ComfyUI-QwenVL-Utils

By AkihaTatsuView on GitHub →

Comprehensive QwenVL integration for ComfyUI with HuggingFace and GGUF model support

How much VRAM does ComfyUI-QwenVL-Utils require?

Direct Answer: The ComfyUI node ComfyUI-QwenVL-Utils 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.

High (2-4GB)
Base VRAM:
256MB (0.3GB)
Recommended GPU:
4GB+ VRAM
Low VRAM Mode:
✓ Supported
Estimation Confidence:
HIGH

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 ComfyUI-QwenVL-Utils?

Direct Answer: Running ComfyUI-QwenVL-Utils requires installing the following Python package dependencies: accelerate>=0.20.0, huggingface_hub>=0.14.0, numpy>=1.20.0, opencv-python>=4.5.0, pillow>=8.0.0, psutil>=5.0.0, torch>=1.13.0 # 2.0+ recommended for torch.compile and SDPA, but 1.13+ works, transformers>=4.37.0 # 4.45+ recommended for Qwen2-VL, 4.37+ minimum. This node specifically requires PyTorch version 1.13.0 or newer.

requirements.txt
accelerate>=0.20.0
huggingface_hub>=0.14.0
numpy>=1.20.0
opencv-python>=4.5.0
pillow>=8.0.0
psutil>=5.0.0
torch>=1.13.0  # 2.0+ recommended for torch.compile and SDPA, but 1.13+ works
transformers>=4.37.0  # 4.45+ recommended for Qwen2-VL, 4.37+ minimum

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 1.13.0+.

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

Frequently Asked Questions

How much VRAM does ComfyUI-QwenVL-Utils require?

ComfyUI-QwenVL-Utils 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-QwenVL-Utils 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-QwenVL-Utils need?

ComfyUI-QwenVL-Utils requires the following PyTorch-related packages: torch>=1.13.0 # 2.0+ recommended for torch.compile and SDPA, but 1.13+ works. 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-QwenVL-Utils?

To run ComfyUI-QwenVL-Utils, you need to install: accelerate>=0.20.0, huggingface_hub>=0.14.0, numpy>=1.20.0, opencv-python>=4.5.0, pillow>=8.0.0, psutil>=5.0.0, torch>=1.13.0 # 2.0+ recommended for torch.compile and SDPA, but 1.13+ works, transformers>=4.37.0 # 4.45+ recommended for Qwen2-VL, 4.37+ minimum. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running ComfyUI-QwenVL-Utils?

ComfyUI-QwenVL-Utils 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-QwenVL-Utils in ComfyUI?

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