# mikbry/awesome-webgpu

😎 Curated list of awesome things around WebGPU ecosystem.

Repository: https://github.com/mikbry/awesome-webgpu
Canonical: https://ross.abutalabs.com/products/awesome-webgpu
License: CC0-1.0
License Family: permissive
Topics: webgpu, webgl, w3c, javascript, 3d, gpu-computing, awesome-list, awesome
Last push: 2026-01-21T09:09:35+00:00

## Health v2 (maintenance only)
Score: 61/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 63, release rhythm 35, longevity 100
- inputs: {"age_days": 2393, "days_push": 224, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1965, forks 109 (observed 2026-08-28T04:05:59.863986+00:00)

## What it is
A curated awesome-list of WebGPU resources including specifications, tutorials, libraries, demos, and debugging tools. It serves as a reference hub for the W3C WebGPU standard for modern 3D rendering and GPU computing in the browser.

## Use cases
- find webgpu tutorials and learning materials
- discover webgpu libraries and frameworks
- check webgpu browser support status
- learn wgsl shading language
- find webgpu demos and examples
- locate webgpu debugging and profiling tools

## When to choose
- you are starting to learn WebGPU and want a single entry point
- you need to survey the WebGPU ecosystem for libraries or tools
- you want up-to-date links to specs, docs, and community resources

## When to avoid
- you need an actual WebGPU implementation or runtime library
- you want a tutorial rather than a link collection
- you are looking for WebGL or OpenGL resources specifically

## Facets
- artifact type: learning-resource
- maturity: active
- function: graphics, gpu-computing, developer-tools
- domain: web-development, graphics, awesome-lists, tutorials
- platform: browser
- tags: webgpu, awesome-list, wgsl, 3d-graphics, curated-resources, web-server

## Member repositories
- mikbry/awesome-webgpu (main) score 61

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:59.863986+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 2026-08-30T03:05:28.769840+00:00, confidence not recorded.
  - readme: https://github.com/mikbry/awesome-webgpu (fetched 2026-08-28T04:05:59.863986+00:00, sha 82955b8beda2)
- Data as of 2026-08-30T08:39:29.467469+00:00.