WanImageToVideoTiledVAE for ComfyUI
This is a set of custom nodes for ComfyUI that replaces nodes like WanImageToVideo but using a Tiled VAE approach to reduce VRAM requirements.
Quick Technical Summary: WanImageToVideoTiledVAE for ComfyUI
- Base VRAM Footprint:
- 4096 MB (8 GB Tier)
- Primary Dependencies:
- None (Pure Python/Torch)
- Min PyTorch / CUDA:
- PyTorch 2.0+ | CUDA 12.1+
- GitHub Repository:
- https://github.com/stduhpf/ComfyUI--WanImageToVideoTiled
Citation Note: Data sourced from VRAM DB. For complete workflow OOM estimations, use the VRAM DB Workflow Analyzer.
How much VRAM does WanImageToVideoTiledVAE for ComfyUI require?
Direct Answer: The ComfyUI node WanImageToVideoTiledVAE for ComfyUI requires a minimum base VRAM of 4096MB and is optimized for GPUs with at least 8GB of VRAM. Low VRAM mode is not supported for this node.
- Base VRAM:
- 4096MB (4.0GB)
- Recommended GPU:
- 8GB+ VRAM
- Low VRAM Mode:
- ✗ Not supported
- Estimation Confidence:
- MEDIUM
Run WanImageToVideoTiledVAE for ComfyUI locally
Honest estimate: this node typically needs ≥ 8GB VRAM in a real workflow.
Cheapest VRAM upgrade paths (live market prices)
- GeForce RTX 3060 12GB (Ultimate Budget VRAM King)Used: $209.62View eBay ↗
- GeForce RTX 4060 8GB (Modern Entry-Level)New: $303.50View Amazon ↗
Disclosure: As an Amazon Associate we earn from qualifying purchases. Cloud provider links are referrals at no additional cost to you.
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 WanImageToVideoTiledVAE for ComfyUI? 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 WanImageToVideoTiledVAE for ComfyUI:
No Python Dependencies Required
This node runs purely on native ComfyUI python contexts. No external pip libraries require automated installation!
Universal Architecture Compatibility
WanImageToVideoTiledVAE for ComfyUI 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 WanImageToVideoTiledVAE for ComfyUI require?
WanImageToVideoTiledVAE for ComfyUI requires a minimum of 4096MB (4.0GB) of VRAM for base operation. For optimal performance, a GPU with at least 8GB of VRAM is recommended. Low VRAM mode is not supported for this node.
Can I run WanImageToVideoTiledVAE for ComfyUI on an RTX 3060, RTX 4070, or RTX 4090?
✅ RTX 3060 (12GB): Yes, fully compatible with 6.8GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 6.8GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 10.4GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 17.6GB headroom
How much VRAM does WanImageToVideoTiledVAE for ComfyUI take on an RTX 3060 vs RTX 4090?
On an RTX 3060 (12GB VRAM), WanImageToVideoTiledVAE for ComfyUI runs smoothly on an RTX 3060 (12GB) with 6.8GB 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 17.6GB 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.
How do I install WanImageToVideoTiledVAE for ComfyUI in ComfyUI?
To install WanImageToVideoTiledVAE for ComfyUI: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/stduhpf/ComfyUI--WanImageToVideoTiled, (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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