Offline Token Counter: No API Calls, No Data Leaks
The article introduces a browser-based token counter tool that works offline, without sending any data to a server. It supports various large language models and provides detailed token analysis.
Why it matters
This tool addresses privacy concerns around token counting and provides a convenient offline solution for developers working with large language models.
Key Points
- 1Offline token counting tool built with pure JavaScript
- 2Supports major LLMs like GPT-4, Claude, LLaMA, and Gemini
- 3Provides token count, character/word count, context window usage, and cost estimates
- 4Avoids data leaks by running entirely in the browser
Details
The article presents a token counting tool that runs entirely in the browser, without making any network calls. This addresses privacy concerns around using online tokenizers that send user data to a backend server. The tool supports a range of large language models, including GPT-4, Claude, LLaMA, and Gemini, and provides detailed analysis such as total token count, character and word count, context window usage, and cost estimates. While the tokenizer implementation is a simplified BPE approximation, it handles common English subword splits and CJK character-by-character splitting. The author notes that for exact counts, users should use official tokenizers or APIs, but this tool is intended for fast estimates during development. The goal was to create a lightweight, offline-capable tool that doesn't require a build step or Node.js, just a standalone HTML file.
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