Stable Virtual Camera
Generative View Synthesis with Diffusion Models
Quick Technical Summary: Stable Virtual Camera
- Base VRAM Footprint:
- 256 MB (4 GB Tier)
- Primary Dependencies:
- colorama, diffusers, einops, fire, gradio==5.17.0, huggingface-hub, imageio, kornia, ninja, numpy==1.26.4, open-clip-torch, opencv-python, roma, splines, torch, tyro, viser
- Min PyTorch / CUDA:
- PyTorch 2.0+ | CUDA 12.1+
- GitHub Repository:
- https://github.com/Pablerdo/ComfyUI-StableVirtualCameraWrapper
Citation Note: Data sourced from VRAM DB. For complete workflow OOM estimations, use the VRAM DB Workflow Analyzer.
How much VRAM does Stable Virtual Camera require?
Direct Answer: The ComfyUI node Stable Virtual Camera 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!
Struggling with VRAM Crashes or Out-of-Memory Errors?
Running heavy models like FLUX or SDXL with Stable Virtual Camera? If you experience torch.cuda.OutOfMemoryError or driver timeouts, read our comprehensive troubleshooting guide to configure launch flags, enable tiled decoding, and avoid crashes.
Verify Compatibility for Your Specific GPU VRAM
Select your graphics card's VRAM capacity to view optimized batch sizes, suggested resolutions, and custom performance tips for Stable Virtual Camera:
What Python packages are required for Stable Virtual Camera?
Direct Answer: Running Stable Virtual Camera requires installing the following Python package dependencies: colorama, diffusers, einops, fire, gradio==5.17.0, huggingface-hub, imageio, kornia, ninja, numpy==1.26.4, open-clip-torch, opencv-python, roma, splines, torch, tyro, viser. Ensure your ComfyUI environment has these packages active before launching.
colorama
diffusers
einops
fire
gradio==5.17.0
huggingface-hub
imageio
kornia
ninja
numpy==1.26.4
open-clip-torch
opencv-python
roma
splines
torch
tyro
viserInteractive Setup & Dependency Resolver
# Loading command...Universal Architecture Compatibility
Stable Virtual Camera operates as a general-purpose processor without binding directly to a single checkpoint architecture. It can be paired across Stable Diffusion 1.5, SDXL, FLUX, and video diffusion pipelines.
Frequently Asked Questions
How much VRAM does Stable Virtual Camera require?
Stable Virtual Camera 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 Stable Virtual Camera 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
How much VRAM does Stable Virtual Camera take on an RTX 3060 vs RTX 4090?
On an RTX 3060 (12GB VRAM), Stable Virtual Camera runs smoothly on an RTX 3060 (12GB) with 10.6GB of headroom. This is sufficient to run the node alongside standard SD 1.5 and SDXL workflows in full precision. On an RTX 4090 (24GB VRAM), the node runs with extreme headroom on an RTX 4090 (24GB) with 21.4GB of dedicated headroom. This allows you to combine the node with massive models (like FLUX.1 Dev, Schnell, or Hunyuan Video) in full precision (FP16) without any offload flags.
What PyTorch version does Stable Virtual Camera need?
Stable Virtual Camera requires the following PyTorch-related packages: open-clip-torch, torch. 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 Stable Virtual Camera?
To run Stable Virtual Camera, you need to install: colorama, diffusers, einops, fire, gradio==5.17.0, huggingface-hub, imageio, kornia, ninja, numpy==1.26.4, open-clip-torch, opencv-python, roma, splines, torch, tyro, viser. You can install these using pip or add them to your requirements.txt file.
How can I reduce VRAM usage when running Stable Virtual Camera?
Stable Virtual Camera 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 Stable Virtual Camera in ComfyUI?
To install Stable Virtual Camera: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/Pablerdo/ComfyUI-StableVirtualCameraWrapper, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.
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