Update official QuantFunc Civitai homepage

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---
license: other
license_name: krea-2-community-license
base_model:
- krea/Krea-2-Turbo
base_model_relation: quantized
pipeline_tag: text-to-image
library_name: diffusers
tags:
- text-to-image
- image-generation
- quantized
- 4-bit
- int4
- turbo
- krea
- krea-2
- quantfunc
- comfyui
---
<div align="center" style="margin-top: 50px;">
  <a href="https://github.com/QuantFunc/ComfyUI-QuantFunc">
    <img src="https://raw.githubusercontent.com/QuantFunc/ComfyUI-QuantFunc/main/assets/logo.webp" width="300" alt="QuantFunc logo">
  </a>
</div>
<p align="center">
  🌐 <a href="https://www.quantfunc.com/">Website</a> &nbsp;|&nbsp;
  🐙 <a href="https://github.com/QuantFunc/ComfyUI-QuantFunc">GitHub</a> &nbsp;|&nbsp;
  🤗 <a href="https://huggingface.co/QuantFunc">Hugging Face</a> &nbsp;|&nbsp;
  🤖 <a href="https://www.modelscope.cn/profile/QuantFunc">ModelScope</a> &nbsp;|&nbsp;
  🎨 <a href="https://civitai.com/user/quantfunc">Civitai</a> &nbsp;|&nbsp;
  🎮 <a href="https://discord.gg/jCp9TpFWcn">Discord</a>
</p>

# Krea-2-QuantFunc-4bit

**4x compression, quality held.**

QuantFunc INT4 compresses Krea-2-Turbo to about a quarter of its 16-bit size. In our visual comparisons, composition, detail, color and style stay close to the 16-bit baseline, roughly on par with FP8 and INT8 ConvRot.

## Showcase

All images below were generated by Krea-2-QuantFunc-4bit.

| Portrait photography | Sci-fi scene |
|---|---|
| ![Portrait](https://huggingface.co/QuantFunc/Krea-2-QuantFunc-4bit/resolve/main/assets/krea2_show.webp) | ![Sci-fi](https://huggingface.co/QuantFunc/Krea-2-QuantFunc-4bit/resolve/main/assets/krea2_show2.webp) |
| **Impasto art** | **Watercolor illustration** |
| ![Impasto](https://huggingface.co/QuantFunc/Krea-2-QuantFunc-4bit/resolve/main/assets/krea2_show3.webp) | ![Watercolor](https://huggingface.co/QuantFunc/Krea-2-QuantFunc-4bit/resolve/main/assets/krea2_show4.webp) |

## Fast denoising, fast end-to-end too

### High-VRAM

On an RTX 4090, same workflow and generation settings:

| Stage | QuantFunc INT4 | FP8 | Speedup |
|---|---:|---:|---:|
| Denoising | **1.6s** | 5.0s | **3.13x** |
| End-to-end | **2.5s** | 6.5s | **2.6x** |

> End-to-end includes text encoder, denoising and VAE. Text encoder and VAE are not part of the QuantFunc plugin's acceleration path today. Actual speed varies with resolution, steps, driver, software version and hardware.

### Low-VRAM

On 8 GB / 12 GB and similar VRAM-constrained setups, 4-bit weights cut weight-bandwidth demand significantly, adding extra speedup — up to roughly **11x**. Actual gains depend on VRAM capacity/bandwidth, offload behavior and generation settings.

## Swap one loader, keep your workflow

1. Install or update [ComfyUI-QuantFunc](https://github.com/QuantFunc/ComfyUI-QuantFunc).
2. Download the r128 or r32 weights.
3. Swap your model loader for the QuantFunc loader and pick the matching weight file.

Every other node, connection and generation parameter stays as-is.

Krea-2-Turbo is a distilled turbo model — use fewer sampling steps and turn CFG off (guidance 1.0).

## RTX 20-series through GB300, one build covers it all

Runs on every NVIDIA **SM75+** GPU: RTX 20/30/40/50-series, A100, H100, H200, B100, B200, GB300.

## Choose a model

| Variant | File | Size | Use case |
|---|---|---:|---|
| **r128** | `krea2-turbo-quantfunc-int4-r128.safetensors` | ~8.3 GB | Quality-first, recommended |
| **r32** | `krea2-turbo-quantfunc-int4-r32.safetensors` | ~7.8 GB | Size/VRAM-first |

## Loading

Weights use QuantFunc's own safetensors format — load with **ComfyUI-QuantFunc** or the **QuantFunc inference engine**, not as a drop-in Diffusers checkpoint. (This repo declares `library_name: diffusers` purely so Hugging Face counts real downloads of the flat `.safetensors` files above — see [HF's download-stats docs](https://huggingface.co/docs/hub/models-download-stats) — not because the files load via the `diffusers` package.)

## Source & license

This repository distributes derived quantized weights produced from:

- Base model: [krea/Krea-2-Turbo](https://huggingface.co/krea/Krea-2-Turbo)
- Pretrained base: [krea/Krea-2-Raw](https://huggingface.co/krea/Krea-2-Raw)

Weights follow the **Krea 2 Community License** — please read the original model's license terms before use.

