ComfyUI_SDXL_LongContext
SDXL Long Context extends SDXL positional embeddings from 77 to 248 tokens using learned sinusoidal extrapolation method. (Description by CC)
Quick Technical Summary: ComfyUI_SDXL_LongContext
- Base VRAM Footprint:
- 8192 MB (12 GB Tier)
- Primary Dependencies:
- None (Pure Python/Torch)
- Min PyTorch / CUDA:
- PyTorch 2.0+ | CUDA 12.1+
- GitHub Repository:
- https://github.com/brahianrosswill/ComfyUI_SDXL_LongContext
Citation Note: Data sourced from VRAM DB. For complete workflow OOM estimations, use the VRAM DB Workflow Analyzer.
How much VRAM does ComfyUI_SDXL_LongContext require?
Direct Answer: The ComfyUI node ComfyUI_SDXL_LongContext requires a minimum base VRAM of 8192MB and is optimized for GPUs with at least 12GB of VRAM. Low VRAM mode is not supported for this node.
- Base VRAM:
- 8192MB (8.0GB)
- Recommended GPU:
- 12GB+ VRAM
- Low VRAM Mode:
- ✗ Not supported
- Estimation Confidence:
- HIGH
Cheapest VRAM Upgrade Paths (Live Market Prices):
- GeForce RTX 3060 12GB (Budget 12GB Upgrade)──► Used: $209.62View eBay ↗
- GeForce RTX 4070 12GB (High-Performance 12GB)──► New: $535.75View 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 ComfyUI_SDXL_LongContext:
Buy NVIDIA GeForce RTX 4070 (12GB VRAM)
Tired of renting cloud rigs? Run ComfyUI locally with absolute zero latency. The sweet spot for Stable Diffusion XL (SDXL) and quantized FLUX.1 (FP8/GGUF) workflows.
Local GPU Upgrade vs. Cloud Rental
Compare the real financial break-even point for ComfyUI generation.
Buy NVIDIA GeForce RTX 4070
- Card Purchase Price:
- $540.00
- Active Wattage Draw:
- 200 Watts
- Annual Electric Cost:
- $0.00
Rent GPU On-Demand
- Estimated Cloud Rate:
- $0.22 / hr
- Weekly Cloud Billing:
- $0.00
- Annual Cost (Equivalent):
- $0.00
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Compatible Foundations
This node is verified to support or optimize workflows for the following foundation model families:
Frequently Asked Questions
How much VRAM does ComfyUI_SDXL_LongContext require?
ComfyUI_SDXL_LongContext requires a minimum of 8192MB (8.0GB) of VRAM for base operation. For optimal performance, a GPU with at least 12GB of VRAM is recommended. Low VRAM mode is not supported for this node.
Can I run ComfyUI_SDXL_LongContext on an RTX 3060, RTX 4070, or RTX 4090?
✅ RTX 3060 (12GB): Yes, fully compatible with 2.8GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 2.8GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 6.4GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 13.6GB headroom
How much VRAM does ComfyUI_SDXL_LongContext take on an RTX 3060 vs RTX 4090?
On an RTX 3060 (12GB VRAM), ComfyUI_SDXL_LongContext runs smoothly on an RTX 3060 (12GB) with 2.8GB 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 13.6GB 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 ComfyUI_SDXL_LongContext in ComfyUI?
To install ComfyUI_SDXL_LongContext: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/brahianrosswill/ComfyUI_SDXL_LongContext, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.