Turbopack logo

Turbopack

Organization
vercel
turbopack

Turbopack expert guidance. Use when configuring the Next.js bundler, optimizing HMR, debugging build issues, or understanding the Turbopack vs Webpack differences.

Overview

Publishervercel
Repositoryvercel-plugin
Skill nameturbopack
Stars
286
Forks
56
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by vercel on GitHub. Read the source before you install it.

Installation

Install the Turbopack AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/vercel/vercel-plugin.git /tmp/vercel-plugin
mkdir -p .claude/skills
cp -r /tmp/vercel-plugin/skills/turbopack .claude/skills/turbopack
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Turbopack in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Turbopack on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Turbopack is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Turbopack

You are an expert in Turbopack — the Rust-powered JavaScript/TypeScript bundler built by Vercel. It is the default bundler in Next.js 16.

Key Features

  • Instant HMR: Hot Module Replacement that doesn't degrade with app size
  • File System Caching (Stable): Dev server artifacts cached on disk between restarts — up to 14x faster startup on large projects. Enabled by default in Next.js 16.1+, no config needed. Build caching planned next.
  • Multi-environment builds: Browser, Server, Edge, SSR, React Server Components
  • Native RSC support: Built for React Server Components from the ground up
  • TypeScript, JSX, CSS, CSS Modules, WebAssembly: Out of the box
  • Rust-powered: Incremental computation engine for maximum performance

Configuration (Next.js 16)

In Next.js 16, Turbopack config is top-level (moved from experimental.turbopack):

js
// next.config.ts
import type { NextConfig } from 'next'

const nextConfig: NextConfig = {
  turbopack: {
    // Resolve aliases (like webpack resolve.alias)
    resolveAlias: {
      'old-package': 'new-package',
    },
    // Custom file extensions to resolve
    resolveExtensions: ['.ts', '.tsx', '.js', '.jsx', '.json'],
  },
}

export default nextConfig

CSS and CSS Modules Handling

Turbopack handles CSS natively without additional configuration.

Global CSS

Import global CSS in your root layout:

tsx
// app/layout.tsx
import './globals.css'

CSS Modules

CSS Modules work out of the box with .module.css files:

tsx
// components/Button.tsx
import styles from './Button.module.css'

export function Button({ children }) {
  return <button className={styles.primary}>{children}</button>
}

PostCSS

Turbopack reads your postcss.config.js automatically. Tailwind CSS v4 works with zero config:

js
// postcss.config.js
module.exports = {
  plugins: {
    '@tailwindcss/postcss': {},
    autoprefixer: {},
  },
}

Sass / SCSS

Install sass and import .scss files directly — Turbopack compiles them natively:

bash
npm install sass
tsx
import styles from './Component.module.scss'

Common CSS pitfalls

  • CSS ordering differs from webpack: Turbopack may load CSS chunks in a different order. Avoid relying on source-order specificity across files — use more specific selectors or CSS Modules.
  • @import in global CSS: Use standard CSS @import — Turbopack resolves them, but circular imports cause build failures.
  • CSS-in-JS libraries: styled-components and emotion work but require their SWC plugins configured under compiler in next.config.

Tree Shaking

Turbopack performs tree shaking at the module level in production builds. Key behaviors:

  • ES module exports: Only used exports are included — write export on each function/constant rather than barrel export *
  • Side-effect-free packages: Mark packages as side-effect-free in package.json to enable aggressive tree shaking:
json
{
  "name": "my-ui-lib",
  "sideEffects": false
}
  • Barrel file optimization: Turbopack can skip unused re-exports from barrel files (index.ts) when the package declares "sideEffects": false
  • Dynamic imports: import() expressions create async chunk boundaries — Turbopack splits these into separate chunks automatically

Diagnosing large bundles

Built-in analyzer (Next.js 16.1+, experimental): Works natively with Turbopack. Offers route-specific filtering, import tracing, and RSC boundary analysis:

ts
// next.config.ts
const nextConfig: NextConfig = {
  experimental: {
    bundleAnalyzer: true,
  },
}

Legacy @next/bundle-analyzer: Still works as a fallback:

bash
ANALYZE=true next build
ts
// next.config.ts
import withBundleAnalyzer from '@next/bundle-analyzer'

const nextConfig = withBundleAnalyzer({
  enabled: process.env.ANALYZE === 'true',
})({
  // your config
})

Custom Loader Migration from Webpack

Turbopack does not support webpack loaders directly. Here is how to migrate common patterns:

Webpack LoaderTurbopack Equivalent
css-loader + style-loaderBuilt-in CSS support — remove loaders
sass-loaderBuilt-in — install sass package
postcss-loaderBuilt-in — reads postcss.config.js
file-loader / url-loaderBuilt-in static asset handling
svgr / @svgr/webpackUse @svgr/webpack via turbopack.rules
raw-loaderUse import x from './file?raw'
graphql-tag/loaderUse a build-time codegen step instead
worker-loaderUse native new Worker(new URL(...)) syntax

