EmberFrame Nodes
A growing collection of EmberFrame utility nodes for Comfy, including advanced PiD sampling, Z-Image/Flux latent normalization, wildcard prompt helpers, and resolution tools.
Quick Technical Summary: EmberFrame Nodes
- Base VRAM Footprint:
- 12288 MB (24 GB Tier)
- Primary Dependencies:
- None (Pure Python/Torch)
- Min PyTorch / CUDA:
- PyTorch 2.0+ | CUDA 12.1+
- GitHub Repository:
- https://github.com/emberframe/emberframe-nodes
Citation Note: Data sourced from VRAM DB. For complete workflow OOM estimations, use the VRAM DB Workflow Analyzer.
How much VRAM does EmberFrame Nodes require?
Direct Answer: The ComfyUI node EmberFrame Nodes requires a minimum base VRAM of 12288MB and is optimized for GPUs with at least 24GB of VRAM. Low VRAM mode is not supported for this node.
- Base VRAM:
- 12288MB (12.0GB)
- Recommended GPU:
- 24GB+ VRAM
- Low VRAM Mode:
- ✗ Not supported
- Estimation Confidence:
- HIGH
Cheapest VRAM Upgrade Paths (Live Market Prices):
- GeForce RTX 3090 24GB (Best Used 24GB Value)──► Used: $624.42View eBay ↗
- GeForce RTX 4090 24GB (Ultimate AI Beast)──► New: $1802.60View Amazon ↗
Interactive VRAM Compatibility Estimator
Your GPU has plenty of headroom. You can run this node safely with your active configurations!
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 EmberFrame Nodes:
Buy NVIDIA GeForce RTX 4090 (24GB VRAM)
Tired of renting cloud rigs? Run ComfyUI locally with absolute zero latency. Critical for native FP16 video models (Hunyuan, Wan 2.1) and massive multi-model pipelines.
Local GPU Upgrade vs. Cloud Rental
Compare the real financial break-even point for ComfyUI generation.
Buy NVIDIA GeForce RTX 4090
- Card Purchase Price:
- $1800.00
- Active Wattage Draw:
- 450 Watts
- Annual Electric Cost:
- $0.00
Rent GPU On-Demand
- Estimated Cloud Rate:
- $0.44 / hr
- Weekly Cloud Billing:
- $0.00
- Annual Cost (Equivalent):
- $0.00
Are you the author of this node?
Help your users avoid out-of-memory errors by displaying this professional, dynamic VRAM badge on your GitHub README. Copy the markdown below to embed it with a backlink directly to this hardware specification profile.
Compatible Foundations
This node is verified to support or optimize workflows for the following foundation model families:
Frequently Asked Questions
How much VRAM does EmberFrame Nodes require?
EmberFrame Nodes requires a minimum of 12288MB (12.0GB) of VRAM for base operation. For optimal performance, a GPU with at least 24GB of VRAM is recommended. Low VRAM mode is not supported for this node.
Can I run EmberFrame Nodes on an RTX 3060, RTX 4070, or RTX 4090?
❌ RTX 3060 (12GB): Insufficient VRAM (needs 12.0GB minimum). ❌ RTX 4070 (12GB): Insufficient VRAM (needs 12.0GB minimum). ⚠️ RTX 4070 Ti (16GB): Can run, but may experience performance issues or require low VRAM mode. ✅ RTX 4090 (24GB): Yes, fully compatible with 9.6GB headroom
How much VRAM does EmberFrame Nodes take on an RTX 3060 vs RTX 4090?
On an RTX 3060 (12GB VRAM), EmberFrame Nodes will struggle or run out of memory on an RTX 3060 (12GB) without aggressive memory offloading (using --lowvram), as the node's base footprint of 12.0GB takes up a large portion of the card's capacity. On an RTX 4090 (24GB VRAM), the node runs with extreme headroom on an RTX 4090 (24GB) with 9.6GB 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 EmberFrame Nodes in ComfyUI?
To install EmberFrame Nodes: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/emberframe/emberframe-nodes, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.