FP8 - All-in-one model here: <a target="_blank" rel="ugc" href="https://civarchive.com/models/671478">https://civarchive.com/models/671478</a> (but, try GGUF first!)[Note: Unzip the download to get the GGUF. Civit doesn't support it natively, hence this workaround]A merge of <a target="_blank" rel="ugc" href="https://civarchive.com/models/645943">FluxUnchained</a> and <a target="_blank" rel="ugc" href="https://civarchive.com/models/657607">FastFlux</a> - converted to GGUF. As a result, it can now generate artistic NSFW images in 4-8 steps while consuming very low VRAM. The Q_4_0 model consumes around 6.5 GB VRAM and takes around 1.5 min to generate a 1024x1024 image with 8 steps. [See <a target="_blank" rel="ugc" href="https://github.com/lllyasviel/stable-diffusion-webui-forge/discussions/1050">https://github.com/lllyasviel/stable-diffusion-webui-forge/discussions/1050</a> to learn more about Forge UI GGUF support and also where to download the VAE, clip_l and t5xxl models.]You can also combine it with other LoRAs to get the effect you want.<h3 id="which-model-should-i-download-ry7kri0dk">Which model should I download?</h3>[Current situation: Using the updated Forge UI and Comfy UI (GGUF node) I can run Q8_0 on my 11GB 1080ti.]Download the one that fits in your VRAM. The additional inference cost is quite small if the model fits in the GPU. Size order is Q4_0 &lt; Q4_1 &lt; Q5_0 &lt; Q5_1 &lt; Q8_0.<ul><li>Q4_0 and Q4_1 should fit in 8 GB VRAM</li><li>Q5_0 and Q5_1 should fit in 11 GB VRAM</li><li>Q8_0 if you have more!</li></ul>Note: With CPU offloading, you will be able to run a model even if doesn't fit in your VRAM.<h2 id="lora-usage-tips-znti9zu3m">LoRA usage tips</h2>The model seems to work pretty well with LoRAs (tested in Comfy). But you might need to increase the number of steps a little (8-10).All license terms associated with Flux.1 Dev and Schnell apply.

GGUF: FastFlux Unchained (FluxUnchained merged in Flux.S)

Bigger than Q4_0, better than Q4_0

ggufFastfluxUnchained_q41V1.zip

Files with SHA256: 6ea2cbc6aadab84c02e36ae3e763ed74b267dc751a27eb22a6d9b907cb78ad77