## Community

- 🌐 [QuantFunc website](https://www.quantfunc.com/)
- 🐙 [ComfyUI-QuantFunc on GitHub](https://github.com/QuantFunc/ComfyUI-QuantFunc)
- 🎮 [Discord](https://discord.gg/jCp9TpFWcn)

	---
	license: other
	license_name: krea-2-community-license
	base_model:
	- krea/Krea-2-Turbo
	base_model_relation: quantized
	pipeline_tag: text-to-image
	library_name: diffusers
	tags:
	- text-to-image
	- image-generation
	- quantized
	- 4-bit
	- int4
	- turbo
	- krea
	- krea-2
	- quantfunc
	- comfyui
	---

	<div align="center" style="margin-top: 50px;">
	<a href="https://github.com/QuantFunc/ComfyUI-QuantFunc">
	<img src="https://raw.githubusercontent.com/QuantFunc/ComfyUI-QuantFunc/main/assets/logo.webp" width="300" alt="QuantFunc logo">
	</a>
	</div>

	<p align="center">
	🌐 <a href="https://www.quantfunc.com/">Website</a>  \|
	🐙 <a href="https://github.com/QuantFunc/ComfyUI-QuantFunc">GitHub</a>  \|
	🤗 <a href="https://huggingface.co/QuantFunc">Hugging Face</a>  \|
	🤖 <a href="https://www.modelscope.cn/profile/QuantFunc">ModelScope</a>  \|
	🎨 <a href="https://civitai.com/user/quantfunc">Civitai</a>  \|
	🎮 <a href="https://discord.gg/jCp9TpFWcn">Discord</a>
	</p>

	# Krea-2-QuantFunc-4bit

	4x compression, quality held.

	QuantFunc INT4 compresses Krea-2-Turbo to about a quarter of its 16-bit size. In our visual comparisons, composition, detail, color and style stay close to the 16-bit baseline, roughly on par with FP8 and INT8 ConvRot.

	## Showcase

	All images below were generated by Krea-2-QuantFunc-4bit.

	\| Portrait photography \| Sci-fi scene \|
	\|---\|---\|
	\| ![Portrait](https://huggingface.co/QuantFunc/Krea-2-QuantFunc-4bit/resolve/main/assets/krea2_show.webp) \| ![Sci-fi](https://huggingface.co/QuantFunc/Krea-2-QuantFunc-4bit/resolve/main/assets/krea2_show2.webp) \|
	\| Impasto art \| Watercolor illustration \|
	\| ![Impasto](https://huggingface.co/QuantFunc/Krea-2-QuantFunc-4bit/resolve/main/assets/krea2_show3.webp) \| ![Watercolor](https://huggingface.co/QuantFunc/Krea-2-QuantFunc-4bit/resolve/main/assets/krea2_show4.webp) \|

	## Fast denoising, fast end-to-end too

	### High-VRAM

	On an RTX 4090, same workflow and generation settings:

	\| Stage \| QuantFunc INT4 \| FP8 \| Speedup \|
	\|---\|---:\|---:\|---:\|
	\| Denoising \| 1.6s \| 5.0s \| 3.13x \|
	\| End-to-end \| 2.5s \| 6.5s \| 2.6x \|

	> End-to-end includes text encoder, denoising and VAE. Text encoder and VAE are not part of the QuantFunc plugin's acceleration path today. Actual speed varies with resolution, steps, driver, software version and hardware.

	### Low-VRAM

	On 8 GB / 12 GB and similar VRAM-constrained setups, 4-bit weights cut weight-bandwidth demand significantly, adding extra speedup — up to roughly 11x. Actual gains depend on VRAM capacity/bandwidth, offload behavior and generation settings.

	## Swap one loader, keep your workflow

	1. Install or update [ComfyUI-QuantFunc](https://github.com/QuantFunc/ComfyUI-QuantFunc).
	2. Download the r128 or r32 weights.
	3. Swap your model loader for the QuantFunc loader and pick the matching weight file.

	Every other node, connection and generation parameter stays as-is.

	Krea-2-Turbo is a distilled turbo model — use fewer sampling steps and turn CFG off (guidance 1.0).

	## RTX 20-series through GB300, one build covers it all

	Runs on every NVIDIA SM75+ GPU: RTX 20/30/40/50-series, A100, H100, H200, B100, B200, GB300.

	## Choose a model

	\| Variant \| File \| Size \| Use case \|
	\|---\|---\|---:\|---\|
	\| r128 \| `krea2-turbo-quantfunc-int4-r128.safetensors` \| ~8.3 GB \| Quality-first, recommended \|
	\| r32 \| `krea2-turbo-quantfunc-int4-r32.safetensors` \| ~7.8 GB \| Size/VRAM-first \|

	## Loading

	Weights use QuantFunc's own safetensors format — load with ComfyUI-QuantFunc or the QuantFunc inference engine, not as a drop-in Diffusers checkpoint. (This repo declares `library_name: diffusers` purely so Hugging Face counts real downloads of the flat `.safetensors` files above — see [HF's download-stats docs](https://huggingface.co/docs/hub/models-download-stats) — not because the files load via the `diffusers` package.)

	## Source & license

	This repository distributes derived quantized weights produced from:

	- Base model: [krea/Krea-2-Turbo](https://huggingface.co/krea/Krea-2-Turbo)
	- Pretrained base: [krea/Krea-2-Raw](https://huggingface.co/krea/Krea-2-Raw)

	Weights follow the Krea 2 Community License — please read the original model's license terms before use.

	## Community

	- 🌐 [QuantFunc website](https://www.quantfunc.com/)
	- 🐙 [ComfyUI-QuantFunc on GitHub](https://github.com/QuantFunc/ComfyUI-QuantFunc)
	- 🎮 [Discord](https://discord.gg/jCp9TpFWcn)