Configuring custom rules (loader replacement)

For loaders that have no built-in equivalent, use turbopack.rules:

js
// next.config.ts
const nextConfig: NextConfig = {
  turbopack: {
    rules: {
      '*.svg': {
        loaders: ['@svgr/webpack'],
        as: '*.js',
      },
    },
  },
}

When migration isn't possible

If a webpack loader has no Turbopack equivalent and no workaround, fall back to webpack:

js
const nextConfig: NextConfig = {
  bundler: 'webpack',
}

File an issue at github.com/vercel/next.js — the Turbopack team tracks loader parity requests.

Production Build Diagnostics

Build failing with Turbopack

  1. Check for unsupported config: Remove any webpack() function from next.config — it's ignored by Turbopack and may mask the real config
  2. Verify turbopack.rules: Ensure custom rules reference valid loaders that are installed
  3. Check for Node.js built-in usage in edge/client: Turbopack enforces environment boundaries — fs, path, etc. cannot be imported in client or edge bundles
  4. Module not found errors: Ensure turbopack.resolveAlias covers any custom resolution that was previously in webpack config

Build output too large

  • Audit "use client" directives — each client component boundary creates a new chunk
  • Check for accidentally bundled server-only packages in client components
  • Use server-only package to enforce server/client boundaries at import time:
bash
npm install server-only
ts
// lib/db.ts
import 'server-only' // Build fails if imported in a client component

Comparing webpack vs Turbopack output

Run both bundlers and compare:

bash
# Turbopack build (default in Next.js 16)
next build

# Webpack build
BUNDLER=webpack next build

Compare .next/ output sizes and page-level chunks.

Performance Profiling

HMR profiling

Enable verbose HMR timing in development:

bash
NEXT_TURBOPACK_TRACING=1 next dev

This writes a trace.json to the project root — open it in chrome://tracing or Perfetto to see module-level timing.

Build profiling

Profile production builds:

bash
NEXT_TURBOPACK_TRACING=1 next build

Look for:

  • Long-running transforms: Indicates a slow SWC plugin or heavy PostCSS config
  • Large module graphs: Reduce barrel file re-exports
  • Cache misses: If incremental builds aren't hitting cache, check for files that change every build (e.g., generated timestamps)

Memory usage

Turbopack's Rust core manages its own memory. If builds OOM:

  • Increase Node.js heap: NODE_OPTIONS='--max-old-space-size=8192' next build
  • Reduce concurrent tasks if running inside Turborepo: turbo build --concurrency=2

Turbopack vs Webpack

FeatureTurbopackWebpack
LanguageRustJavaScript
HMR speedConstant (O(1))Degrades with app size
RSC supportNativePlugin-based
Cold startFastSlower
EcosystemGrowingMassive (loaders, plugins)
Status in Next.js 16DefaultStill supported
Tree shakingModule-levelModule-level
CSS handlingBuilt-inRequires loaders
Production buildsSupportedSupported

When You Might Need Webpack

  • Custom webpack loaders with no Turbopack equivalent
  • Complex webpack plugin configurations (e.g., ModuleFederationPlugin)
  • Specific webpack features not yet in Turbopack (e.g., custom externals functions)

To use webpack instead:

js
// next.config.ts
const nextConfig: NextConfig = {
  bundler: 'webpack', // Opt out of Turbopack
}

Development vs Production

  • Development: Turbopack provides instant HMR and fast refresh
  • Production: Turbopack handles the production build (replaces webpack in Next.js 16)

Common Issues

  1. Missing loader equivalent: Some webpack loaders don't have Turbopack equivalents yet. Check Turbopack docs for supported transformations.
  2. Config migration: Move experimental.turbopack to top-level turbopack in next.config.
  3. Custom aliases: Use turbopack.resolveAlias instead of webpack.resolve.alias.
  4. CSS ordering changes: Test visual regressions when migrating — CSS chunk order may differ.
  5. Environment boundary errors: Server-only modules imported in client components fail at build time — use server-only package.

Official Documentation

Frequently asked questions

What does the Turbopack AI skill do?

Turbopack expert guidance. Use when configuring the Next.js bundler, optimizing HMR, debugging build issues, or understanding the Turbopack vs Webpack differences.

Why use Turbopack on TypingMind?

Because you install it once and use it with any model. Turbopack is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Turbopack in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vercel/vercel-plugin/tree/main/skills/turbopack. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Turbopack?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Turbopack?

As many as you like. As long as a model supports skills, you can use Turbopack with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Turbopack AI skill free?

It is published on GitHub by vercel. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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