What’s the difference between Magnific Precise V2 and other upscalers?

Precise V2 focuses on faithful, structure-preserving enhancement. Compared to creative or generative upscalers, it aims to avoid inventing new content and instead sharpens and clarifies what’s already present.

Do I need a GPU for this workflow?

Not necessarily. MagnificImageUpscalerPreciseV2Node is API-based, so most heavy compute runs on Magnific’s servers. Your local machine handles I/O and preview. You do need an internet connection and a valid API key.

What upscale factors are supported, and how do I go beyond them?

Common options are 2x and 4x (depending on your node version). For larger sizes, chain multiple passes: upscale to 2x or 4x, review quality, then feed the result back through for another pass.

Will colors or style change during upscaling?

The Precise model aims to preserve color and composition. Minor differences can occur due to sharpening or texture enhancement. If your node exposes enhancement strength, lower it to minimize stylistic changes.

Image Upscale: Magnific Precise

This ComfyUI workflow takes any input image and produces a high-resolution version with faithful detail using the Magnific Precise V2 model. It starts with LoadImage, routes the image into MagnificImageUpscalerPreciseV2Node (an API-driven upscaler for Magnific), and sends the result to SaveImage. For visual QA, ImageCompare places the original and the upscaled output side by side so you can inspect sharpness, texture preservation, and artifact control before exporting.

Technically, the MagnificImageUpscalerPreciseV2Node submits your image to the Magnific Precise model over the network (API), which focuses on structure-preserving enhancement rather than creative hallucination. You can set the upscale factor (commonly 2x or 4x) and tune enhancement strength if exposed in your build. The node returns a high-res image that maintains original composition and color with improved clarity. Because this is an API node, it requires an active internet connection and your Magnific API key; local GPU memory usage is minimal compared to on-device super-resolution models.

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.

e12d5ef2ea5a.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