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license: other
license_name: krea-2-community-license
license_link: https://www.krea.ai/krea-2-licensing
base_model: krea/Krea-2
tags:
- text-to-image
- krea
- krea2
- int8
- convrot
- comfyui
- quantized
---
# Krea 2 — INT8 ConvRot
INT8 **ConvRot** quantized weights for **[Krea 2 (K2)](https://www.krea.ai/krea-2)**, for fast, low-VRAM
inference in ComfyUI via the [ComfyUI-INT8-Fast](https://github.com/BobJohnson24/ComfyUI-INT8-Fast) node.
> **This is a modified (quantized) version of the Krea 2 model.** It is **not** an official Krea release and is
> **not** endorsed by Krea. The original weights are © Krea, licensed under the
> [Krea 2 Community License](https://www.krea.ai/krea-2-licensing).
ConvRot is a near-lossless INT8 scheme (~GGUF-Q8 quality) that runs on the INT8 tensor cores of any NVIDIA GPU
with sufficient INT8 TOPS (RTX 30-series and up). On a 3090, INT8 is meaningfully faster than FP8 (which has no
tensor-core acceleration on Ampere) and roughly half the VRAM of BF16.
## Models
| File | Precision | Size | Use |
|------|-----------|------|-----|
| `Krea2-Turbo-int8-ConvRot.safetensors` | INT8 ConvRot | 14.1 GB | 8-step distilled, fast text-to-image |
| `Krea2-Raw-int8-ConvRot.safetensors` | INT8 ConvRot | 14.1 GB | Undistilled base — fine-tuning / LoRA training / research |
Original BF16 checkpoints are ~26.6 GB each. Quantized with the K2 profile: the 28 main DiT blocks are INT8,
while the sensitive layers (`first`, `last`, `tmlp`, `tproj`, `txtfusion`, `txtmlp`) are kept in high precision.
## Requirements
- **ComfyUI ≥ 0.25.0** (native Krea 2 support).
- **[ComfyUI-INT8-Fast](https://github.com/BobJohnson24/ComfyUI-INT8-Fast)** custom node (with a `krea2`
model-type profile — see note below).
- Text encoder: **`qwen3vl_4b_fp8_scaled.safetensors`** → `ComfyUI/models/text_encoders/`
(from [Comfy-Org/Qwen3-VL](https://huggingface.co/Comfy-Org/Qwen3-VL)).
- VAE: **`qwen_image_vae.safetensors`** → `ComfyUI/models/vae/`
(from [Comfy-Org/Qwen-Image_ComfyUI](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI)).
- Put the INT8 `.safetensors` in `ComfyUI/models/diffusion_models/`.
> **Note on the `krea2` profile:** Krea 2 is newer than INT8-Fast's built-in model list. These weights were
> produced with a small added `krea2` exclusion profile (keep `first`/`last`/`tmlp`/`tproj`/`txtfusion`/`txtmlp`
> in high precision). Loading the *pre-quantized* files here does not require that profile — ConvRot metadata
> is embedded per-layer — but reproducing the conversion does.
## Usage
Load with **Load Diffusion Model INT8 (W8A8)** (`OTUNetLoaderW8A8`):
- `unet_name`: the INT8 file
- `on_the_fly_quantization`: **false** (already quantized)
- `enable_convrot`: **true**
- `model_type`: `krea2`
Then the standard K2 graph: `CLIPLoader (type: krea2)` → `VAELoader` → `CLIPTextEncode` → `KSampler` → `VAEDecode`.
Recommended sampler settings:
- **Turbo:** 8 steps, CFG 1.0, `euler` / `simple`, shift 1.15 (model default).
- **Raw:** ~52 steps, CFG ~3.5, `euler` / `simple` (undistilled base; mainly for training).
## Quantization
- **Method:** INT8 ConvRot (row-wise INT8 with convolutional rotation), via ComfyUI-INT8-Fast.
- **Compute:** `torch._int_mm` on INT8 tensor cores; Triton kernels.
- **Quality:** near-lossless vs BF16/FP8 in testing (verified by generation).
## License & attribution
Krea 2 is licensed under the **Krea 2 Community License Agreement**,
Copyright © Krea, Inc. All Rights Reserved. See `LICENSE` / https://www.krea.ai/krea-2-licensing.
These files are a **quantized derivative** of Krea 2; the Krea 2 model name is retained per the license.
Commercial use is permitted only for entities under $1M USD trailing-twelve-month revenue; above that an
Enterprise License from Krea is required. **Deployers must implement reasonable content-filtering** (e.g.
NudeNet, Falconsai/nsfw_image_detection, Hive, or human review) to prevent prohibited content, and disclose
AI-generated outputs where required.
**Credits:** [Krea](https://www.krea.ai) (base model) · [BobJohnson24/ComfyUI-INT8-Fast](https://github.com/BobJohnson24/ComfyUI-INT8-Fast) (INT8 ConvRot method).
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