Do I need any extra extensions or custom nodes?

Core nodes (LoadImage, SaveImage, MarkdownNote) are built-in. The workflow uses a Subgraph node (ID cdb2cf24-…) and optionally VHS_LoadVideo for video frames. If you don’t see VHS_LoadVideo, install the VideoHelperSuite (VHS) extension. Then place the provided model files in models/text_encoders and models/loras as noted.

Where do I put the model files?

Place qwen_2.5_vl_7b_fp8_scaled.safetensors in ComfyUI/models/text_encoders and Qwen-Image-Edit-2511-Lightning-4steps-V1.0-bf16.safetensors in ComfyUI/models/loras. Restart ComfyUI so they appear in any model/LoRA selectors inside the subgraph.

How can I get cleaner or more accurate edits?

Use high-quality input images, write precise instructions (mention target objects, colors, and context), and keep the edit scope focused. If results are too strong or weak, adjust the subgraph’s exposed edit controls (e.g., strength/intensity if available) or try slightly different phrasings. Running at moderate resolutions also helps stability.

Can this do masked or region-specific edits?

This template focuses on instruction-based global edits and does not include masking nodes. You can often localize changes by writing specific instructions (e.g., “only change the jacket color to navy”), or you can extend the workflow by adding a masking path if you need precise region control.

How do I turn edited frames back into a video?

This workflow saves frames via SaveImage. After processing, import the numbered image sequence into a video editor or use a command-line tool (e.g., ffmpeg) to encode a video. If you prefer an in-graph export, add a video writer node and connect it after the edit stage.

AI on the Lot 2026_Qwen-Image-Edit-2511

This ComfyUI tutorial workflow shows how to perform fast, instruction-based image edits using Qwen-Image-Edit-2511. It wires a simple I/O path—LoadImage (or VHS_LoadVideo for frames) into a compact Subgraph node (ID cdb2cf24-c432-439b-b5c8-5f69838580c9)—and ends with SaveImage. Inside the subgraph, the edit is driven by the Qwen 2.5 VL text encoder (qwen_2.5_vl_7b_fp8_scaled.safetensors) and a lightweight LoRA tuned for speed (Qwen-Image-Edit-2511-Lightning-4steps-V1.0-bf16.safetensors). The subgraph encapsulates the model plumbing so you can focus on a plain-language instruction like “make the sky overcast” or “remove the background,” then preview results quickly.

Technically, the workflow routes your source image (or video frames) into the subgraph, where the Qwen 2.5 VL encoder interprets your instruction text and conditions the edit. The Qwen-Image-Edit-2511 Lightning LoRA applies the learned edit behavior while keeping inference fast with very few sampling steps. Because this is packaged as a Subgraph, you get a clean graph and consistent defaults—you can double-click or open the subgraph to inspect or tweak internals as needed. SaveImage captures each result frame to disk; when fed by VHS_LoadVideo, you’ll get a numbered image sequence you can reassemble externally if you want a final video.

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.

a6b2c3fe248c.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 this workflow (TypeScript)
import { Comfy } from "@comfyorg/sdk";

const client = new Comfy({ apiKey: "comfyui-..." });
const wf = await client.workflows.fromFile("workflow_api.json");
const job = await client.run(wf);
await job.getOutputs("<output-node-id>")[0].toFile("output.png");

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