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license: other
license_name: krea-2-license
license_link: https://www.krea.ai/krea-2-licensing
pipeline_tag: text-to-image
library_name: diffusers
tags:
- text-to-image
- image-generation
- dit
- fp8
- comfyui
- diffusers
- krea
- krea2
---
# Krea 2 OSS - Optimized FP8 Weights (Turbo)
This repository provides an optimized **FP8 (float8_e4m3fn) weight-only quantized version** of the newly released **Krea 2 OSS (Turbo)** transformer.
This optimization reduces the model size from the original **24.76 GiB (BF16)** down to **12.01 GiB**, making it highly accessible and runnable on standard consumer hardware (such as 16GB and 24GB GPUs) without sacrificing output quality.
## ⚠️ Licensing & Disclaimer
- **Original Model Creators**: All credit goes to [KREA.ai](https://www.krea.ai) for the original research, architecture, and weights.
- **License**: This model is subject to the **KREA 2 License Agreement**. Please read and comply with the official license terms before using these weights: [KREA 2 Licensing Terms](https://www.krea.ai/krea-2-licensing).
- **Purpose**: This repository is a community-contributed utility. It does not claim ownership of the original model or architecture. Its sole purpose is to provide optimized, consumer-hardware-friendly weights for the open-source community.
---
## 🛠️ Quantization Details (Quality-First FP8)
Unlike generic global quantization scripts that aggressively convert every parameter (which often degrades generation details or introduces NaN/promotion calculation errors in neural networks), this model was quantized using a **selective weight-only strategy**:
1. **Targeted Quantization**: Only 2D floating-point weight matrices (`.weight` keys with `ndim >= 2` and element count `> 1024`) were quantized to `torch.float8_e4m3fn`.
2. **Preserved Precision**:
- All 1D vectors, biases, and normalization scales are kept in their native high-precision (`float32` / `bfloat16`).
- Highly sensitive projection/modulation layers (such as `LastLayer.modulation.lin` vectors) are **completely preserved** in high-precision. This prevents typical mathematical promotion bugs (such as `BFloat16` and `Float8` promotion issues in PyTorch) and retains original output fidelity.
3. **Weight Comparison**:
- **Tensors Quantized to FP8**: 266 tensors.
- **Tensors Kept in Native Precision**: 166 tensors.
- **Size Reduction**: **24.76 GiB ➔ 12.01 GiB** (~51.5% VRAM / disk savings!).
---
## 🖼️ Sample Generations
Below are official sample outputs from the original Krea 2 OSS Turbo model (generated with the same BF16 weights this FP8 conversion is based on):
| | | |
|:-------------------------:|:-------------------------:|:-------------------------:|
|  |  |  |
| **3D** | **Anime** | **Beach** |
|  |  |  |
| **Blocks** | **Cel** | **Dog** |
|  |  |  |
| **Face** | **Flowers** | **Fox** |
|  |  |  |
| **Future** | **Goldface** | **Jester** |
|  |  |  |
| **Mouse** | **Red** | **Ride** |
|  |  |  |
| **Sailor** | **Statue** | **Takeoff** |
|  |  | |
| **Tree** | **Wind** | |
---
## 🚀 How to Use in ComfyUI (Native — 0.25.0+)
ComfyUI 0.25.0+ has **built-in Krea2 support**. No custom nodes needed.
Drop the workflow JSON into ComfyUI and drag it to the canvas.
### 1. Download Required Files
Place these in your `ComfyUI/models/` folder:
| File | Folder | Source |
|------|--------|--------|
| `krea2_turbo_fp8.safetensors` | `unet/` | [AlperKTS/Krea2_FP8](https://huggingface.co/AlperKTS/Krea2_FP8) ← You are here |
| `qwen3vl_4b_fp8_scaled.safetensors` | `text_encoders/` | [Comfy-Org/Qwen3-VL](https://huggingface.co/Comfy-Org/Qwen3-VL/tree/main/text_encoders) |
| `qwen_image_vae.safetensors` | `vae/` | [Comfy-Org/Qwen-Image_ComfyUI](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/tree/main/split_files/vae) |
### 2. Load the Workflow
Drag [`workflows/Krea 2 simple workflow.json`](workflows/Krea%202%20simple%20workflow.json) onto your ComfyUI canvas.
### 3. Queue & Generate!
Turbo defaults: **8 steps, CFG 1.0, `er_sde` sampler, `simple` scheduler, 1280×720.**
---
## 🤝 Acknowledgements
Special thanks to the **KREA.ai** team for releasing Krea 2 to the open-source community. For any commercial licensing inquiries or details about the model, please visit [krea.ai](https://www.krea.ai).
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