Descriptions:
Alibaba’s Qwen Image Layered is a newly released AI model that decomposes images into distinct, independently editable layers with full RGBA transparency support—enabling non-destructive edits to subjects, backgrounds, and text within a single composition. This comprehensive guide from Veteran AI covers how to run the model inside ComfyUI using a workflow originally surfaced in the official ComfyUI GitHub discussion thread, since no formal release channel existed at publication time.
The tutorial explains the model’s unusual architecture: it repurposes Hunyuan Video’s latent space to represent layers as video frames, following the formula of 4× layers + 1 frames (5 frames for one layer, 9 for two, and so on). The video documents the default workflow’s major performance bottleneck—over five minutes of sampling time—then demonstrates an optimization using an 8-step Lightning acceleration model based on Qwen Image Edit 2509, combined with LCM sampling, bringing generation time down to around 58 seconds. Model selection between BF16 (higher quality) and FP8 (lower VRAM) is also covered in detail.
Honest quality notes are included throughout: background artifacts appear in both standard and accelerated runs, layering logic can be inconsistent without explicit prompt guidance, and character segmentation sometimes misses the mark. The creator recommends using text prompts to steer layer separation for more reliable results. The workflow is hosted on RunningHub for those without local GPU access, making this a practical entry point for anyone wanting to experiment with layer-aware AI image editing.
📺 Source: Veteran AI · Published December 23, 2025
🏷️ Format: Tutorial Demo
