# pixiv/three-vrm

Use VRM on Three.js

Repository: https://github.com/pixiv/three-vrm
Canonical: https://ross.abutalabs.com/products/three-vrm
Language: TypeScript
License: MIT
License Family: permissive
Topics: gltf, threejs, vrm, 3d, avatar, webgl
Last push: 2026-08-26T05:02:50+00:00

## Health v2 (maintenance only)
Score: 97/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 92, longevity 100
- inputs: {"age_days": 2647, "days_push": 7, "days_rel": 55, "gap_med": 18.5, "n_releases_24m": 27}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2131, forks 186 (observed 2026-08-28T04:06:17.212091+00:00)

## What it is
A Three.js plugin library by pixiv that adds VRM 3D avatar model support to GLTFLoader. It enables loading, rendering, and manipulating VRM humanoid avatars in WebGL/WebGPU browser applications.

## Use cases
- load VRM avatar models in a three.js scene
- build a VTuber-style 3D character viewer in the browser
- render anime-style humanoid avatars on the web
- animate VRM characters with expressions and look-at in WebGL
- display 3D avatars in a metaverse or chat web app
- convert GLTF loading pipelines to support VRM files

## When to choose
- your project already uses three.js and needs VRM avatar support
- you want a maintained, MIT-licensed VRM loader for the browser
- you need VRM 1.0 support with WebGPURenderer compatibility

## When to avoid
- you are not using three.js as your rendering engine
- you need server-side or offline VRM processing rather than browser rendering
- you need a full game engine rather than a rendering library

## Facets
- artifact type: library
- maturity: active
- function: graphics, image-processing, sdk
- domain: web-development, graphics
- platform: browser, wasm
- tags: vrm, threejs, gltf, avatar, webgl, 3d-models, vtuber, game-development, nodejs, web-server

## Member repositories
- pixiv/three-vrm (main) score 97

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:17.212091+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:52:11.974074+00:00, confidence not recorded.
  - readme: https://github.com/pixiv/three-vrm (fetched 2026-08-28T04:06:17.212091+00:00, sha e321f591c016)
- Data as of 2026-08-30T08:39:29.467469+00:00.