Powerful multi-reference editing creates precise scenes from separate images.

Who it's for: creators who want this pipeline in ComfyUI without assembling nodes from scratch. Not for: one-click results with zero tuning - you still choose inputs, prompts, and settings.

Open preloaded workflow on RunComfy

Open preloaded workflow on RunComfy (browser)

Why RunComfy first
- Fewer missing-node surprises - run the graph in a managed environment before you mirror it locally.
- Quick GPU tryout - useful if your local VRAM or install time is the bottleneck.
- Matches the published JSON - the zip follows the same runnable workflow you can open on RunComfy.

When downloading for local ComfyUI makes sense - you want full control over models on disk, batch scripting, or offline runs.

How to use (local ComfyUI)
1. Load inputs (images/video/audio) in the marked loader nodes.
2. Set prompts, resolution, and seeds; start with a short test run.
3. Export from the Save / Write nodes shown in the graph.

Expectations - First run may pull large weights; cloud runs may require a free RunComfy account.

Overview

Use multi-reference editing to build one polished scene. You define each image's role in plain English. Prompt enhancement retains key subjects and settings. Create styled rooms or coordinated outfits. Build natural group portraits from separate photos. Get precise results with fewer steps.

Important nodes:

Key nodes in Comfyui Qwen Image 2.1 Multi-image Editing workflow

TextGenerateLTX2Prompt (#502)

This node performs the reference-aware prompt enhancement using a Qwen Image 2.1 PE model. Provide your instruction and the assembled image batch to obtain a single, explicit edit prompt grounded in the references. Increase the allowed length when you need to preserve many object attributes, and adjust sampling options to favor either creative paraphrasing or strictly literal rewrites. The preview node shows exactly what the generator will follow.

TextEncodeQwenImage21 (#519)

Encodes the enhanced prompt and up to ten reference images into conditioning for Qwen-Image-2.1. Use the negative_prompt to forbid unwanted duplicates, collage effects, or extra people. The resolution input sets the working scale for feature extraction; match it to your output for stable detail retention. This node can also emit an initial latent that locks composition more tightly when selected via the switch.

ComfySwitchNode (#483)

Toggles the initiation strategy for KSampler. Keep the default blank latent for freer composition that still respects reference identity through conditioning. Switch to the reference latent from TextEncodeQwenImage21 when you want stronger structural guidance; combine this with lower denoising to emphasize the references.

KSampler (#482)

Drives the denoising process of Qwen-Image-2.1. Use seed to reproduce a specific arrangement or to explore variations. Adjust cfg for how firmly the model follows the enhanced prompt and steps for the quality-speed tradeoff. The sampler_name and scheduler choices can subtly change texture and sharpness; pick a consistent pair when iterating on a look.

ResolutionSelector (#13)

Provides fast control over output width and height. Choose an aspect ratio that comfortably frames all referenced elements. Larger resolutions reveal more texture from the references but require more compute, so increase gradually as your composition settles.

Notes

Qwen Image 2.1 Multi-image Editing | Up to 10 Images Inputs - see RunComfy page for the latest node requirements.