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Flux Kontext Dev GGUF (Low VRAM) w/ Detail Daemon & Upscaling

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Description

I've created a simple Flux Kontext Dev GGUF workflow designed specifically for low VRAM systems. By leveraging the GGUF versions of the Kontext model, you can achieve fast, high-quality image generation even on GPUs with as little as 4–6GB of VRAM.

This setup includes:

  • The Flux Kontext Dev GGUF model for efficient generation
  • Integrated detail enhancement (Detail Daemon) and upscaling nodes to boost your final output quality

If you want a full walkthrough of the workflow and installation process—including manual setup, recommended
settings, and tips for both local and cloud deployment—check out my YouTube tutorial linked below:


https://youtu.be/u9u5UvV1S28



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  • - latest (6 months ago)

Primitive Nodes (11)

DetailDaemonSamplerNode (1)

EmptySD3LatentImage (1)

FluxGuidance (1)

FluxKontextImageScale (1)

ModelSamplingFlux (1)

Note (2)

PrimitiveNode (2)

ReferenceLatent (1)

UnetLoaderGGUF (1)

Custom Nodes (15)

ComfyUI

  • - VAEDecode (1)

  • - VAELoader (1)

  • - SamplerCustomAdvanced (1)

  • - VAEEncode (1)

  • - BasicGuider (1)

  • - RandomNoise (1)

  • - DualCLIPLoader (1)

  • - ImageScaleBy (1)

  • - CLIPTextEncode (1)

  • - LoadImage (1)

  • - SaveImage (1)

  • - ImageUpscaleWithModel (1)

  • - UpscaleModelLoader (1)

  • - KSamplerSelect (1)

  • - BasicScheduler (1)

Checkpoints (0)

LoRAs (0)