Skip to main content

​
ComfyUI MoGe Introduction

MoGe (CVPR 2025, from Microsoft Research) is a powerful model for recovering 3D geometry from monocular open-domain images. It estimates metric point maps, metric depth maps, normal maps, and camera FOV: all in a single forward pass. Key capabilities:
  • Accurate 3D geometry estimation: point maps, depth maps, and normal maps from a single image: one model, one forward pass
  • Metric scale (MoGe-2): point maps and depth maps in real-world scale
  • Flexible resolution support: works with various resolutions and aspect ratios (2:1 to 1:2)
  • Fast inference: ~60ms per image on A100 / RTX 3090 (FP16, ViT-L)
  • Mesh generation from both perspective and panoramic images
MoGe comes in two versions:
MoGe-2 adds metric scale and high-quality normal map estimation with sharper visual detail and lower inference latency. MoGe-2 with normal (moge_2_vitl_normal_fp16) is the recommended checkpoint.
Make sure your ComfyUI is updated.Workflows in this guide can be found in the Workflow Templates. If you can’t find them in the template, your ComfyUI may be outdated.If nodes are missing when loading a workflow, possible reasons:
  1. You are not using the latest ComfyUI version (Nightly version)
  2. Some nodes failed to import at startup
ComfyUI now natively supports MoGe nodes. Make sure you have updated to the latest version of ComfyUI before starting.Generated .glb format models will be output to the ComfyUI/output/mesh folder.

​
Model Installation

Download the MoGe checkpoint(s) and save them to the corresponding ComfyUI folder:

​
Example Workflows

​
MoGe: Depth Estimation

Upload a single RGB image and generate a colored depth preview and raw depth map. MoGe depth estimation workflow preview

Run on Comfy Cloud

Open in Comfy Cloud

Download Workflow

Download JSON or search “MoGe: Depth Estimation” in Template Library
Input materials Upload this file to the matching LoadImage node:

alien_world.png

LoadImage node 9 · alien_world.png

​
1.1 Steps to Run

  1. Ensure the LoadMoGeModel node has loaded a MoGe checkpoint
  2. Load an image in the Load Image node
  3. Click Queue or use Ctrl(cmd) + Enter to run
  4. The workflow outputs colored depth preview, raw depth preview, and a mask

​
MoGe: Perspective Geometry Estimation

Upload an image to estimate its perspective geometry. Generate a 3D depth map and surface normals from the input, then convert to a textured GLB mesh. MoGe perspective to mesh workflow preview

Run on Comfy Cloud

Open in Comfy Cloud

Download Workflow

Download JSON or search “MoGe: Perspective Geometry Estimation” in Template Library
Input materials Upload this file to the matching LoadImage node:

modern_living_room.png

LoadImage node 9 · modern_living_room.png
Input image
This is monocular geometry estimation: occluded areas and object backsides will be missing or fragmented. Useful for quick scene prototyping, reference geometry, or visualizing depth and normals as a mesh, but not a replacement for multi-view 3D reconstruction.

​
2.1 Steps to Run

  1. Ensure the LoadMoGeModel node has loaded a MoGe checkpoint
  2. Load a perspective photo in the Load Image node
  3. (Optional) View the OpenGL and DirectX normal previews
  4. Click Queue or use Ctrl(cmd) + Enter to run

​
Moge: Panorama to Mesh

Upload an equirectangular 360° panorama image and generate a textured GLB mesh with vertex colors. MoGe panorama to mesh workflow preview

Run on Comfy Cloud

Open in Comfy Cloud

Download Workflow

Download JSON or search “Moge: Panorama to Mesh” in Template Library
Input materials Upload this file to the matching LoadImage node:

lego_street_panorama.png

LoadImage node 28 · lego_street_panorama.png
Input panorama
The workflow uses MoGePanoramaInference to split the panorama into 12 perspective views, run monocular geometry estimation on each view independently, then merge them into a single mesh.

​
3.1 Steps to Run

  1. Ensure the LoadMoGeModel node has loaded one of the MoGe checkpoints
  2. Load an equirectangular panorama image in the Load Image node
  3. Click Queue or use Ctrl(cmd) + Enter to run

​
Community Resources