ComfyUI-QwenVL-MultiImage
A powerful ComfyUI custom node that integrates Qwen2.5-VL and Qwen3-VL vision-language models with multi-image support. Process multiple images simultaneously with advanced AI capabilities for image understanding, comparison, and analysis.
How much VRAM does ComfyUI-QwenVL-MultiImage require?
Direct Answer: The ComfyUI node ComfyUI-QwenVL-MultiImage 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.
- Base VRAM:
- 128MB (0.1GB)
- Recommended GPU:
- 4GB+ VRAM
- Low VRAM Mode:
- ✓ Supported
- Estimation Confidence:
- MEDIUM
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-QwenVL-MultiImage?
Direct Answer: Running ComfyUI-QwenVL-MultiImage requires installing the following Python package dependencies: accelerate>=0.20.0, bitsandbytes>=0.41.0, pillow>=10.0.0, qwen-vl-utils>=0.0.8, sentencepiece>=0.1.99, torch>=2.0.0, torchvision>=0.15.0, transformers>=4.45.0. This node specifically requires PyTorch version 2.0.0 or newer.
accelerate>=0.20.0
bitsandbytes>=0.41.0
pillow>=10.0.0
qwen-vl-utils>=0.0.8
sentencepiece>=0.1.99
torch>=2.0.0
torchvision>=0.15.0
transformers>=4.45.0Interactive 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-QwenVL-MultiImage require?
ComfyUI-QwenVL-MultiImage 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 ComfyUI-QwenVL-MultiImage 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 PyTorch version does ComfyUI-QwenVL-MultiImage need?
ComfyUI-QwenVL-MultiImage requires the following PyTorch-related packages: torch>=2.0.0, torchvision>=0.15.0. 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-QwenVL-MultiImage?
To run ComfyUI-QwenVL-MultiImage, you need to install: accelerate>=0.20.0, bitsandbytes>=0.41.0, pillow>=10.0.0, qwen-vl-utils>=0.0.8, sentencepiece>=0.1.99, torch>=2.0.0, torchvision>=0.15.0, transformers>=4.45.0. You can install these using pip or add them to your requirements.txt file.
How can I reduce VRAM usage when running ComfyUI-QwenVL-MultiImage?
ComfyUI-QwenVL-MultiImage 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-MultiImage in ComfyUI?
To install ComfyUI-QwenVL-MultiImage: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/hardik-uppal/ComfyUI-QwenVL-MultiImage, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.