black-forest-labs_FLUX.1-schnell
black-forest-labs · View on Hugging Face ↗
Model card
The complete upstream card, rendered from this payload's README.md — the same hash-verified bytes the torrent distributes. Images and off-site links are removed; the original card on Hugging Face carries them.
language:
- en license: apache-2.0 tags:
- text-to-image
- image-generation
- flux
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
- Cutting-edge output quality and competitive prompt following, matching the performance of closed source alternatives.
- Trained using latent adversarial diffusion distillation,
FLUX.1 [schnell]can generate high-quality images in only 1 to 4 steps. - Released under the
apache-2.0licence, 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
- bfl.ml (currently
FLUX.1 [pro]) - replicate.com
- fal.ai
- mystic.ai
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.
Magnet link
Opens the swarm directly in your torrent client — no file download needed. Copy-paste works too:
magnet:?xt=urn:btih:d66b55825310de0d8fa54b6a37b3dbc372615681&dn=black-forest-labs_FLUX.1-schnellOpen magnet in torrent client · infohash d66b55825310de0d8fa54b6a37b3dbc372615681
Files & hashes
| Path | Size | sha1 | sha256 |
|---|---|---|---|
| README.md | 3.6 KB (3,681 B) | d02a8ab09a5e82933d8d59e499169c8ae26f128e | 66f915ff73552215a78f83852312eda079af1f5a08a258b6b6733350101c58aa |
| ae.safetensors | 319.8 MB (335,304,388 B) | 95e36a32f0e2368fc24023b11c776d22c158855e | afc8e28272cd15db3919bacdb6918ce9c1ed22e96cb12c4d5ed0fba823529e38 |
| flux1-schnell.safetensors | 22.15 GB (23,782,506,688 B) | 248007f97ac5e1269568dbac833e2bfb82a0daa1 | 9403429e0052277ac2a87ad800adece5481eecefd9ed334e1f348723621d2a0a |
| model_index.json | 536 B (536 B) | f2dcd899e03be059304cc980a87bb9389008ba2f | 24946df21ff25e210486b5f6b14208983a90c9c73f8d48cfa724c0e4e03f7201 |
| scheduler/scheduler_config.json | 274 B (274 B) | 0bdb1b0ee10b0b31745d2654369613d432dc297a | b129cebacf8f851867ec5c7c4d3f4bf787e232525a53becf4df5a72278a788d5 |
| schnell_grid.jpeg | 1.6 MB (1,671,111 B) | cde2cb873b2a3880e4c0ac2b478ab89bb00e94a2 | 5bff488da88933a529825e4fd72e10c3824e22508dc1d6f36b49850fa517ac44 |
| text_encoder/config.json | 613 B (613 B) | 5ebd923ce51522c605f64ab3d26ea024672777b6 | d79d5c8c6ce85112a923d621a5412886ddbbb0636210fc0f72f450582e675542 |
| text_encoder/model.safetensors | 234.7 MB (246,144,352 B) | a0333e58716ab750e45b8c0451e15166aa171b35 | 893d67a23f4693ed42cdab4cbad7fe3e727cf59609c40da28a46b5470f9ed082 |
| text_encoder_2/config.json | 782 B (782 B) | b00a8a6908682a2091f1194b81f220fd2b67c41c | 9001e5a8ae0571a362f806b87b6105dd1a15c33dca237b606d2561164109beeb |
| text_encoder_2/model-00001-of-00002.safetensors | 4.65 GB (4,994,582,224 B) | 425ba28604cb5fe79e70a650b37391cabf35d56e | ec87bffd1923e8b2774a6d240c922a41f6143081d52cf83b8fe39e9d838c893e |
| text_encoder_2/model-00002-of-00002.safetensors | 4.22 GB (4,530,066,360 B) | d3e1d573aa443a7995074096906d35020d409b89 | a5640855b301fcdbceddfa90ae8066cd9414aff020552a201a255ecf2059da00 |
| text_encoder_2/model.safetensors.index.json | 19.4 KB (19,885 B) | c8728bc3dca59d2616a2a594cbac3ddb9eb77d5b | 3bacec0f0cf392399d4a385908f67dd73df99c9e9cfee669f148858ba9fbdb0a |
| tokenizer/merges.txt | 512.3 KB (524,619 B) | 76e821f1b6f0a9709293c3b6b51ed90980b3166b | 9fd691f7c8039210e0fced15865466c65820d09b63988b0174bfe25de299051a |
