ComfyUI-QwenASR
A lightweight ComfyUI custom node pack for Qwen3-ASR, providing simple speech‑to‑text workflows with local model caching and optional timestamp output. Supports Qwen/Qwen3‑ASR‑1.7B and 0.6B, with HuggingFace/ModelScope download options and clean integration for ComfyUI pipelines.
How much VRAM does ComfyUI-QwenASR require?
Direct Answer: The ComfyUI node ComfyUI-QwenASR requires a minimum base VRAM of 256MB and is optimized for GPUs with at least 4GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.
- Base VRAM:
- 256MB (0.3GB)
- Recommended GPU:
- 4GB+ VRAM
- Low VRAM Mode:
- ✓ Supported
- Estimation Confidence:
- HIGH
Interactive VRAM Compatibility Estimator
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 ComfyUI-QwenASR?
Direct Answer: Running ComfyUI-QwenASR requires installing the following Python package dependencies: accelerate>=1.12.0, dynet38==2.2, huggingface_hub, modelscope, nagisa==0.2.11, numpy, soundfile, soynlp==0.0.493, torch>=2.0.0, torchaudio>=2.0.0, transformers>=4.57.0. This node specifically requires PyTorch version 2.0.0 or newer.
accelerate>=1.12.0
dynet38==2.2
huggingface_hub
modelscope
nagisa==0.2.11
numpy
soundfile
soynlp==0.0.493
torch>=2.0.0
torchaudio>=2.0.0
transformers>=4.57.0Interactive Setup & Dependency Resolver
# Loading command...Special Environment Requirements:
Requires PyTorch version 2.0.0+.
# Loading PyTorch command...Frequently Asked Questions
How much VRAM does ComfyUI-QwenASR require?
ComfyUI-QwenASR requires a minimum of 256MB (0.3GB) 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 ComfyUI-QwenASR on an RTX 3060, RTX 4070, or RTX 4090?
✅ RTX 3060 (12GB): Yes, fully compatible with 10.6GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 10.6GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 14.2GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 21.4GB headroom
What PyTorch version does ComfyUI-QwenASR need?
ComfyUI-QwenASR requires the following PyTorch-related packages: torch>=2.0.0, torchaudio>=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 ComfyUI-QwenASR?
To run ComfyUI-QwenASR, you need to install: accelerate>=1.12.0, dynet38==2.2, huggingface_hub, modelscope, nagisa==0.2.11, numpy, soundfile, soynlp==0.0.493, torch>=2.0.0, torchaudio>=2.0.0, transformers>=4.57.0. You can install these using pip or add them to your requirements.txt file.
How can I reduce VRAM usage when running ComfyUI-QwenASR?
ComfyUI-QwenASR 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 ComfyUI-QwenASR in ComfyUI?
To install ComfyUI-QwenASR: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/1038lab/ComfyUI-QwenASR, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.