Nodes/AUN ComfyUI Nodes/Inputs Refine Basic
ComfyUI Node

Inputs Refine Basic

Basic inputs plus an optional refine checkpoint — no filename baggage

By loz2754·Created 10 months ago·Updated a day ago· 8
Inputs Refine Basic
  • ref_image
  • bundle_input
  • MODEL
  • CLIP
  • VAE
  • MODEL REFINE
  • ckpt name
  • ckpt name refine
  • sampler
  • scheduler
  • cfg
  • steps
  • latent
  • width
  • height
  • seed
  • batch size
  • speed lora ratio
  • bundle
◄ckpt_name▾►
◄refine_ckptNone►
◄speed_lorafalse►
◄speed_lora_modelNone►
◄speed_lora_strength1.00►
◄speed_lora_full_bothfalse►
◄speed_lora_ratio1.00►
◄clip_skip-1►
◄sampler▾►
◄scheduler▾►
◄cfg2.0►
◄steps10►
◄width720►
◄height720►
◄aspect_ratio▾►
◄aspect_modeOriginal►
◄batch_size1►
◄seed0►
◄megapixels1.0►
◄multiple8►
◄set►

AUNInputsRefineBasic is the "Basic" version of the refine idea: it keeps the lighter Inputs Basic contract - checkpoint, sampler settings, empty latent - and adds one thing, an optional second model for a refinement pass. No save-prep outputs, no legacy filename sockets. It's the recommended-shaped node for anyone who wants the "generate then refine with a second checkpoint" pattern without the full Inputs node's wall of save machinery.

What it does

Load the main checkpoint with ckpt_name, then optionally refine_ckpt - select 'None' to reuse the main model for refinement. When you pick a separate refine checkpoint you get a second MODEL REFINE output (and ckpt name refine) to feed a refinement sampler. The rest is the Basic contract: sampler/scheduler/cfg/steps, aspect_ratio/width/height with aspect_mode and megapixels/multiple, batch_size, seed, clip_skip, and the SpeedLoRA group.

The SpeedLoRA handling is where refine nodes earn their keep: speed_lora_full_both applies the full strength to both main and refine models, while speed_lora_ratio splits it (main model gets that fraction, refiner gets the rest). Outputs include the resolved speed lora ratio, so you can see what landed where. A SpeedLoRA tuned for composition can fight a refiner; splitting it is often the difference between a cleaner final pass and a muddy one.

Inputs and outputs

Inputs: ckpt_name, refine_ckpt, SpeedLoRA group, clip_skip, sampler/scheduler/cfg/steps, aspect_ratio/width/height/aspect_mode, batch_size, seed, megapixels, multiple.

Outputs: MODEL, CLIP, VAE, MODEL REFINE, ckpt name, ckpt name refine, sampler, scheduler, cfg, steps, latent, width, height, seed, batch size, speed lora ratio.

Installing it

Same pack, same install:

  • ComfyUI Manager: search "AUN ComfyUI Nodes", install, restart.
  • Manual: cd custom_nodes && git clone https://github.com/loz2754/AUN-ComfyUI-Nodes, then restart.

Manual installs and a ModuleNotFoundError: cv2 error? pip install -r custom_nodes/AUN-ComfyUI-Nodes/requirements.txt.

Common issues

If an old workflow using this node loads with SpeedLoRA widgets that look off, the README's migration note covers it - the input set changed and widgets may need re-checking or reconnecting. Otherwise the same rules as the other Basic nodes: this node has no filename outputs (plan save naming separately), and when the refiner misbehaves, adjust the speed_lora_ratio split before chasing sampler settings.

CategoryAUN Nodes/Loaders+Inputs

Inputs (23)

NameTypeDefaultDescription
ckpt_nameCOMBOThe checkpoint model file to load.
refine_ckptCOMBONoneAn optional refinement checkpoint to load as a separate refine model. Select 'None' to reuse the main model.
speed_loraBOOLEANfalseEnable or disable SpeedLoRA optimizations.
speed_lora_modelCOMBONoneThe SpeedLoRA model to apply. Select 'None' to disable SpeedLoRA.
speed_lora_strengthFLOAT1.000–3Multiplier applied to the selected SpeedLoRA weights.
speed_lora_full_bothBOOLEANfalseApply the full SpeedLoRA strength to both the main and refine models.
speed_lora_ratioFLOAT1.000–1Share of the SpeedLoRA strength applied to the main model. The refine model receives the remaining share.
clip_skipINT-1-24–-1Number of last layers of CLIP to skip. -1 is a good default.
samplerCOMBOThe sampling algorithm to use.
schedulerCOMBOThe noise schedule to use.
cfgFLOAT2.0-2–100Classifier-Free Guidance scale. Higher values increase prompt adherence.
stepsINT101–10000Number of sampling steps.
widthINT72064–8192Image width. Used when 'aspect_ratio' is 'custom'.
heightINT72064–8192Image height. Used when 'aspect_ratio' is 'custom'.
aspect_ratioCOMBOSelect a predefined aspect ratio or ratio to automatically set width and height.
aspect_modeCOMBOOriginalRandom swaps dimensions 50% of the time, Swap forces a swap, Original keeps the original order.
batch_sizeINT11–64Number of latent images to generate in a batch.
seedINT0-18446744073709550000–18446744073709550000The random seed for generation.
megapixelsFLOAT1.00.1–16Target total megapixels used when a ratio is selected.
multipleINT88–128Nearest multiple to round computed resolution to. Used with ratio.
ref_imageoptIMAGEOptional reference image. When connected, aspect_mode is set automatically to match its orientation.
bundle_inputoptOBVPM_BUNDLEOptional OBVPM bundle override.
setoptSTRINGConstant name. When non-empty, sets an OBVPM bundle constant.

Outputs (17)

NameTypeDescription
MODELMODEL—
CLIPCLIP—
VAEVAE—
MODEL REFINEMODEL—
ckpt nameSTRING—
ckpt name refineSTRING—
sampler*—
scheduler*—
cfgFLOAT—
stepsINT—
latentLATENT—
widthINT—
heightINT—
seedINT—
batch sizeINT—
speed lora ratioFLOAT—
bundleOBVPM_BUNDLE—