Krea 2 — INT8 ConvRot
INT8
ConvRot quantized weights for
Krea 2 (K2), for fast, low-VRAM
inference in ComfyUI via the
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.
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 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).
- VAE:
qwen_image_vae.safetensors → ComfyUI/models/vae/
(from 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 fileon_the_fly_quantization: false (already quantized)enable_convrot: truemodel_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 (base model) ·
BobJohnson24/ComfyUI-INT8-Fast (INT8 ConvRot method).
