Boogu-Image-0.1-Turbo-hotfix โ INT8 Quantized
INT8 tensor-wise quantization of Boogu-Image-0.1-Turbo-hotfix, produced with 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 โ 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_quantmetadata 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
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
- Place the
.safetensorsfile inComfyUI/models/diffusion_models/ - Load it with the Load Diffusion Model (UNETLoader) node
- Use the standard Boogu Turbo workflow:
- Text encoder:
qwen3vl_8b_fp8_scaled.safetensors - VAE:
flux1_vae_bf16.safetensors - Steps: 4 (Turbo default)
- Text encoder:
- 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 by the Boogu team (Apache-2.0)
- Quantization tooling: silveroxides/convert_to_quant
License
Apache-2.0, inherited from the base Boogu-Image-0.1 model.
Model tree for Winnougan/Boogu-INT8
Base model
Boogu/Boogu-Image-0.1-Turbo