IN NO EVENT SHALL BLACK FOREST LABS, INC. BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH USE OF THIS MODEL.

中国农历蛇年钜献!

V3.0 版模型全面升级，可能是目前Flux Dev 微调模型中，模型能力最均衡，LoRA 兼容性，真实感，出图质量和艺术创作力最接近 Flux Pro 的模型。

Great upgrade for Chinese Snake Year!

Fully upgraded Version 3.0, it may be the best model in the current Flux Dev fine-tuning models. Have the very good balance in model capabilities, LoRA compatibility, realism, image quality and artistic creativity closest to the Flux Pro model.

DedistilledMixTuned Dev V3.0:

V3.0 版模型使用指南：

模型通过分层融合技术，去除反蒸馏干扰，与原版 Flux.1 Dev 模型完全兼容，具有更高的 LoRA 权重敏感性。1024x1024 分斌率以下，建议 euler/deis + normal/beta/simple 等，1024 - 2048 大分斌率图像，建议 ddim/dpm_2/dpmpp_2m/heunpp2 + ddim_uniform/beta.

细节最强：dpmpp_2m+beta，艺术性最好：heunpp2+ddim_uniform

建议：KSampler, 20-30步。

工作流请参见图：https://civitai.com/images/53432419

The model is fully compatible with the original Flux.1 Dev. Had removed the de-distillation interference, and has a higher sensitivity to LoRA weights. For 1024x1024 and below, euler/deis + normal/beta/simple, etc., 1024 - 2048 for large binning images, ddim/dpm_2/dpmpp_2m/heunpp2 + ddim_uniform/beta.

More details: dpmpp_2m + beta, More artistry: heunpp2 + ddim_uniform

Recommended: KSampler, steps 20-30.

Workflow of the model pls ref: https://civitai.com/images/53432419

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洗去蒸馏油腻，回归模型本真。

Wash away the distillation and return to the original basic.

如果您使用后觉得模型不错，请多多返图，谢谢！

If you feel the model is good for you, please post the image here, thanks a lot!

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DedistilledMixTuned Dev V2.0:

2025 新年献礼！经过一个多月打造，在 v1.0 基础上全新升级 V2.0 版本，以照片级的真实感，在细节体现、出图速度、LoRA兼容性、光影和谐度等方面达到一个新的平衡。

2025 New Year Gift! More than a month of training and fine-tuning, The V2.0 version has been upgraded based on v1.0, and has reached a better balance in detail reflection, drawing speed, LoRA compatibility, light and shadow harmony with photorealistic realism.

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DedistilledMixTuned Schnell V1.0:

可能是目前基于 Flux.1 Schnell 调制的各种模型中，快速出图(4-8步)，遵循原版 Flux Schnell 构图风格，提示词还原能力强，且在出图质量、出图细节、回归真实和风格多样化方面取得最佳平衡的开源可商用 Schnell 基础模型。

Only 4 step, The Model may achieve to the best balance in terms of image quality, details, reality, and style diversity compare with other tuned of Flux.1 Schnell. and have a good ability of prompt following, good of the original Flux model style following.

Based on FLUX.1-schnell, Merge of LibreFLUX, finetuned by ComfyUI, Block_Patcher_ComfyUI, ComfyUI_essentials and other tools. Recommended 4-8 steps, usually step 4 is OK. Greatly improved quality and reality compare to other Flux.1 Schnell model.

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DedistilledMixTuned Dev V1.0:

可能是目前快速出图(10步以内)的 Flux 微调模型中，遵循原版 Flux.1 Dev 风格，提示词还原能力强、出图质量最好、出图细节超越 Flux.1 Dev 模型，最接近 Flux.1 Pro 的基础模型。

May be the Best Quality Step 6-10 Model, In some details, it surpasses the Flux.1 Dev model and approaches the Flux.1 Pro model. and have good ability of prompt following, good of the original Flux.1 Dev style following.

Also on Huggingface.co

Based on Flux-Fusion-V2, Merge of flux-dev-de-distill, finetuned by ComfyUI, Block_Patcher_ComfyUI, ComfyUI_essentials and other tools. Recommended 6-10 steps. Greatly improved quality compared to other Flux.1 model.

GGUF Q8_0 / Q5_1 /Q4_1 量化版本模型文件，经过测试，已同步提供，将不会再提供别的量化版本，如有需要，朋友们可根据下面提示信息，自己下载 fp8 后进行量化。

GGUF Q8_0 / Q5_1 /Q4_1 quantized model file, had tested, and uploaded the same time, over-quantization will lose the advantages of this high-speed and high-precision model, so no other quantization will be provided, you can download the FP8 model file and quantizate it according to the following tips.

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Recommend:

UNET versions (Model only) need Text Encoders and VAE, I recommend use below CLIP and Text Encoder model, will get better prompt guidance:

Long CLIP: https://huggingface.co/zer0int/CLIP-GmP-ViT-L-14/blob/main/ViT-L-14-TEXT-detail-improved-hiT-GmP-TE-only-HF.safetensors
Text Encoders: https://huggingface.co/silveroxides/CLIP-Collection/blob/main/t5xxl_flan_latest-fp8_e4m3fn.safetensors
VAE: https://huggingface.co/black-forest-labs/FLUX.1-schnell/tree/main/vae
GGUF Version: you need install GGUF model support nodes, https://github.com/city96/ComfyUI-GGUF

Simple workflow: a very simple workflow as below, needn't any other comfy custom nodes(For GGUF version, please use UNET Loader(GGUF) node of city96's):

Thanks for:

https://huggingface.co/black-forest-labs/FLUX.1-dev, A very good open source T2I model. under the FLUX.1 [dev] Non-Commercial License.

https://huggingface.co/black-forest-labs/FLUX.1-schnell, A very good open source T2I model, under the apache-2.0 licence.

https://huggingface.co/Anibaaal, Flux-Fusion is a very good mix and tuned model.

https://huggingface.co/nyanko7, Flux-dev-de-distill is a great experimental project! thanks for the inference.py scripts.

https://huggingface.co/jimmycarter/LibreFLUX, A free, de-distilled FLUX model, is an Apache 2.0 version of FLUX.1-schnell.

https://huggingface.co/MonsterMMORPG, Furkan share a lot of Flux.1 model testing and tuning courses, some special test for the de-distill model.

https://github.com/cubiq/Block_Patcher_ComfyUI, cubiq's Flux blocks patcher sampler let me do a lot of test to know how the Flux.1 block parameter value change the image gerentrating. His ComfyUI_essentials have a FluxBlocksBuster node, let me can adjust the blocks value easy. that is a great work!

https://huggingface.co/twodgirl, Share the model quantization script and the test dataset.

https://huggingface.co/John6666, Share the model convert script and the model collections.

https://github.com/city96/ComfyUI-GGUF, Native support GGUF Quantization Model.

https://github.com/leejet/stable-diffusion.cpp, Provider pure C/C++ GGUF model convert scripts.

Attn: For easy convert to GGUF Q5/Q4, you can use https://github.com/ruSauron/to-gguf-bat script, download it and put to the same directory with sd.exe file, then just pull my fp8.safetensors model file to bat file in exploer, will pop a CMD windows, and follow the menu to conver the one you want.

LICENSE

The weights fall under the FLUX.1 [dev] Non-Commercial License.