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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 Generation
This Space provides an interface for the Tencent HunyuanImage-3.0 model, a powerful native multimodal model for image generation.
About HunyuanImage-3.0
HunyuanImage-3.0 is a groundbreaking model that:
- Features 80B total parameters with 13B activated per token (MoE architecture)
- Unifies multimodal understanding and generation in an autoregressive framework
- Achieves performance comparable to leading closed-source models
- Supports intelligent prompt understanding and automatic elaboration
⚠️ Important Notes
Hardware Requirements:
- Direct inference requires 3×80GB GPU memory (240GB total)
- ZeroGPU is insufficient for full model inference
- For production use, consider:
- Using Inference API endpoints
- Deploying on appropriate hardware (4×80GB GPUs recommended)
- Using inference providers like FAL AI
Current Implementation: This Space demonstrates the UI structure and configuration. For actual inference:
- The model needs to be loaded with proper hardware
- Or integrate with Inference API/providers
- Or use model quantization techniques
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
Features
- 🎯 Advanced prompt understanding
- 🖼️ Multiple resolution support (auto, 1024x1024, 1280x768, 768x1280)
- 🎲 Seed control for reproducibility
- ⚙️ Configurable diffusion steps
- 📝 Example prompts included
API Endpoint (Coming Soon)
This Space will support API endpoints for integration with n8n and other workflow tools.
Links
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}
}