---
license: apache-2.0
base_model:
  - Boogu/Boogu-Image-0.1-Turbo
tags:
  - text-to-image
  - image-generation
  - quantized
  - int8
  - boogu
  - comfyui
---

# Boogu-Image-0.1-Turbo-hotfix — INT8 Quantized

![Example output](https://huggingface.co/Winnougan/Boogu-INT8/resolve/main/Promotion/Boogu_00001_.png)

INT8 tensor-wise quantization of [Boogu-Image-0.1-Turbo-hotfix](https://huggingface.co/Boogu/Boogu-Image-0.1-Turbo), produced with [`convert_to_quant`](https://github.com/silveroxides/convert_to_quant).

This is the four-step distilled Turbo variant of the Boogu-Image-0.1 family, quantized to INT8 for reduced VRAM usage and faster loading while preserving output quality.

## Quantization Details

- **Format:** INT8, tensor-wise scaling (`int8_tensorwise`)
- **Method:** Simple quantization (no learned rounding / SVD optimization)
- **ConvRot:** Not applied — Boogu's attention/feed-forward layer dimensions (840, 3360) are not compatible with ConvRot's group-size requirements (group size must be a power of 4 and evenly divide `in_features`)
- **Metadata:** Includes `comfy_quant` metadata for native ComfyUI compatibility

### Excluded Layers (kept in BF16)

The following layers were kept at full precision rather than quantized, based on community guidance for this architecture:

```
image_index_embedding
ref_image_patch_embedder.weight
*.norm1.linear.weight (all blocks)
norm_out.linear_1.weight
norm_out.linear_2.weight
```

These are embedding and normalization/modulation layers, which are commonly excluded from quantization to preserve generation quality and avoid instability.

### Conversion Command

```bash
ctq -i boogu_image_turbo_hotfix_bf16.safetensors \
    -o boogu_image_turbo_hotfix_int8.safetensors \
    --int8 --scaling_mode tensor --simple --low-memory \
    --comfy_quant --save-quant-metadata \
    --exclude-layers "(image_index_embedding|ref_image_patch_embedder|norm1\.linear|norm_out)"
```

## Usage in ComfyUI

1. Place the `.safetensors` file in `ComfyUI/models/diffusion_models/`
2. Load it with the **Load Diffusion Model (UNETLoader)** node
3. Use the standard Boogu Turbo workflow:
   - Text encoder: `qwen3vl_8b_fp8_scaled.safetensors`
   - VAE: `flux1_vae_bf16.safetensors`
   - Steps: 4 (Turbo default)
4. **Note:** The first generation after loading may take significantly longer (several minutes) due to one-time kernel warmup for this model's tensor shapes. Subsequent generations run at normal speed.

Requires a reasonably recent ComfyUI build with INT8 tensor-wise (`int8_tensorwise`) support. If you hit a `KeyError` related to quantization format on load, update ComfyUI or check that your build supports this format.

## Credits

- Base model: [Boogu-Image-0.1](https://github.com/boogu-project/Boogu-Image) by the Boogu team (Apache-2.0)
- Quantization tooling: [silveroxides/convert_to_quant](https://github.com/silveroxides/convert_to_quant)

## License

Apache-2.0, inherited from the base Boogu-Image-0.1 model.