ComfyUI-Upscaler-TensorRT-RTX

By ThreadsOfFateView on GitHub →

NVIDIA TensorRT-accelerated upscaler with dynamic shape support, up to 30x faster upscaling with automatic engine building and persistent timing cache. (Description by CC)

VRAM Requirements

Direct Answer: The ComfyUI node ComfyUI-Upscaler-TensorRT-RTX requires a minimum base VRAM of 3072MB and is optimized for GPUs with at least 8GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.

Very High (4-8GB)
Base VRAM:
3072MB (3.0GB)
Recommended GPU:
8GB+ 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!

Deploy on High-Performance GPUs

Need more VRAM to run ComfyUI with this node? Rent low-cost, high-performance GPUs on Vast.ai instantly.

🚀 Deploy on Vast.ai

Deploy on Cloud GPUs

Need more VRAM to run ComfyUI with this node? Rent low-cost, high-performance cloud GPUs on RunPod instantly.

🚀 Deploy on RunPod

Python Dependencies

Direct Answer: Running ComfyUI-Upscaler-TensorRT-RTX requires installing the following Python package dependencies: cuda-toolkit, numpy, onnx, onnxconverter_common, onnxsim, polygraphy, tensorrt_rtx, torch, tqdm. Ensure your ComfyUI environment has these packages active before launching.

requirements.txt
cuda-toolkit
numpy
onnx
onnxconverter_common
onnxsim
polygraphy
tensorrt_rtx
torch
tqdm

🛠️ Interactive Setup & Dependency Resolver

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