license: other
license_name: krea-2-community-license
license_link: https://huggingface.co/krea/Krea-2-Turbo
tags:
- krea2
- diffusion
- dit
- comfyui
- int8
- int8_tensorwise
- convrot
- quantization
base_model:
- krea/Krea-2-Turbo
- krea/Krea-2
Krea 2 INT8 ConvRot (native int8_tensorwise)
Native ComfyUI INT8 ConvRot checkpoints for Krea 2 Turbo and Krea 2 Raw,
quantized from the official BF16 weights so they load with the stock
Load Diffusion Model (UNETLoader) node — no OTUNetLoaderW8A8 /
ComfyUI-INT8-Fast custom loader required.
Files
| File | Size | Source BF16 | Notes |
|---|---|---|---|
Krea2-Turbo-int8-ConvRot.safetensors |
~13.2 GB | krea2_turbo_bf16.safetensors (Comfy-Org/Krea-2) |
8-step distilled |
Krea2-Raw-int8-ConvRot.safetensors |
~13.2 GB | krea2_raw_bf16.safetensors |
Undistilled base |
Place both under ComfyUI/models/diffusion_models/.
Per-tensor metadata (.comfy_quant JSON)
{
"format": "int8_tensorwise",
"orig_dtype": "torch.bfloat16",
"convrot": true,
"convrot_groupsize": 256,
"per_row": true
}
Older “INT8-Fast” exports that only carry
{"convrot": true, "per_row": true} (no "format": "int8_tensorwise")
do not load in stock ComfyUI ≥ 0.27 — this repo replaces those.
Requirements
- ComfyUI ≥ 0.27.0 (native
int8_tensorwise+ ConvRot) - comfy-kitchen with INT8 kernels (shipped with current ComfyUI)
- NVIDIA GPU with INT8 tensor cores (RTX 30 / 40 / 50, SM ≥ 7.5)
- Companion assets (unchanged): Qwen3-VL text encoder + Qwen Image VAE
Usage (ComfyUI)
- Drop the
.safetensorsintomodels/diffusion_models/ - Use Load Diffusion Model (
UNETLoader),weight_dtype: default - Standard Krea 2 graph: CLIPLoader (
type: krea2) → CLIPTextEncode → KSampler / FLS → VAEDecode
LoRAs: use a normal LoRA stack / LoraLoader on the MODEL output. Prefer
clip_strength = 0 for Krea UNet-only LoRAs so text encode can cache.
Conversion (reproduce)
ctq -i krea2_turbo_bf16.safetensors \
-o Krea2-Turbo-int8-ConvRot.safetensors \
--int8 --convrot --convrot-group-size 256 \
--scaling_mode row \
--comfy_quant --save-quant-metadata --krea2 \
--simple --low-memory --device cuda
Same for Raw (krea2_raw_bf16.safetensors). --scaling_mode row is mandatory.
Verify after convert
from safetensors import safe_open
import json
with safe_open("Krea2-Turbo-int8-ConvRot.safetensors", framework="pt") as f:
raw = f.get_tensor([k for k in f.keys() if k.endswith(".comfy_quant")][0]).tolist()
print(json.loads(bytes(raw)))
# Must include: format=int8_tensorwise, convrot=True, per_row=True, convrot_groupsize=256
Provenance
- Upstream Turbo: krea/Krea-2-Turbo / Comfy packaging Comfy-Org/Krea-2
- Upstream Raw: Krea 2 Raw BF16 (Comfy-Org packaging)
- Quant tool: silveroxides/convert_to_quant (
ctq) - Quant date: 2026-08-20
- Architecture profile:
--krea2(sensitive first/last/modulation layers kept high precision)
License
Follow the upstream Krea 2 Community License for the base models. This repo only redistributes lossy INT8+ConvRot re-quantizations of those weights.