ComfyUI Model Randomizer
A custom node for ComfyUI that randomly selects a checkpoint from a configurable list of models. Each model entry has its own CFG range, probability weight, and enable/disable toggle.
Replaces the common chain of Load Checkpoint → Context Big → Fast Muter → Random Unmuter with a single, self-contained node.
Features
- Weighted random selection — assign probability weights to favor certain models
- Per-model CFG range — set a min/max CFG for each entry; a random value is picked within the range
- Enable/disable toggle — temporarily exclude models without removing them
- Seed control — use a fixed seed for reproducible selections, or
0for fully random - Checkpoint caching — skips reloading when the same model is selected consecutively
- Drag-to-reorder — move entries up/down with built-in buttons
- Add/remove entries — dynamically grow or shrink the model list
Outputs
| Output | Description |
|---|---|
MODEL |
Diffusion model from the selected checkpoint |
CLIP |
CLIP model from the selected checkpoint |
VAE |
VAE model from the selected checkpoint |
MODEL_NAME |
Filename of the selected checkpoint |
CFG |
Random CFG value within the selected model's range |
Installation
Clone into the custom_nodes directory:
cd ComfyUI/custom_nodes
git clone https://github.com/Mervent/comfyui-model-randomizer.git
Restart ComfyUI. The node appears under loaders → Model Randomizer.
Usage
- Add the Model Randomizer node to your workflow
- Click Add Model to create model entries
- For each entry, select a checkpoint and configure:
- CFG Min / Max — the range for random CFG generation
- Weight — relative probability (higher = more likely to be picked)
- Enabled — toggle to include/exclude from selection
- Connect the outputs to the rest of your pipeline
Set seed to a non-zero value for reproducible results across runs, or leave at 0 for a fresh random pick every time.