GGUF: FastFlux (Flux.1-Schnell Merged with Flux.1-Dev)
Q4_0_v1
nakif0968
Flux1.D merged in Flux1.S. It can generate good-quality images (better than Schnell) with just 4 steps, and the quality further improves with more steps, while consuming a very low amount of VRAM. Q_4_0 can produce 1024x1024 images in 45 seconds on my 11GB 1080ti, while using around 6.5 Gigs of VRAM.
It can be used in ComfyUI with this custom node or with Forge UI.
Which model should I download?
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: On Forge UI there is the prospect of CPU offloading, which might be missing on Comfy (yet). With CPU offloading, you might be able to run a model even if doesn't fit in your VRAM.
LoRA usage tips
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).
Updates
V2: I created the original (v1) from an fp8 checkpoint. Due to double quantization, it accumulated more errors. So I found that v1 couldn't produce sharp images. For v2 I manually merged the bf16 Dev and Schnell checkpoints and then made the GGUF. This version can produce more details and much crisper results.
Resources
See https://github.com/lllyasviel/stable-diffusion-webui-forge/discussions/1050 to learn more about Forge UI GGUF support and also where to download the VAE, clip_l and t5xxl models.
All the license terms associated with Flux.1 Dev and Flux.1 Schnell apply.
PS: Credit goes to jice and comfy.org for the merge recipe. I used a slightly modified version of https://github.com/city96/ComfyUI-GGUF/blob/main/tools/convert.py to create this.
What is GGUF: FastFlux (Flux.1-Schnell Merged with Flux.1-Dev)?
GGUF: FastFlux (Flux.1-Schnell Merged with Flux.1-Dev) is a highly specialized Image generation AI Model of type Safetensors / Checkpoint AI Model created by AI community user nakif0968. Derived from the powerful Stable Diffusion (Flux.1 S) model, GGUF: FastFlux (Flux.1-Schnell Merged with Flux.1-Dev) has undergone an extensive fine-tuning process, leveraging the power of a dataset consisting of images generated by other AI models or user-contributed data. This fine-tuning process ensures that GGUF: FastFlux (Flux.1-Schnell Merged with Flux.1-Dev) is capable of generating images that are highly relevant to the specific use-cases it was designed for, such as base model, merge, base models.
With a rating of 0 and over 0 ratings, GGUF: FastFlux (Flux.1-Schnell Merged with Flux.1-Dev) is a popular choice among users for generating high-quality images from text prompts.
Can I download GGUF: FastFlux (Flux.1-Schnell Merged with Flux.1-Dev)?
Yes! You can download the latest version of GGUF: FastFlux (Flux.1-Schnell Merged with Flux.1-Dev) from here.
How to use GGUF: FastFlux (Flux.1-Schnell Merged with Flux.1-Dev)?
To use GGUF: FastFlux (Flux.1-Schnell Merged with Flux.1-Dev), download the model checkpoint file and set up an UI for running Stable Diffusion models (for example, AUTOMATIC1111). Then, provide the model with a detailed text prompt to generate an image. Experiment with different prompts and settings to achieve the desired results. If this sounds a bit complicated, check out our initial guide to Stable Diffusion – it might be of help. And if you really want to dive deep into AI image generation and understand how set up AUTOMATIC1111 to use Safetensors / Checkpoint AI Models like GGUF: FastFlux (Flux.1-Schnell Merged with Flux.1-Dev), check out our crash course in AI image generation.
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Latest version (Q4_0_v1): 1 File
About this version: Q4_0_v1
Q4_0: Memory consumption is similar to NF4 quants.
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