal identifiable information that can be used to harm an individual.
  • To harass, abuse, threaten, stalk, or bully individuals or groups of individuals.
  • To create non-consensual nudity or illegal pornographic content.
  • For fully automated decision making that adversely impacts an individual's legal rights or otherwise creates or modifies a binding, enforceable obligation.
  • Generating or facilitating large-scale disinformation campaigns.

Requirements

Models

2

Sources

1 source
Hugging FacePrimaryVersion cb2d0f958483a378c26558405a06224a6889b9f4
huggingface.co/lzyvegetable/FLUX.1-schnell/tree/cb2d0f958483a378c26558405a06224a6889b9f4

Verified Oct 3

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Model artifacts

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ae.safetensors

safetensors · FP32 (tensor header) · 320 MB · SHA-256 afc8e28272cd…9e38 · Hugging Face

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flux1-schnell.safetensors

safetensors · 22.1 GB · SHA-256 9403429e0052…2a0a · Hugging Face

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text_encoder_2/model-00001-of-00002.safetensors

safetensors · 4.65 GB · SHA-256 ec87bffd1923…893e · Hugging Face

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text_encoder_2/model-00002-of-00002.safetensors

safetensors · 4.22 GB · SHA-256 a5640855b301…da00 · Hugging Face

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text_encoder/model.safetensors

safetensors · 235 MB · SHA-256 893d67a23f46…d082 · Hugging Face

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vae/diffusion_pytorch_model.safetensors

safetensors · 160 MB · SHA-256 f5b59a268515…40a3 · Hugging Face

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Source excerpts

3 excerpts

--- language: - en license: apache-2.0 tags: - text-to-image - image-generation - flux --- ![FLUX.1 [schnell] Grid](./schnell_grid.jpeg) `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](https://blackforestlabs.ai/announcing-black-forest-labs/). # Key Features 1. Cutting-edge output quality and competitive prompt following, matching the performance of closed source alternatives. 2. Trained using latent adversarial diffusion distillation, `FLUX.1 [schnell]` can generate high-quality images in only 1 to 4 steps. 3. Released under the `apache-2.0` licence, the model can be used for personal, scientific, and commercial purposes. # Usage We provide a reference implementation of `FLUX.1 [schnell]`, as well as sampling code, in a dedicated [github repository](https://github.com/black-forest-labs/flux). Developers and creatives looking to build on top of `FLUX.1 [schnell]` are encouraged to use this as a starting point. ## API Endpoints The FLUX.1 models are also available via API from the following sources - [bfl.ml](https://docs.bfl.ml/) (currently `FLUX.1 [pro]`) - [replicate.com](https://replicate.com/collections/flux) - [fal.ai](https://fal.ai/models/fal-ai/flux/schnell) - [mystic.ai](https://www.mystic.ai/black-forest-labs/flux1-schnell) ## ComfyUI `FLUX.1 [schnell]` is also available in [Comfy UI](https://github.com/comfyanonymous/ComfyUI) for local inference with a node-based workflow. ## Diffusers To use `FLUX.1 [schnell]` with the 🧨 diffusers python library, first install or upgrade diffusers ```shell pip install -U diffusers ``` Then you can use `FluxPipeline` to run the model ```python import torch from diffusers import FluxPipeline pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16) pipe.enable_model_cpu_offload() #save some VRAM by offloading the model to CPU. Remove this if you have enough GPU power prompt = "A cat holding a sign that says hello world" image = pipe( prompt, guidance_scale=0.0, num_inference_steps=4, max_sequence_length=256, generator=torch.Generator("cpu").manual_seed(0) ).images[0] image.save("flux-schnell.png") ``` To learn more check out the [diffusers](https://huggingface.co/docs/diffusers/main/en/api/pipelines/flux) documentation --- # L...

Source context: 1193 downloads · 1 likes · Pipeline text-to-image · Library diffusers · Repo lzyvegetable/FLUX.1-schnell

Source context: 1228 downloads · 1 likes · Pipeline text-to-image · Library diffusers · Repo lzyvegetable/FLUX.1-schnell