27.5KB language-agnostic WebGPU syntax highlighter

83 points by bpierre 8 hours ago on hackernews | 26 comments

import { highlight } from 'gpu-lexer'

const spans = await highlight('source code')
// {
//   type: 'plain' | 'comment' | 'string' | 'number' | 'keyword' | 'type' | 'function' | 'constant' | 'operator'
//   start: number
//   end: number
// }[]

gpu-lexer splits source code into simple parts—words, whitespace, newlines, and symbols. Then a tiny WebGPU model combines local and whole-file context to label each part. It is designed for any language: instead of choosing a grammar, it guesses each part's type from the surrounding source, even when it never saw that language or syntax during training. Adjacent labels become the highlight spans returned to your code.

This is an experiment, not a grammar-equivalent highlighter. On files kept out of training, 12.57% of the current model's token labels differ from Shiki. This measures agreement with Shiki—not objective correctness—and unseen languages or real-world code may differ more often.

Highlight 10× three.min.jswarmed browser time · lower is better

One browser run after one warm-up on September 8, 2026. The input was 10 concatenated copies of three.min.js (5.56M characters). MacBook Pro, Apple M4 Pro, 20-core GPU, 24GB, macOS 26.6.2, Chrome 152. Each engine ran in a dedicated worker; DOM rendering was excluded. gpu-lexer and Shiki returned token data, Starry Night returned a HAST tree, while Sugar High, Prism.js, and Highlight.js returned highlighted HTML. Sugar High 2.3.1, Prism.js 1.30.0, Highlight.js 11.12.0, Starry Night 3.11.0, and Shiki 4.4.3.

Loaded library sizeruntime + selected language coverage · lower is better

Minified and Brotli-compressed browser bundles measured on September 8, 2026. Major web includes javascript, typescript, css, html, json, and markdown. gpu-lexer uses the same bundle for every language. Starry Night totals include its Oniguruma WASM payload.

Top-25 weighted correctnesspopularity-weighted agreement with Shiki · higher is better

Shiki is the 100% normalization reference. Each library's token names are mapped to the same nine classes: plain, comment, string, number, keyword, type, function, constant, and operator. Scores compare non-whitespace source parts across 1,069 held-out files in the GitHub Innovation Graph top 25 for 2026-Q1, weighted by each language's pusher count. Unsupported languages score zero; corpus size does not affect the weights.

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75 languages

react.development.js0 bytes