ComfyUI Coherent Video Sampler Node (V0.3)

A custom node for ComfyUI that enables coherent video generation while maintaining efficient memory usage, specifically optimized for heavy models like Flux.

Features

🎥 Frame-by-frame video processing with motion preservation

🧠 Efficient memory management for heavy models

🔄 Progressive denoising with coherence maintenance

💫 Dynamic quality control and motion guidance

🎨 Style preservation across frames

🛠️ Advanced adjustment controls for fine-tuning

Installation

Install from ComfyUI manager

or

Navigate to your ComfyUI custom nodes directory:

cd ComfyUI/custom_nodes

Clone this repository:

git clone https://github.com/ShmuelRonen/ComfyUI-CohernetVideoSampler.git

Restart ComfyUI

Usage

For Deforum-like results please use ‘shuttle-3-diffusion-fp8.safetensors’ 4 steps flux model

The node appears in the node menu as “Cohernet Video Sampler”.

Core Parameters Guide

The sampler now includes four key adjustment parameters that work together to control different aspects of video generation:

denoise (0.0-1.0):

Primary denoising control for the sampling process

Controls overall deviation from input

Lower values (0.3-0.5): Subtle changes, closer to input

Higher values (0.7-0.9): More dramatic transformations

Recommended: 0.6 for balanced results

motion_strength (0.0-1.0):

Controls motion intensity between frames

Affects transition smoothness

Lower values (0.3-0.4): More static, stable output

Higher values (0.7-0.8): Pronounced motion, dynamic transitions

Recommended: 0.5 for natural movement

consistency_strength (0.0-1.0):

Maintains visual consistency across frames

Controls style preservation

Lower values (0.7-0.8): More variation allowed

Higher values (0.9-1.0): Strict consistency enforcement

Recommended: 0.9 for coherent results

denoise_strength (0.0-1.0):

Secondary denoising for artifact reduction

Fine-tunes final output quality

Lower values (0.5-0.7): Preserve more details

Higher values (0.8-0.9): Smoother, cleaner output

Recommended: 0.8 for balanced detail preservation

Parameter Combinations for Different Effects

High Quality Stable Video

denoise: 0.6
motion_strength: 0.5
consistency_strength: 0.9
denoise_strength: 0.8

Dynamic Movement Priority

denoise: 0.5
motion_strength: 0.7
consistency_strength: 0.8
denoise_strength: 0.7

Maximum Detail Preservation

denoise: 0.4
motion_strength: 0.4
consistency_strength: 0.85
denoise_strength: 0.6

Other Inputs

model: Your diffusion model (tested extensively with Flux)

positive: Positive prompt conditioning

negative: Negative prompt conditioning

video_latents: Input video in latent space (from VAE Encode)

seed: Generation seed

steps: Number of sampling steps

cfg: Classifier free guidance scale

sampler_name: Choice of sampler

scheduler: Choice of scheduler

Memory Management

The node implements several memory optimization techniques:

Progressive batch processing

Automatic VRAM cleanup

Dynamic batch size adjustment

Efficient latent space operations

This allows it to work smoothly even with memory-intensive models like Flux without OOM errors.

Memory Usage Examples

When using with Flux model:

20 frame video @ 512×512: ~8GB VRAM

40 frame video @ 512×512: ~10GB VRAM

Processing happens in windows of frames to maintain stable memory usage

Optimization Tips

For Smoother Videos:

Increase consistency_strength

Decrease motion_strength slightly

Keep denoise moderate

Maintain high denoise_strength

For More Dynamic Videos:

Increase motion_strength

Decrease consistency_strength slightly

Lower denoise_strength for detail

Adjust denoise based on desired change level

For Maximum Quality:

Balance all parameters

Use higher consistency_strength

Moderate motion_strength

Higher denoise_strength

Known Limitations

Very long videos might need to be processed in segments

Extreme motion can affect coherence

High denoise values might reduce motion preservation

Parameter interactions can be complex

Future Plans

Additional motion control parameters

Custom denoising patterns

Advanced style preservation options

Multi-model support optimization

Parameter presets for common use cases

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

License

MIT License

Acknowledgments

ComfyUI team for the amazing framework

Flux model team for the inspiration in handling heavy models