import torch
from diffusers import ZImagePipeline, AutoencoderKL, FlowMatchEulerDiscreteScheduler
from transformers import Qwen3Model, AutoTokenizer
from sdnq import load_sdnq_model

model_path = "Tongyi-MAI_Z-Image-Turbo-int8"

# Load transformer with SDNQ (quantized to 8-bit)
transformer = load_sdnq_model(
    f"{model_path}/transformer",
    model_cls=ZImageTransformer2DModel,
    device="cpu"
)

# Load other components from this model (all included!)
vae = AutoencoderKL.from_pretrained(f"{model_path}/vae", torch_dtype=torch.float16)
text_encoder = Qwen3Model.from_pretrained(f"{model_path}/text_encoder", torch_dtype=torch.float16)
tokenizer = AutoTokenizer.from_pretrained(f"{model_path}/tokenizer")
scheduler = FlowMatchEulerDiscreteScheduler.from_pretrained(f"{model_path}/scheduler")

# Construct pipeline
pipe = ZImagePipeline(
    transformer=transformer,
    vae=vae,
    text_encoder=text_encoder,
    tokenizer=tokenizer,
    scheduler=scheduler,
)

pipe.to("cuda")

# Generate an image
image = pipe(
    prompt="A serene mountain landscape at sunrise",
    num_inference_steps=20,
).images[0]
image.save("output.png")

Components

✅ transformer (ZImageTransformer2DModel) - Quantized to 8-bit
✅ vae (AutoencoderKL) - Quantized to 8-bit

Note: Some components are included unquantized due to SDNQ library limitations:

📦 text_encoder - Included unquantized (SDNQ bug workaround)

Quantization Details

Original model: Tongyi-MAI/Z-Image-Turbo
Quantization: 8-bit
Quantizer: SDNQ
Date: 2026-01-18 13:41:50

Size Reduction

Original: ~30GB (estimated)
Quantized: See individual component sizes

Notes

This is a complete drop-in replacement - all components included
SDNQ quantization provides excellent quality at reduced size
Requires sdnq library to be installed: pip install sdnq
Quality loss is minimal with 8-bit quantization
Some components may be included unquantized due to library limitations

Quantized with BugQuant

TheCodingBug/Z-Image-Turbo-int8

Tongyi-MAI/Z-Image-Turbo - Quantized (8-bit)

Overview

Architecture

Usage

Components

Quantization Details

Size Reduction

Notes

TheCodingBug/
Z-Image-Turbo-int8