README.md

metadata

title: HunyuanImage-3.0
emoji: 🎨
colorFrom: purple
colorTo: blue
sdk: gradio
sdk_version: 5.44.0
app_file: app.py
pinned: false
short_description: Text-to-Image generation using Tencent HunyuanImage-3.0

🎨 HunyuanImage-3.0 Text-to-Image with Inference API

This Space provides an interface for the Tencent HunyuanImage-3.0 model using Hugging Face Inference API (paid from your account balance).

✅ What's New

• Real image generation using HF Inference API
• n8n integration via REST API endpoint
• Base64 image output for easy integration
• Automatic token-based authentication

🔧 Setup Instructions

1. Get Your HF Token

1. Go to Hugging Face Settings > Access Tokens
2. Create a new token with write permissions
3. Copy the token (starts with hf_...)

2. Set Your Token in Space

1. Go to Settings
2. Find "Variables and secrets" section
3. Click "Replace" next to HF_TOKEN
4. Paste your actual token (replace the placeholder)
5. Click "Save"

3. Restart the Space

After setting the token, click "Restart space" in Settings.

📡 API Endpoint for n8n Integration

Using the Gradio API

The Space provides a REST API that can be called from n8n using the HTTP Request node.

Endpoint URL:

https://alae65-hunyuanimage-3.hf.space/gradio_api/call/api_generate

n8n HTTP Node Configuration

1. Add an HTTP Request node in n8n
2. Configure as follows:

Method: POST

URL:

https://alae65-hunyuanimage-3.hf.space/gradio_api/call/api_generate

Body (JSON):

{
  "data": [
    "A serene mountain landscape with a crystal clear lake",
    42,
    50
  ]
}

Parameters:

• data[0] (string): Your image prompt
• data[1] (integer): Seed number (for reproducibility)
• data[2] (integer): Number of inference steps (10-100)

Response Format: The API returns a JSON with:

{
  "success": true,
  "image_base64": "iVBORw0KGgoAAAANSUhEUg...",
  "seed": 42,
  "status": "Success!",
  "prompt": "A serene mountain landscape..."
}

Example n8n Workflow

1. Trigger → Webhook or Schedule
2. HTTP Request → Call HunyuanImage API
3. Code → Decode base64 image if needed
4. Save or Send → Store image or send via email/Slack

Python Example

import requests
import base64
from PIL import Image
from io import BytesIO

url = "https://alae65-hunyuanimage-3.hf.space/gradio_api/call/api_generate"

payload = {
    "data": [
        "A beautiful sunset over the ocean",
        42,
        50
    ]
}

response = requests.post(url, json=payload)
result = response.json()

if result.get("success"):
    # Decode base64 image
    image_data = base64.b64decode(result["image_base64"])
    image = Image.open(BytesIO(image_data))
    image.save("output.png")
    print("Image saved successfully!")

🎯 Features

• 🎯 Advanced prompt understanding
• 🖼️ Multiple resolution support
• 🎲 Seed control for reproducibility
• ⚙️ Configurable diffusion steps (10-100)
• 📝 Example prompts included
• 🔌 REST API for n8n and automation
• 📦 Base64 image encoding

💰 Pricing

This Space uses the Hugging Face Inference API which is billed based on usage:

• Cost is deducted from your HF account balance
• You mentioned having $9 credit available
• Check Billing Settings for details

📚 Model Information

• Model: tencent/HunyuanImage-3.0
• Architecture: Autoregressive MoE (64 experts)
• Parameters: 80B total, 13B active per token
• License: tencent-hunyuan-community
• Paper: arXiv:2509.23951

🔗 Links

• Official Website
• GitHub Repository
• Technical Paper
• Model Card

📝 Citation

@article{cao2025hunyuanimage,
  title={HunyuanImage 3.0 Technical Report},
  author={Cao, Siyu and Chen, Hangting and others},
  journal={arXiv preprint arXiv:2509.23951},
  year={2025}
}