Nabil Asofi

Library / ComfyUI

ComfyUI Thumbnail Factory

Generate a batch of consistent thumbnail backgrounds from one prompt, with room for the title left clear.

Setup time
30 min
Stack
ComfyUILLM API
Replaces
an hour of scrolling stock libraries and still not matching your last ten thumbnails

What it does, in order

ComfyUI Thumbnail Factory — pipeline of 4 steps Pipeline of 4 steps: 1. Set subject and palette (LLM API); 2. Generate the batch (ComfyUI); 3. Hold the palette (ComfyUI); 4. Cut to the safe area (ComfyUI). 01 Set subject and palette LLM API 02 Generate the batch ComfyUI 03 Hold the palette ComfyUI 04 Cut to the safe area ComfyUI ComfyUI Thumbnail Factory — pipeline of 4 steps Pipeline of 4 steps: 1. Set subject and palette (LLM API); 2. Generate the batch (ComfyUI); 3. Hold the palette (ComfyUI); 4. Cut to the safe area (ComfyUI). 01 Set subject and palette LLM API 02 Generate the batch ComfyUI 03 Hold the palette ComfyUI 04 Cut to the safe area ComfyUI
4 steps. The final node is the artifact you end up with.

What this does

A batch generator for thumbnail plates. Give it a subject and a palette; it returns a set of images in the same visual family, each composed with the subject pushed to one side and empty space where the title goes.

It generates backgrounds, not finished thumbnails. Text rendered inside a diffusion model is unreliable, and a misspelled title costs you more than the time you saved. Compose the words in your editor over a clean plate.

What you get

  • The workflow JSON, with batch size and seed increment wired so one run produces many variations
  • A composition guide: where to leave space and how much, for the aspect ratios you actually post
  • The palette-locking node group, so every run stays in the same colour family
  • A prompt sheet including the negative prompt that stops the usual mess

What it replaces

The stock-photo crawl — forty minutes of scrolling, one download, and a thumbnail that does not match the previous ten.

Honest limits

It cannot render your title. Keep text out of the model entirely and set it afterwards.

Generated faces are the weak point. In a thumbnail they read as generated, and audiences have become good at spotting it. Use this for objects, scenes, textures and abstract plates; put a real person in the frame only when you have a real person to photograph.

Expect roughly two unusable images in every ten. That is what batching is for.