This workflow compares two editing strategies in Nano Banana 2.1—prompt-only global edits versus mask-guided local edits—using a single model node (GeminiNanoBanana2V2) and a consistent pipeline. It loads your image (e.g., the provided silver_frame_profile.png), applies your natural-language edit, and renders a side-by-side before/after via ImageCompare so you can judge impact at a glance. Running once without a mask showcases broad, scene-wide transformations; running with a mask constrains changes to selected regions while preserving the rest.
Methodologically, you keep the same prompt and parameters and only toggle whether a mask is supplied to GeminiNanoBanana2V2. This isolates the effect of masking: global edits offer cohesive stylistic shifts but risk drifting subjects and text, while masked edits improve control and identity retention but may show edge artifacts if the mask is hard. SaveImageAdvanced preserves versioned outputs, and MarkdownNote helps you log prompts, mask intent, and observations across runs for repeatable, defensible comparisons.
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.
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.
FAQ
