🎨 Text to Image

Z-Image-Turbo

Tongyi-MAI/Z-Image-Turbo

Get AI Model →
1.2M
Downloads
❤️
4.5K
Likes
🏷️
11
Tags
📦
diffusers
Library
Model Details
Full Model IDTongyi-MAI/Z-Image-Turbo
Pipeline / Tasktext-to-image
Librarydiffusers
Downloads (all-time)1.2M
Likes4.5K
Last Modified1/30/2026
Author / OrgTongyi-MAI
PrivateNo — public
⚡ Quick Usage (Python)

Using the 🤗 Transformers library. Install with pip install transformers

from transformers import pipeline

# Load the model
pipe = pipeline("text-to-image", model="Tongyi-MAI/Z-Image-Turbo")

# Run inference
result = pipe("Your input here")
print(result)
🏷️ Tags
diffuserssafetensorstext-to-imageenarxiv:2511.22699arxiv:2511.22677arxiv:2511.13649license:apache-2.0diffusers:ZImagePipelinedeploy:azureregion:us
More Text to Image Models
See all →
stable-diffusion-xl-base-1.0

stabilityai/stable-diffusion-xl-base-1.0

2.0M❤️ 7.6K
Get AI Model →
stable-diffusion-v1-5

stable-diffusion-v1-5/stable-diffusion-v1-5

1.5M❤️ 1.1K
Get AI Model →
FLUX.2-klein-base-4B

black-forest-labs/FLUX.2-klein-base-4B

1.5M❤️ 126
Get AI Model →
🚀 Use This Model

Access model files, inference API, and full documentation on Hugging Face.

Open on Hugging Face →Browse Model Files ↗← Browse All Models
🎨 Task: Text to Image

This model is designed for the Text to Image task. Explore more models for this use case.

All Text to Image Models →
📊 Popularity
Downloads1.2M
❤️ Community Likes4.5K
🛠️ Requirements
  • Install: pip install diffusers
  • Python 3.8+ recommended for Transformers.
  • GPU (CUDA) speeds up inference significantly.
  • Use model.half() for fp16 on limited VRAM.
👋 Need help with code?