Qwen3 Triton TTS

By newgrit1004View on GitHub →

ComfyUI node wrapping qwen3-tts-triton for 7-mode Qwen3-TTS inference (Triton kernel fusion + TurboQuant KV cache)

How much VRAM does Qwen3 Triton TTS require?

Direct Answer: The ComfyUI node Qwen3 Triton TTS requires a minimum base VRAM of 128MB and is optimized for GPUs with at least 4GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.

High (2-4GB)
Base VRAM:
128MB (0.1GB)
Recommended GPU:
4GB+ VRAM
Low VRAM Mode:
✓ 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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What Python packages are required for Qwen3 Triton TTS?

Direct Answer: Running Qwen3 Triton TTS requires installing the following Python package dependencies: qwen3-tts-triton>=0.2.0. Ensure your ComfyUI environment has these packages active before launching.

requirements.txt
qwen3-tts-triton>=0.2.0

Interactive Setup & Dependency Resolver

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

Related Custom Nodes

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

Audio Batch
by set-soft1.5GB VRAM
ComfyUI Custom Dia
by nobrainX2128MB VRAM
ComfyUI Stable Audio Open 1.0 Sampler
by lks-ai1.5GB VRAM
ComfyUI jhj Kokoro Onnx
by jhj0517128MB VRAM
ComfyUI-Dia
by Yuan-ManX128MB VRAM

Frequently Asked Questions

How much VRAM does Qwen3 Triton TTS require?

Qwen3 Triton TTS requires a minimum of 128MB (0.1GB) of VRAM for base operation. For optimal performance, a GPU with at least 4GB of VRAM is recommended. This node supports low VRAM mode for resource-constrained setups.

Can I run Qwen3 Triton TTS on an RTX 3060, RTX 4070, or RTX 4090?

✅ RTX 3060 (12GB): Yes, fully compatible with 10.7GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 10.7GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 14.3GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 21.5GB headroom

What Python packages are required for Qwen3 Triton TTS?

To run Qwen3 Triton TTS, you need to install: qwen3-tts-triton>=0.2.0. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running Qwen3 Triton TTS?

Qwen3 Triton TTS supports low VRAM mode. To reduce memory usage: (1) Enable --lowvram or --medvram flags in ComfyUI, (2) Reduce batch size to 1, (3) Use fp16 or fp8 precision if supported, (4) Close other GPU applications.

How do I install Qwen3 Triton TTS in ComfyUI?

To install Qwen3 Triton TTS: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/newgrit1004/ComfyUI-Qwen3-TTS-Triton, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.