ComfyUI-KSampler-Matrix-Lab Puts Sampler Battles In A Visual Grid

ComfyUI-KSampler-Matrix-Lab is a custom node for ComfyUI that generates a labeled comparison grid of different sampler and scheduler combinations. It runs each selected pair sequentially using the same base settings to produce one final image output. This lets users quickly evaluate how different choices affect image generation without manually reconfiguring nodes.
Developer Btitkin built the node to eliminate the tedious process of duplicating KSamplers and adjusting settings one by one. The tool was released as an open-source project under the MIT license, welcoming community feedback and contributions. It addresses a common pain point for anyone who regularly tests multiple sampler and scheduler configurations inside ComfyUI.
A visual grid for sampler comparisons
- Compare multiple sampler/scheduler pairs side by side.
- Dynamic dropdowns of locally available samplers and schedulers.
- Up to nine sampler slots and nine scheduler slots.
- Same-seed or increment-per-cell seed modes.
- Sequential cell generation to limit GPU memory spikes.
- Per-cell labels showing sampler and scheduler names.
- Error placeholder cells when a combination fails.
- Top header with model, VAE, steps, CFG, and denoise.
This node is ideal for artists and studios who need to find the most reliable sampler and scheduler combination quickly. Researchers and power users can use the same-seed mode for precise visual comparisons. Local AI teams can automate their testing workflows and save hours on manual iteration.
Developer notes and early feedback
Generation runs sequentially, so very large grids take longer but help avoid running out of GPU memory. Some custom model loaders may not expose complete metadata, which can cause the top header to display “unknown” in those fields. The developer encourages feedback on GitHub and plans to refine the node based on community suggestions.
"I mainly made it because I wanted a faster way to compare sampler/scheduler behavior without manually duplicating KSamplers or changing settings one by one." — Source: Reddit