KSampler Matrix Lab compares sampler and scheduler combinations with one model.
Model Matrix Lab compares multiple installed models with one sampler and scheduler.

Both nodes run tests sequentially and return one labeled IMAGE output that can be connected to Preview Image or Save Image.

Features

Compare sampler and scheduler combinations in a single grid.
Dynamic sampler and scheduler dropdowns from the local ComfyUI installation.
Up to 9 sampler slots and 9 scheduler slots.
None option for unused sampler or scheduler slots.
Sequential generation to avoid large all-at-once batches.
Same-seed comparison mode.
Increment-per-cell seed mode.
Per-cell labels with sampler and scheduler names.
Top run header with model, VAE, CLIP, steps, CFG, and denoise metadata.
Error placeholder cells when continue_on_error is enabled.
Safety limit for maximum combinations.
Compare up to 20 checkpoints or standalone diffusion models.
Automatically populated model dropdowns from local ComfyUI model folders.
Shared prompt, sampler, scheduler, seed, steps, CFG, denoise, and latent for model comparisons.
Configurable model grid column count.

Screenshots

Node

Example Workflow

Output Grid

Installation

Clone this repository into your ComfyUI custom_nodes directory:

cd ComfyUI/custom_nodes
git clone https://github.com/btitkin/ComfyUI-KSampler-Matrix-Lab.git

Restart ComfyUI after installation.

Nodes

The package adds:

KSampler Matrix Lab
Model Matrix Lab

Category:

ComfyUI-KSampler-Matrix-Lab

Output:

IMAGE

Included Workflow

The example workflow contains ready-to-use setups for both nodes:

Workflows/KSamplerMatrixLab_Workflow.json

Drag the JSON file into ComfyUI or use Workflow > Open to load it.

KSampler Matrix Lab Workflow

Use the node with a standard ComfyUI generation workflow:

Load Checkpoint / model loader
CLIP Text Encode positive
CLIP Text Encode negative
Empty Latent Image
KSampler Matrix Lab
Preview Image or Save Image

Connect:

MODEL to model
positive conditioning to positive
negative conditioning to negative
latent to latent_image
VAE to vae

Model Matrix Lab

Model Matrix Lab compares installed models using the same generation settings and prompt text.

Screenshots

Node

Output Grid

The node scans:

ComfyUI/models/checkpoints
ComfyUI/models/unet
ComfyUI/models/diffusion_models

It provides model slots:

model_01 ... model_20

Set unused slots to None. Model choices are labeled as either:

checkpoint | filename
diffusion | filename

Checkpoint selections use their embedded CLIP and VAE when available. Standalone diffusion models require compatible external CLIP and VAE connections. These optional connections are also used as fallbacks when a checkpoint does not contain its own CLIP or VAE.

Use the text fields inside the node for the positive and negative prompts. This allows every checkpoint to encode the same text with its own text encoder.

Connect:

LATENT to latent_image
a compatible external CLIP to the optional clip input when required
a compatible external VAE to the optional vae input when required

All selected models use the same:

latent,
seed,
sampler,
scheduler,
steps,
CFG,
denoise.

The output is a configurable model comparison grid with the model source and filename above each cell. The optional top header shows the shared sampler, scheduler, steps, CFG, and denoise settings.

Sampler and Scheduler Selection

The node provides dropdown slots:

sampler_01 ... sampler_09
scheduler_01 ... scheduler_09

Set unused slots to:

None

Duplicate sampler or scheduler selections are ignored after the first occurrence.

Grid Layout

The final image grid uses:

columns for schedulers,
rows for samplers,
generated images as cells,
optional grid lines,
repeated per-cell sampler/scheduler labels,
an optional top metadata header.

The top metadata header includes:

Model
VAE
CLIP
Steps
CFG
Denoise

Model, VAE, and CLIP names are inferred from the ComfyUI workflow when possible. Some custom loaders may not expose enough metadata, in which case the header may show unknown.

Seed Modes

same_seed_for_all

Uses the same seed for every cell. This is best for direct sampler/scheduler comparison.

increment_per_cell

Uses seed + cell_index for each cell. This is useful for quick variation previews.

Error Handling

When continue_on_error is enabled, a failed sampler/scheduler combination or model produces an error placeholder cell and the rest of the matrix continues.

When disabled, the node stops on the first failed test.

Notes

Generation is sequential by design.
Very large grids can use significant RAM during final image composition.
If the input latent batch size is greater than 1, the first decoded image is used for each grid cell.
Full behavior depends on the samplers and schedulers available in the local ComfyUI installation.

License

MIT