---
title: "Flux GGUF Quantized Weights in ComfyUI — Folder Path, VRAM & Node Setup"
description: "How to install and run Flux GGUF Quantized Weights (City96 ComfyUI-GGUF) in ComfyUI on Windows. Target folder: models/unet/, recommended VRAM: 6 GB–12 GB depending on Q4_K_S to Q8_0."
canonical: https://comfy.ink/models/gguf-flux-quantized
updated: 2026-10-17
---

# Flux GGUF Quantized Weights in ComfyUI

Quantized transformer weights that let 8 GB and 12 GB Windows GPUs run Flux.1 Dev and Hunyuan Video without swapping to disk. Requires 6 GB–12 GB depending on Q4_K_S to Q8_0 VRAM and loads from models/unet/.

## Facts (2026-10-17)

- **Model Family:** City96 ComfyUI-GGUF
- **VRAM Target:** 6 GB–12 GB depending on Q4_K_S to Q8_0
- **ComfyUI Folder:** models/unet/
- **Precision:** GGUF Q4_K_S, Q5_K_M, Q8_0
- **Default Sampler:** UnetLoaderGGUF + DualCLIPLoaderGGUF

## Flux GGUF Quantized Weights Quick Reference for ComfyUI Windows

| Parameter | Recommended Setting | Notes |
| --- | --- | --- |
| Target Directory | models/unet/ | Refresh canvas with R key after copying |
| VRAM Tier | 6 GB–12 GB depending on Q4_K_S to Q8_0 | Use --lowvram or GGUF Q4 on 8 GB cards |
| Weight Format | GGUF Q4_K_S, Q5_K_M, Q8_0 | Never load untrusted .ckpt pickle files |
| Sampler Recipe | UnetLoaderGGUF + DualCLIPLoaderGGUF | Wire through core KSampler node |

## Where to place Flux GGUF Quantized Weights weights on Windows

Quantized transformer weights that let 8 GB and 12 GB Windows GPUs run Flux.1 Dev and Hunyuan Video without swapping to disk.

Place the primary `.safetensors` or `.gguf` weight file inside `models/unet/` inside your ComfyUI directory, or point [extra_model_paths.yaml](https://comfy.ink/install/extra-model-paths-yaml-setup) to your existing shared models drive.

After moving the file, press **R** on the [ComfyUI Studio](https://comfy.ink/studio) canvas (or click Refresh) so the loader dropdown lists the new checkpoint immediately without restarting the server.

## Recommended loader nodes and sampler settings

- **Precision & Memory:** GGUF Q4_K_S, Q5_K_M, Q8_0. Cards at the lower end of 6 GB–12 GB depending on Q4_K_S to Q8_0 should pair this model with [FP8 or GGUF quantization](https://comfy.ink/words/gguf-quantization) and [VAE Decode (Tiled)](https://comfy.ink/nodes/vae-decode-encode).
- **Sampler & Scheduler:** UnetLoaderGGUF + DualCLIPLoaderGGUF. Wire the model output into [KSampler](https://comfy.ink/nodes/ksampler) and connect the matching CLIP and VAE streams.
- **Installer:** If you have not set up the desktop environment yet, get the Windows build at [/download](https://comfy.ink/download).

## FAQ

### Which folder does Flux GGUF Quantized Weights go into in ComfyUI?

Put Flux GGUF Quantized Weights inside `models/unet/` in your ComfyUI installation, then press R on the canvas to refresh node dropdowns.

### Can I run Flux GGUF Quantized Weights on an 8 GB NVIDIA GPU?

Yes — use FP8 or GGUF Q4/Q5 weights via [ComfyUI-GGUF](https://comfy.ink/nodes/gguf-loader-nodes) and keep [tiled VAE decoding](https://comfy.ink/nodes/vae-decode-encode) enabled so peak VRAM stays under 8 GB.

## Related

- [ComfyUI Models & Checkpoints](https://comfy.ink/models)
- [KSampler & KSampler (Advanced)](https://comfy.ink/nodes/ksampler)
- [Load Checkpoint (CheckpointLoaderSimple)](https://comfy.ink/nodes/load-checkpoint)
- [ComfyUI VRAM Requirements for SDXL, Flux & Video (6GB–24GB)](https://comfy.ink/guides/comfyui-vram-requirements-guide)
- [Flux.1 Dev in ComfyUI](https://comfy.ink/models/flux-1-dev)

## Download

Free desktop app: [Download Comfy](https://comfy.ink/download)

Markdown mirror: https://comfy.ink/models/gguf-flux-quantized.md