This workflow generates high-quality images from text prompts using Qwen Image 2.1, an open-weight diffusion model known for strong layout and typography rendering and native 2K (2048×2048) output. At its core is a custom Qwen generator node (UUID: c291ceec-b98f-4751-9d0b-7bc288f27b30) that loads either qwen_image_2.1_bf16.safetensors or the memory-saving qwen_image_2.1_int8_convrot.safetensors. By default, it produces a single 1024×1024 image in about 25 sampling steps, with support for transparent (alpha) backgrounds when saved as PNG. ResolutionSelector sets the canvas size, and SaveImageAdvanced handles file output and metadata.

Technically, the subgraph encapsulates prompt conditioning and a built-in sampler inside the Qwen node, so you don’t need separate sampler nodes. You provide a prompt (and optionally a negative prompt if exposed), choose a resolution, and the node performs the full diffusion pass. The workflow’s MarkdownNote/Note nodes document on-canvas instructions, while SaveImageAdvanced ensures your output is written with correct color and alpha handling. This makes it ideal for fast concept visualizations, posters, and assets that benefit from clean text and layout—without leaving the ComfyUI canvas.