neptunite/moodyDesireMix_GGUF

Moody Desire Mix v1.0 - GGUF Quantizations

GGUF quantized versions of Moody Desire Mix v1.0 (Flux.2 Klein 9B Checkpoint), quantized from the original FP16 source using the city96/ComfyUI-GGUF toolchain.

GGUF 量化版本，原始模型来自 Moody Desire Mix v1.0 （Flux.2 Klein 9B Checkpoint），使用 city96/ComfyUI-GGUF 工具链从 FP16 源文件量化而来。

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Available Versions / 可用版本

File / 文件	Quant / 量化	Size / 大小	VRAM / 推荐显存	Quality / 画质保留
moodyDesireMix_v10_Q8_0.gguf	Q8_0	~10 GB	12GB+	98–99%
moodyDesireMix_v10_Q6_K.gguf	Q6_K	~8 GB	10GB+	95–97%
moodyDesireMix_v10_Q5_K_M.gguf	Q5_K_M	~7 GB	8GB+	90–93%
moodyDesireMix_v10_Q4_K_M.gguf	Q4_K_M	~6 GB	6GB+	80–87%

Recommendation: Use Q8_0 if VRAM allows. Q6_K / Q5_K_M for 6–10GB cards. Q4_K_M for 4–6GB cards as a last resort.

建议：显存充裕优先选 Q8_0；6–10GB 显卡推荐 Q6_K 或 Q5_K_M；4–6GB 显卡选 Q4_K_M。

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Usage (ComfyUI) / 使用方法（ComfyUI）

Step 1 — Install ComfyUI-GGUF / 安装 ComfyUI-GGUF

Search for ComfyUI-GGUF in ComfyUI Manager and install it, or clone manually:

在 ComfyUI Manager 中搜索并安装 ComfyUI-GGUF，或手动克隆：

cd ComfyUI/custom_nodes
git clone https://github.com/city96/ComfyUI-GGUF

Step 2 — Place the Model File / 放置模型文件

Place the downloaded .gguf file into:

将下载的 .gguf 文件放入：

ComfyUI/models/unet/

Step 3 — Load in Workflow / 在 Workflow 中加载

In the ComfyUI canvas:

1. Double-click to open the node search
2. Search for Unet Loader (GGUF) and replace your existing Load Diffusion Model node
3. Select the .gguf file from the dropdown

在 ComfyUI 画布中：

1. 双击空白处打开节点搜索
2. 搜索 **Unet Loader (GGUF)**，替换原有的 Load Diffusion Model 节点
3. 在节点下拉菜单中选择对应的 .gguf 文件

About GGUF Quantization / 关于 GGUF 量化

GGUF is a quantization format popularized by llama.cpp that supports offloading model layers to system RAM, enabling large models to run even when VRAM is insufficient. Q8_0 has negligible quality loss compared to FP16, while Q5_K_M offers the best balance between file size and image quality.

GGUF 是 llama.cpp 推广的量化格式，支持将模型层卸载到系统内存（RAM）， 在显存不足时也能运行大模型。Q8_0 与 FP16 原版质量差距极小，Q5_K_M 是文件大小与画质的最佳折中选择。

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Original Model / 原始模型

• Original / 原始模型：Moody Desire Mix v1.0 on CivitAI
• Base Architecture / 基础架构：Flux.2 Klein 9B
• Quantization Tool / 量化工具：city96/ComfyUI-GGUF tools