| tokenizer/special_tokens_map.json | 588 B (588 B) | cf0682d6de72c1547f41b4f6d7c59f62deffef94 | 2cdb3b8331a60c92fc1e55a13e9fd61fd2293c5a51275fdcccd62b780052530e |
| tokenizer/tokenizer_config.json | 705 B (705 B) | 180a4e1be2a7d0b38a44108d6f24f585f35147b1 | 6bdcee9ccce2a16ca2b4c0c5ed00b42c50ea225f4472a8c4c1e963a2902c2881 |
| tokenizer/vocab.json | 1.0 MB (1,059,962 B) | 469be27c5c010538f845f518c4f5e8574c78f7c8 | e089ad92ba36837a0d31433e555c8f45fe601ab5c221d4f607ded32d9f7a4349 |
| tokenizer_2/special_tokens_map.json | 2.5 KB (2,543 B) | 17ade346a1042cbe0c1436f5bedcbd85c099d582 | 7a1985a994c41886db38c719d2a3d2f40606663cc19d7c5d6a85d349320e06d2 |
| tokenizer_2/spiece.model | 773.1 KB (791,656 B) | 5f05e7c57adf916bdba74912b0b37dea5c585988 | d60acb128cf7b7f2536e8f38a5b18a05535c9e14c7a355904270e15b0945ea86 |
| tokenizer_2/tokenizer.json | 2.3 MB (2,424,235 B) | 21ed409afa3df5a822caa0fd5da30d13941f90b5 | f5dfec163765e18e270537fe896c49f5fad74db1525641d9b255a3008b999596 |
| tokenizer_2/tokenizer_config.json | 20.3 KB (20,817 B) | b336fa236135e6c87e246485e4d69e415cc57da0 | 1a3d2db64215ed77854dd4208aac5f8361c1b5471cabd19c0ef1472d1a895eb0 |
| transformer/config.json | 321 B (321 B) | 67e7b3526946734ed5f9014dc8fc2557714cce3e | 397cfb92299488013ec3af6142a2a877366f8d2e44efbb4f3e33479e7960d3d0 |
| transformer/diffusion_pytorch_model-00001-of-00003.safetensors | 9.28 GB (9,962,580,296 B) | 07f6767b6e01dc98db83b0c64a9150c6fd6a6cfb | 9b633dbe87316385c5b1c262bd4b5a01e3d955170661d63dcec8a01e89c0d820 |
| transformer/diffusion_pytorch_model-00002-of-00003.safetensors | 9.27 GB (9,949,328,904 B) | f28f823f125578524f279456d35e52a3bb8a2a64 | 58b4434078f0c2567ddc54e3b5cbf39626ab55fbd9d5c22956e183668f535dec |
| transformer/diffusion_pytorch_model-00003-of-00003.safetensors | 3.60 GB (3,870,584,832 B) | bcc24f5f1e1a34374e18e310ba88624df553ee06 | e2cbc25471ed5186e69a9b51098300cb2f612556453e38a372c851a220ed238d |
| transformer/diffusion_pytorch_model.safetensors.index.json | 118.0 KB (120,822 B) | bf1b236a5e90a3e5ffc62c916914d3696ad276e7 | 783f857a5872f069e75daf4a5abe5efd6ff9ec2f37d71159767910cebfe048a6 |
| vae/config.json | 774 B (774 B) | b43183d0f5f0274bccd8054cd0069fc1d5f64586 | bc1e208f414a315365fbecf426838f43b87c9d5c051219e0968a56e2644b2998 |
| vae/diffusion_pytorch_model.safetensors | 159.9 MB (167,666,902 B) | 1eb8410f0c0120aff9f9101b64cea0801a1e1dde | f5b59a26851551b67ae1fe58d32e76486e1e812def4696a4bea97f16604d40a3 |
Cite this release
- Canonical URL
- https://aiseedbank.org/models/black-forest-labs_FLUX.1-schnell/
- Slug
- black-forest-labs_FLUX.1-schnell
- Infohash
- d66b55825310de0d8fa54b6a37b3dbc372615681
- License
- apache-2.0
- Signing key fingerprint
- 85a3b32c3712427b
Every file carries a locally computed sha256 — verify a download against the signed sums: black-forest-labs_FLUX.1-schnell.SHA256SUMS (+ minisign signature).
Provenance
| Upstream repository | black-forest-labs/FLUX.1-schnell |
|---|---|
| Revision (pinned) | 741f7c3ce8b383c54771c7003378a50191e9efe9 |
| Fetched at | 2026-09-04T07:15:33Z |
| License at fetch | apache-2.0 |
| Snapshot tool | huggingface · seedbank 0.1.0 |
Trackers
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✓ verified · rehash-vs-hf-metadata at 2026-09-04T07:26:15Z
apache-2.053.87 GB (57,845,408,870 bytes)diffuserssafetensorstext-to-imageimage-generationfluxendpoints_compatiblediffusers:FluxPipeline1 language (en)