Warning: This is the 16-step model. The faster 8-step model can be found HERE

[Note: Unzip the download to get the GGUF. Civit doesn't support it natively, hence this workaround]

A merge of Flux.D with the 16-step HyperSD LoRA from ByteDance - turned into GGUF. As a result, you get an ultra-memory efficient and fast DEV (CFG sensitive) model that generates fully denoised images with just 16 steps while consuming ~6.2 GB VRAM (for the Q4_0 quant). Also, the quality is pretty close to the original DEV model with ~30 steps.

Advantages

Quality similar to the original DEV model, while requiring only ~16 steps.
Better quality and expressivity than the 8-step HyperFlux in general.
For the same seed, the output image is pretty similar to the original DEV model, so you can use it to do quick searches and do a final generation with the dev model.
Sometimes you might even get better results than the DEV model due to serendipity :) .
Disadvantage: requires 16 steps.

Which model should I download?

[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 < Q4_1 < Q5_0 < Q5_1 < Q8_0.

Q4_0 and Q4_1 should fit in 8 GB VRAM
Q5_0 and Q5_1 should fit in 11 GB VRAM
Q8_0 if you have more!

Note: With CPU offloading, you will be able to run a model even if doesn't fit in your VRAM.

All the license terms associated with Flux.1 Dev apply.

PS: Credit goes to ByteDance for the HyperSD Flux 16-steps LoRA which can be found at https://huggingface.co/ByteDance/Hyper-SD/tree/main

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