README.md

---
tags:
- int8-convrot
- comfyui
---

# ComfyUI-Native-Int8-ConvRot

INT8 ConvRot models, converted to the native quantization format ComfyUI expects.

INT8 ConvRot currently offers one of the best quality-to-performance ratios of any
quantization method. In my personal experience, INT8 ConvRot models provide quality
close to BF16 at generation speeds matching or beating FP8_Scaled.

> "INT8 ConvRot is row-wise INT8 with parameters and activations rotated before
> quantization via ConvRot."
> — [ComfyUI-INT8-Fast Metrics.md](https://github.com/BobJohnson24/ComfyUI-INT8-Fast/blob/main/Metrics.md)

## Models
If there is a model that you would like that is not in this list, make a [request](https://huggingface.co/obsxrver/ComfyUI-Native-INT8_ConvRot/discussions)
| File | Model | Original Creator's Repo |
|---|---|---|
| [`checkpoints/hidream_o1_image_int8-convrot.safetensors`](https://huggingface.co/obsxrver/ComfyUI-Native-INT8_ConvRot/blob/main/checkpoints/hidream_o1_image_int8-convrot.safetensors) | HiDream-O1-Image | [HiDream-ai/HiDream-O1-Image](https://huggingface.co/HiDream-ai/HiDream-O1-Image) |
| [`checkpoints/hidream_o1_image_dev_int8-convrot.safetensors`](https://huggingface.co/obsxrver/ComfyUI-Native-INT8_ConvRot/blob/main/checkpoints/hidream_o1_image_dev_int8-convrot.safetensors) | HiDream-O1-Image-Dev | [HiDream-ai/HiDream-O1-Image-Dev](https://huggingface.co/HiDream-ai/HiDream-O1-Image-Dev) |
| [`checkpoints/ltx-2.3-22b-dev-int8-ConvRot.safetensors`](https://huggingface.co/obsxrver/ComfyUI-Native-INT8_ConvRot/blob/main/checkpoints/ltx-2.3-22b-dev-int8-ConvRot.safetensors) | LTX-2.3 22B Dev | [Lightricks/LTX-2.3](https://huggingface.co/Lightricks/LTX-2.3) |
| [`checkpoints/ltx-2.3-22b-distilled-1.1-int8-ConvRot.safetensors`](https://huggingface.co/obsxrver/ComfyUI-Native-INT8_ConvRot/blob/main/checkpoints/ltx-2.3-22b-distilled-1.1-int8-ConvRot.safetensors) | LTX-2.3 22B Distilled v1.1 | [Lightricks/LTX-2.3](https://huggingface.co/Lightricks/LTX-2.3) |
| [`checkpoints/sulphur_dev_INT8_ConvRot.safetensors`](https://huggingface.co/obsxrver/ComfyUI-Native-INT8_ConvRot/blob/main/checkpoints/sulphur_dev_INT8_ConvRot.safetensors) | Sulphur 2 Dev | [SulphurAI/Sulphur-2-base](https://huggingface.co/SulphurAI/Sulphur-2-base) |
| [`checkpoints/sulphur_distill_INT8_ConvRot.safetensors`](https://huggingface.co/obsxrver/ComfyUI-Native-INT8_ConvRot/blob/main/checkpoints/sulphur_distill_INT8_ConvRot.safetensors) | Sulphur 2 Distill | [SulphurAI/Sulphur-2-base](https://huggingface.co/SulphurAI/Sulphur-2-base) |
| [`diffusion_models/anima-preview3-base-int8-ConvRot.safetensors`](https://huggingface.co/obsxrver/ComfyUI-Native-INT8_ConvRot/blob/main/diffusion_models/anima-preview3-base-int8-ConvRot.safetensors) | Anima Preview 3 (Base) | [circlestone-labs/Anima](https://huggingface.co/circlestone-labs/Anima) |
| [`diffusion_models/flux-2-klein-9b_int8_convrot.safetensors`](https://huggingface.co/obsxrver/ComfyUI-Native-INT8_ConvRot/blob/main/diffusion_models/flux-2-klein-9b_int8_convrot.safetensors) | FLUX.2 [klein] 9B | [black-forest-labs/FLUX.2-klein-9B](https://huggingface.co/black-forest-labs/FLUX.2-klein-9B) |
| [`diffusion_models/Krea2-Turbo-int8-ConvRot.safetensors`](https://huggingface.co/obsxrver/ComfyUI-Native-INT8_ConvRot/blob/main/diffusion_models/Krea2-Turbo-int8-ConvRot.safetensors) | Krea 2 Turbo | [krea/Krea-2-Turbo](https://huggingface.co/krea/Krea-2-Turbo) |
| [`diffusion_models/qwen-image-2512-int8-ConvRot.safetensors`](https://huggingface.co/obsxrver/ComfyUI-Native-INT8_ConvRot/blob/main/diffusion_models/qwen-image-2512-int8-ConvRot.safetensors) | Qwen-Image-2512 | [Qwen/Qwen-Image-2512](https://huggingface.co/Qwen/Qwen-Image-2512) |
| [`diffusion_models/wan2.2_i2v_high_int8_convrot.safetensors`](https://huggingface.co/obsxrver/ComfyUI-Native-INT8_ConvRot/blob/main/diffusion_models/wan2.2_i2v_high_int8_convrot.safetensors) | Wan2.2 I2V A14B (High Noise) | [Wan-AI/Wan2.2-I2V-A14B](https://huggingface.co/Wan-AI/Wan2.2-I2V-A14B) |
| [`diffusion_models/wan2.2_i2v_low_int8_convrot.safetensors`](https://huggingface.co/obsxrver/ComfyUI-Native-INT8_ConvRot/blob/main/diffusion_models/wan2.2_i2v_low_int8_convrot.safetensors) | Wan2.2 I2V A14B (Low Noise) | [Wan-AI/Wan2.2-I2V-A14B](https://huggingface.co/Wan-AI/Wan2.2-I2V-A14B) |
| [`diffusion_models/wan2.2_t2v_high_int8_ConvRot.safetensors`](https://huggingface.co/obsxrver/ComfyUI-Native-INT8_ConvRot/blob/main/diffusion_models/wan2.2_t2v_high_int8_ConvRot.safetensors) | Wan2.2 T2V A14B (High Noise) | [Wan-AI/Wan2.2-T2V-A14B](https://huggingface.co/Wan-AI/Wan2.2-T2V-A14B) |
| [`diffusion_models/wan2.2_t2v_low_int8_ConvRot.safetensors`](https://huggingface.co/obsxrver/ComfyUI-Native-INT8_ConvRot/blob/main/diffusion_models/wan2.2_t2v_low_int8_ConvRot.safetensors) | Wan2.2 T2V A14B (Low Noise) | [Wan-AI/Wan2.2-T2V-A14B](https://huggingface.co/Wan-AI/Wan2.2-T2V-A14B) |
| [`diffusion_models/z_image_turbo_int8_convrot.safetensors`](https://huggingface.co/obsxrver/ComfyUI-Native-INT8_ConvRot/blob/main/diffusion_models/z_image_turbo_int8_convrot.safetensors) | Z-Image Turbo | [Tongyi-MAI/Z-Image-Turbo](https://huggingface.co/Tongyi-MAI/Z-Image-Turbo) |

