DVA_Qwen_TTS

By DVAView on GitHub →

High-quality multilingual TTS with voice cloning, emotion control, and support for Qwen3-TTS models (CustomVoice, VoiceDesign, Base).

How much VRAM does DVA_Qwen_TTS require?

Direct Answer: The ComfyUI node DVA_Qwen_TTS requires a minimum base VRAM of 4096MB and is optimized for GPUs with at least 8GB of VRAM. Low VRAM mode is not supported for this node.

Very High (4-8GB)
Base VRAM:
4096MB (4.0GB)
Recommended GPU:
8GB+ VRAM
Low VRAM Mode:
✗ Not supported
Estimation Confidence:
MEDIUM

Interactive VRAM Compatibility Estimator

Estimated Total VRAM: 3.00 GBTarget: 8 GB
✅ Comfortable Fit

Your GPU has plenty of headroom. You can run this node safely with your active configurations!

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Deploy on Cloud GPUs

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What Python packages are required for DVA_Qwen_TTS?

Direct Answer: Running DVA_Qwen_TTS requires installing the following Python package dependencies: numpy>=1.24.0, qwen-tts>=0.1.0, soundfile>=0.12.0, torch>=2.0.0, transformers>=4.37.0. This node specifically requires PyTorch version 2.0.0 or newer.

requirements.txt
numpy>=1.24.0
qwen-tts>=0.1.0
soundfile>=0.12.0
torch>=2.0.0
transformers>=4.37.0

Interactive Setup & Dependency Resolver

Operating System:
Environment Type:
Run this terminal command in your ComfyUI root folder:
# Loading command...

Special Environment Requirements:

Requires PyTorch version 2.0.0+.

To update PyTorch for your selected setup, run:
# Loading PyTorch command...

Related Custom Nodes

The following custom nodes run in the same PyTorch / CUDA environment and share similar categories or workflows:

ComfyUI WhisperX Pro
by loockluo1.5GB VRAM
ComfyUI-AudioX
by lum3on4.0GB VRAM
ComfyUI-FireRedTTS
by 1038lab4.0GB VRAM
ComfyUI-MegaTTS
by 1038lab256MB VRAM
ComfyUI-QwenASR
by 1038lab256MB VRAM

Frequently Asked Questions

How much VRAM does DVA_Qwen_TTS require?

DVA_Qwen_TTS requires a minimum of 4096MB (4.0GB) of VRAM for base operation. For optimal performance, a GPU with at least 8GB of VRAM is recommended. Low VRAM mode is not supported for this node.

Can I run DVA_Qwen_TTS on an RTX 3060, RTX 4070, or RTX 4090?

✅ RTX 3060 (12GB): Yes, fully compatible with 6.8GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 6.8GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 10.4GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 17.6GB headroom

What PyTorch version does DVA_Qwen_TTS need?

DVA_Qwen_TTS requires the following PyTorch-related packages: torch>=2.0.0. Ensure your ComfyUI environment has these installed. Ensure your PyTorch installation matches your CUDA version (use torch.version.cuda to check).

What Python packages are required for DVA_Qwen_TTS?

To run DVA_Qwen_TTS, you need to install: numpy>=1.24.0, qwen-tts>=0.1.0, soundfile>=0.12.0, torch>=2.0.0, transformers>=4.37.0. You can install these using pip or add them to your requirements.txt file.

How do I install DVA_Qwen_TTS in ComfyUI?

To install DVA_Qwen_TTS: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/SLVGITHUB/QWEN3_TTS_DVA, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.