Comfyui_TTP_Toolset
This is a workflow for my simple logic amazing upscale node for DIT model. it can be common use for Flux,Hunyuan,SD3 It can simple tile the initial image into pieces and then use image-interrogator to get each tile prompts for more accurate upscale process. The condition will be properly handled and the hallucination will be significantly eliminated.
Quick Technical Summary: Comfyui_TTP_Toolset
- 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/TTPlanetPig/Comfyui_TTP_Toolset
Citation Note: Data sourced from VRAM DB. For complete workflow OOM estimations, use the VRAM DB Workflow Analyzer.
How much VRAM does Comfyui_TTP_Toolset require?
Direct Answer: The ComfyUI node Comfyui_TTP_Toolset 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
Run Comfyui_TTP_Toolset locally
Honest estimate: this node typically needs ≥ 24GB VRAM in a real workflow.
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 ↗
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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 Comfyui_TTP_Toolset? 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 Comfyui_TTP_Toolset:
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
No Python Dependencies Required
This node runs purely on native ComfyUI python contexts. No external pip libraries require automated installation!
Universal Architecture Compatibility
Comfyui_TTP_Toolset 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.
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_TTP_Toolset require?
Comfyui_TTP_Toolset 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 Comfyui_TTP_Toolset 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 Comfyui_TTP_Toolset take on an RTX 3060 vs RTX 4090?
On an RTX 3060 (12GB VRAM), Comfyui_TTP_Toolset 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 Comfyui_TTP_Toolset in ComfyUI?
To install Comfyui_TTP_Toolset: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/TTPlanetPig/Comfyui_TTP_Toolset, (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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