## Quality Ranking

Per the latent-divergence benchmarks in [Metrics.md](https://github.com/BobJohnson24/ComfyUI-INT8-Fast/blob/main/Metrics.md):

```
GGUF Q8 > INT8 ConvRot > MXFP8 > FP8 >= INT8 Row > INT8 Tensorwise
```

Note: this is the general takeaway across all tested models. In several individual
benchmarks (e.g. Anima, Flux2 Klein 9B, Qwen Image 2512), INT8 ConvRot actually
scored *better* than GGUF Q8.

## Requirements

- A ComfyUI version that includes native INT8 support
  ([Comfy-Org/ComfyUI#14636](https://github.com/Comfy-Org/ComfyUI/pull/14636),
  merged June 2026). Update if your loader reports an invalid quantization type.
- Models load with the standard **Load Diffusion Model** node — no custom node needed.

## How to Quantize a Model to INT8 ConvRot

1. Install silveroxides' [convert_to_quant](https://github.com/silveroxides/convert_to_quant):

   ```bash
   pip install -U convert-to-quant
   ```

   > INT8 kernels require Triton (native on Linux; use `triton-windows` on Windows).
   > PyTorch must be installed separately with the correct CUDA version.

2. Convert the model:

   ```bash
   ctq -i source_model_bf16.safetensors -o converted_model_int8_convrot.safetensors \
     --int8 --scaling_mode row --simple --convrot --convrot-group-size [64,256,1024] \
     --comfy_quant --save-quant-metadata --<model-arch-flag>
   ```

### Notes

- `--convrot-group-size` accepts 64, 256, or 1024. **It is recommended to choose a value that divides evenly into all of the model's layer dimensions.**
- `--<model-arch-flag>` selects the layer-exclusion preset for your model architecture
  (e.g. `--wan`, `--flux2`, `--zimage`). Run `ctq --help-filters` (or `ctq -hf`) for
  the full list.

## References

1. [Reddit: "So is INT8-ConvRot the new hot thing?"](https://www.reddit.com/r/StableDiffusion/comments/1uimp1j/so_is_int8convrot_the_new_hot_thing/)
2. [ComfyUI-INT8-Fast — Metrics.md](https://github.com/BobJohnson24/ComfyUI-INT8-Fast/blob/main/Metrics.md) (benchmark methodology & full tables)
3. [Comfy-Org/Boogu-Image discussion #10](https://huggingface.co/Comfy-Org/Boogu-Image/discussions/10#6a404ed359b6d5b4e834a644)
4. [ComfyUI PR #14636 — Support int8 models](https://github.com/Comfy-Org/ComfyUI/pull/14636)
5. [bertbobson/ComfyUI-INT8_ConvRot](https://huggingface.co/bertbobson/ComfyUI-INT8_ConvRot)
6. [silveroxides/convert_to_quant](https://github.com/silveroxides/convert_to_quant)

## Licensing and Commercial Use
All models are distributed strictly under their upstream license with no added restrictions. Verify permissibility with the original creator before commercial use.