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realrebelai/Boogu-Image-Edit_GGUFs overview

Boogu Image 0.1 Edit GGUF <img src="https://cdn uploads.huggingface.co/production/uploads/68761990332d15464ccc8dee/3C8kcxCP nnSg oNqmg5n.png" width="300" heigh…

ggufcomfyuiimage-editboogubase_model:Boogu/Boogu-Image-0.1-Editbase_model:quantized:Boogu/Boogu-Image-0.1-Editlicense:apache-2.0region:us

Runs locally from ~6.37 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline

Repository Files & Downloads

5 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
boogu-edit-dit-Q4_0.ggufGGUFQ4_06.37 GBDownload
boogu-edit-dit-Q4_1.ggufGGUFQ4_16.93 GBDownload
boogu-edit-dit-Q5_0.ggufGGUFQ5_07.49 GBDownload
boogu-edit-dit-Q5_1.ggufGGUFQ5_18.05 GBDownload
boogu-edit-dit-Q8_0.ggufGGUFQ8_010.84 GBDownload

Model Details

Model IDrealrebelai/Boogu-Image-Edit_GGUFs
Authorrealrebelai
Pipeline
Licenseapache-2.0
Base modelBoogu/Boogu-Image-0.1-Edit
Last modified2026-06-20T07:37:13.000Z

Model README

---

license: apache-2.0

base_model: Boogu/Boogu-Image-0.1-Edit

base_model_relation: quantized

tags:

  • comfyui
  • gguf
  • image-edit
  • boogu

---

Boogu-Image-0.1-Edit GGUF

<img src="https://cdn-uploads.huggingface.co/production/uploads/68761990332d15464ccc8dee/3C8kcxCP-nnSg-oNqmg5n.png" width="300" height="300" />

Required Text Encoder & VAE

  • Text Encoder (Qwen3-VL): You must use an FP8 scaled version of the Qwen3-VL encoder.

* Download the FP8 encoder from the Comfy-Org Boogu Repo.

  • VAE (Flux): The Boogu pipeline utilizes the standard Flux VAE.

* Download flux1_vae_bf16.safetensors from the Comfy-Org Boogu Repo

⚠️ Why are there no Q2 or Q3 K-Quants?

Currently, this repo only provides Flat Quants (Q4_0, Q4_1, Q5_0, Q5_1, Q8_0).

Standard K-quants (like Q2_K or Q3_K_M) require a hardcoded architectural mapping blueprint inside the llama.cpp source code. Because the Boogu/OmniGen architecture is brand new, those K-quant blueprints do not exist in the compiler yet. Flat quants bypass this requirement by forcing all 2D tensors to the target bit-depth.

If you are running an 8GB VRAM setup (like an RTX 3070), the Q4_0 is the recommended sweet spot for VRAM savings and quality.

How to use in ComfyUI

Prerequisite: Core Update Override

Native support for the Boogu/OmniGen architecture has been merged from Pull Request #14523. If your Load Clip node doesnt have the Boogu architecture, you must manually fetch the PR into your ComfyUI installation.

  1. Open a command prompt directly inside your ComfyUI folder.
  2. Run the following commands to fetch and switch to the PR branch:
   git fetch origin pull/14523/head:boogu-pr
   git checkout boogu-pr

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