Features

• Real-time Visualization - See your text being tokenized as you type
• Multiple Model Support - Compare tokenization across all OpenAI GPT models
• Cost Optimization - Understand token counts to optimize your API usage
• Privacy First - All processing happens in your browser, no data sent to servers
• Lightning Fast - Instant tokenization with OpenAI's official tiktoken library
• Comprehensive Models - Support for 60+ models including GPT-4o, GPT-3.5, and code models

Why Tokenization Matters

When using OpenAI's API, you're charged per token, not per word. Understanding tokenization helps you:

• Reduce API costs by writing efficient prompts
• Avoid hitting token limits in your requests
• Optimize model performance by understanding how text is processed
• Compare different models for your specific use case

Example: "Hello, world!" might be:

• 3 tokens in GPT-4o
• 4 tokens in GPT-3.5-turbo
• This directly affects your API costs!

Getting Started

Quick Start

Visit happytokenizer.com and start typing in the text area. That's it!

Using the Tool

1. Enter or paste your text in the main text area
2. Select a model from the dropdown to see how it tokenizes your text
3. View token breakdown including token IDs and character mappings
4. Compare models to find the most cost-effective option for your needs

Supported Models

Modern Models (o200k_base)

• GPT-4o series (gpt-4o, gpt-4o-mini, etc.)
• Latest OpenAI models with optimized encoding

Chat Models (cl100k_base)

• GPT-3.5 series (gpt-3.5-turbo, gpt-3.5-turbo-16k)
• GPT-4 series (gpt-4, gpt-4-32k)

Code Models (p50k_base)

• Code-davinci series
• Optimized for code generation

And Many More...

• Legacy models (r50k_base)
• Edit models (p50k_edit)
• Open-source models (o200k_harmony)

View the complete list at happytokenizer.com/models

For Developers

Local Development

Want to run HappyTokenizer locally or contribute? Here's how:

# Clone the repository
git clone https://github.com/yourusername/happytokenizer.git
cd happytokenizer

# Install dependencies
pnpm install

# Start development server
pnpm dev

# Build for production
pnpm build

Tech Stack

• Framework: Astro with React
• Styling: Tailwind CSS with custom design system
• Tokenization: OpenAI's official tiktoken library
• Type Safety: TypeScript throughout
• Build Tool: Vite

Architecture

src/
├── components/
│   ├── react/          # React components with client-side logic
│   └── Footer.astro    # Footer component
├── layouts/
│   └── MainLayout.astro  # SEO-optimized base layout
├── pages/
│   ├── index.astro     # Main tokenizer page
│   └── models.astro    # Complete model manifest
└── utils/
    └── modelEncodings.ts  # Model configurations

Privacy & Security

HappyTokenizer is designed with privacy as a core principle:

• No data sent to servers - All processing happens locally
• No tracking or analytics - Your data stays yours
• Open source - Transparent and auditable code
• No cookies - Zero tracking technologies

Contributing

We welcome contributions! Here's how you can help:

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Make your changes and test them
4. Commit your changes: git commit -m 'Add amazing feature'
5. Push to the branch: git push origin feature/amazing-feature
6. Open a Pull Request

Areas for Contribution

• UI/UX improvements - Better visualization ideas
• Mobile enhancements - Responsive design improvements
• Performance - Faster tokenization or loading
• Documentation - Better guides and examples
• Bug fixes - Report and fix issues

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• OpenAI for the tiktoken library
• The Astro team for the amazing framework
• All contributors who help improve this tool

Contact

• Website
• Issues
• Discussions

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