ComfyUI Flux Trainer
Currently supports LoRA training, and untested full finetune with code from kohya's scripts: [a/https://github.com/kohya-ss/sd-scripts](https://github.com/kohya-ss/sd-scripts)
How much VRAM does ComfyUI Flux Trainer require?
Direct Answer: The ComfyUI node ComfyUI Flux Trainer 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
Interactive VRAM Compatibility Estimator
Your GPU has plenty of headroom. You can run this node safely with your active configurations!
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Deploy on Cloud GPUs
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What Python packages are required for ComfyUI Flux Trainer?
Direct Answer: Running ComfyUI Flux Trainer requires installing the following Python package dependencies: accelerate>=0.33.0, altair>=4.2.2, bitsandbytes>=0.44.0, came_pytorch, diffusers>=0.25.0, einops>=0.7.0, ftfy>=6.1.1, huggingface-hub>=0.24.5, imagesize>=1.4.1, lion-pytorch>=0.0.6, matplotlib, numpy<=1.26.4, opencv-python>=4.7.0.68, prodigy-plus-schedule-free>=1.9.0, prodigyopt>=1.0, protobuf, rich>=13.7.0, safetensors>=0.4.4, schedulefree>=1.2.7, sentencepiece>=0.2.0, toml>=0.10.2, transformers>=4.44.0, voluptuous>=0.13.1. Ensure your ComfyUI environment has these packages active before launching.
accelerate>=0.33.0
altair>=4.2.2
bitsandbytes>=0.44.0
came_pytorch
diffusers>=0.25.0
einops>=0.7.0
ftfy>=6.1.1
huggingface-hub>=0.24.5
imagesize>=1.4.1
lion-pytorch>=0.0.6
matplotlib
numpy<=1.26.4
opencv-python>=4.7.0.68
prodigy-plus-schedule-free>=1.9.0
prodigyopt>=1.0
protobuf
rich>=13.7.0
safetensors>=0.4.4
schedulefree>=1.2.7
sentencepiece>=0.2.0
toml>=0.10.2
transformers>=4.44.0
voluptuous>=0.13.1Interactive Setup & Dependency Resolver
# Loading command...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 Flux Trainer require?
ComfyUI Flux Trainer 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 Flux Trainer 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
What PyTorch version does ComfyUI Flux Trainer need?
ComfyUI Flux Trainer requires the following PyTorch-related packages: came_pytorch, lion-pytorch>=0.0.6. 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 ComfyUI Flux Trainer?
To run ComfyUI Flux Trainer, you need to install: accelerate>=0.33.0, altair>=4.2.2, bitsandbytes>=0.44.0, came_pytorch, diffusers>=0.25.0, einops>=0.7.0, ftfy>=6.1.1, huggingface-hub>=0.24.5, imagesize>=1.4.1, lion-pytorch>=0.0.6, matplotlib, numpy<=1.26.4, opencv-python>=4.7.0.68, prodigy-plus-schedule-free>=1.9.0, prodigyopt>=1.0, protobuf, rich>=13.7.0, safetensors>=0.4.4, schedulefree>=1.2.7, sentencepiece>=0.2.0, toml>=0.10.2, transformers>=4.44.0, voluptuous>=0.13.1. You can install these using pip or add them to your requirements.txt file.
How do I install ComfyUI Flux Trainer in ComfyUI?
To install ComfyUI Flux Trainer: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/kijai/ComfyUI-FluxTrainer, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.