Instructions to use martin-rizzo/Z-Image-Turbo-INT8-ConvRot-ComfyUI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusion Single File
How to use martin-rizzo/Z-Image-Turbo-INT8-ConvRot-ComfyUI with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Z-Image-Turbo INT8-ConvRot (ComfyUI)
This repository provides an INT8-ConvRot quantized version of the Z-Image-Turbo diffusion model. It has been specifically tailored for fast text-to-image generation within ComfyUI (or any other compatible image generation application).
The ConvRot technique applies a rotational transformation to weights and activations, effectively suppressing outliers before INT8 quantization. This process, combined with the quantization itself, enables a significant reduction in VRAM usage while maintaining excellent prompt comprehension and high-quality image generation comparable to the original BF16 weights.
Model Specifications
- Model Type: Scalable Single-Stream Diffusion Transformer (S3-DiT)
- Model Size: 6 Billion (6B) Parameters
- Base Model: Tongyi-MAI/Z-Image-Turbo
- Quantization: INT8-ConvRot (FP32 Scales) with Mixed BF16 Precision
Provided Files
z_image_turbo_int8_convrot_bf16emixed.safetensors: Quantized model weights in INT8-ConvRot format with FP32 scales, preserving mixed BF16 precision in some layers.
Installation Instructions for ComfyUI
To utilize this checkpoint as a Diffusion Model within your workflow, follow these steps:
- Download the "
z_image_turbo_int8_convrot_bf16emixed.safetensors" file. - Place the file into the corresponding diffusion models directory of your ComfyUI installation. The path is typically: "
ComfyUI/models/diffusion_models/" (or /unet depending on your version). - In the ComfyUI interface, load this file using a standard 'Load Diffusion Model' node.
Note: No special ConvRot-aware custom nodes are required. ComfyUI supports this type of quantization natively starting from version v0.27.0
Production Details
This quantized file was generated from the original checkpoint provided by Tongyi-MAI [Tongyi-MAI/Z-Image-Turbo]. The conversion was performed using the z2comfy utility with the following command:
./z2comfy.sh Z-Image-Turbo --int8convrot --scales-dtype FP32 --scales-trials 32 --mixed-dtype BF16E --mixed-small
Note: The z2comfy command is an experimental utility developed for personal use. It is not fully polished yet and may present some issues, but it is available for download at: https://github.com/martin-rizzo/ZImageCkptTools
References
- Base Model: Tongyi-MAI/Z-Image-Turbo
- Tools: ZImageCkptTools
- ConvRot Text-Encoder: martin-rizzo/Qwen3-4B-INT8-ConvRot-ComfyUI
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