Where do I get the Qwen-Image model files, and how do I install them?

Download from the Comfy-Org/Qwen-Image_ComfyUI repositories on Hugging Face or Modelscope. Follow the repo’s placement instructions (typically within your ComfyUI models directory). Then select the checkpoint in the Qwen-Image node.

What resolutions work best for clean text rendering?

Use the provided presets tested with this workflow: 1328×1328 (1:1), 1664×928 (16:9), 928×1664 (9:16), and 1472×1140 (4:3). Larger sizes can improve readability but increase VRAM and render time.

How much VRAM do I need, and what is FP8 e4m3fn?

On an RTX 4090D 24GB, FP8 e4m3fn runs efficiently and can render a first image in roughly 90 seconds, with later runs faster depending on settings. FP8 e4m3fn is a low-precision configuration that reduces memory use. If you have less VRAM, lower the resolution or use a lighter precision/checkpoint if available.

How can I improve the clarity of multilingual text in the image?

Be explicit and concise about the text and language in your prompt; avoid overly long, complex instructions when you need sharp typography. Choose a suitable resolution preset, prefer high-contrast backgrounds, and iterate on wording if characters look ambiguous.

Qwen-Image: Text to Image - ComfyUI Workflow

This workflow demonstrates text-to-image generation with Qwen-Image’s 20B MMDiT diffusion transformer inside ComfyUI. It centers on a dedicated Qwen-Image generation node (UUID: e5cfe5ba-2ae0-4bc4-869f-ab2228cb44d3), which loads the Qwen-Image model weights and produces an image directly from your prompt. A MarkdownNote node provides inline guidance within the graph, and a SaveImage node writes the final output to your ComfyUI output directory.

Technically, the Qwen-Image node runs the 20B MMDiT model end-to-end, handling prompt conditioning and diffusion steps internally. The official model files are available from the Comfy-Org/Qwen-Image_ComfyUI repositories (Hugging Face or Modelscope). The workflow supports practical presets for aspect ratios and resolutions (e.g., 1328×1328 for 1:1, 1664×928 for 16:9, 928×1664 for 9:16, 1472×1140 for 4:3). On an RTX 4090D 24GB, the FP8 e4m3fn configuration has been observed to complete a first image in roughly 90 seconds and subsequent images faster, depending on settings. Qwen-Image is designed to render multilingual text inside images, making it well-suited for posters, signage, UI mocks, and other graphics where readable text is important.

API

Use this workflow from code

Every Comfy workflow is a JSON graph. The payload below is this workflow, exactly as ComfyUI runs it — fetch it from the URL, keep it in version control, or load it in ComfyUI and run it node by node.

image_qwen_image.json

Fetching workflow JSON…

Run it from TypeScript or Python with the Comfy SDK. The same code targets Comfy Cloud or a ComfyUI you host yourself — only the base URL changes.

// Install (beta)
npm i @comfyorg/sdk

// Run "Qwen-Image: Text to Image" (TypeScript)
import { Comfy } from "@comfyorg/sdk";

const client = new Comfy({ apiKey: "comfyui-..." });

// This workflow, exported in API format (see note below)
const wf = await client.workflows.fromFile("image_qwen_image_api.json");

const job = await client.run(wf);
await job.getOutputs("60")[0].toFile("output.png");  // SaveImage

The SDK takes a workflow in API format: open this workflow in ComfyUI and use File → Export Workflow (API).

Comfy Cloud API access requires a plan with an API key.

SDK docs Get an API key

FAQ

Frequently Asked Questions