Friday project:

Readable rewrite of the hardware-detection module behind @midudev’s canirun-ai. Same heuristics, shaders & spec tables — just descriptive names + JSDoc.

https://t.co/A4Xjb6z7vv

julien-c/canirun.ai

Source: https://github.com/julien-c/canirun.ai

canirun-ai.js

A readable rewrite of the browser-side hardware-detection module used by canirun.ai — the site that tells you which local AI models your machine can run.

The original module ships minified as hardware-ui.<hash>.js. This is the same code with descriptive names, sectioning, JSDoc, and named constants in place of magic numbers. Behavior, thresholds, shaders, and spec tables are unchanged.

What it does

1. Reads what the browser will disclose:
   • WebGL WEBGL_debug_renderer_info → GPU vendor + renderer string
   • WebGPU adapter.info → device + architecture (when available)
   • navigator.deviceMemory, navigator.hardwareConcurrency, User-Agent
2. Benchmarks on-device:
   • CPU: a ~30ms sqrt + sin + cos loop
   • GPU compute (WebGPU): FMA loop → estimated GPU cores
   • GPU memory bandwidth: WebGPU buffer copy, with WebGL texture-sampling fallback
3. Falls back to spec-sheet lookup tables when APIs are blocked or vague (Apple GPUs report only “Apple GPU”; iOS hides everything; mobile vendors refuse to expose adapter info). Includes tables for desktop discrete GPUs, Apple Silicon, mobile SoC GPUs, and SBCs.
4. Scores model fit: classifies a model as can-run, can-run-slow, tight, cannot-run, or unknown, estimates tokens/sec, computes a 0–100 score and a letter grade S–F.

All detection runs locally in the browser — no network calls.

Usage

It’s an ES module:

import { detectHardware, scoreModel, describeDevice } from "./canirun-ai.js";

const hw = await detectHardware();
console.log(describeDevice(hw), hw);

// Score a 7B model that needs ~4.5 GB of memory
const result = scoreModel(4.5, hw, 4.5);
console.log(result); // { status, toksPerSec, memPct, score, grade }

Credits

Original by midudev. This repo is a code-clarity rewrite for educational purposes; the methodology, heuristics, and spec tables are his work.