---
title: Token Counter
emoji: 👀
colorFrom: pink
colorTo: purple
sdk: gradio
sdk_version: 6.2.0
app_file: app.py
pinned: false
license: mit
---

# Token Counter

A Gradio-based web application for counting tokens in text and web content using OpenAI's tiktoken library.

## Features

### Text Input Mode
- Paste or type text directly into the interface
- Real-time token counting as you type
- Support for multiple OpenAI model encodings (GPT-4.1, GPT-5, O1, O3, O4-mini, embeddings, and more)
- Displays token count and character count

### URL Input Mode
- Fetch and analyze content from any URL
- Counts tokens for both HTML and Markdown representations
- Shows token counts and character counts for both formats
- One-click example URL for testing
- **15-minute response caching** to prevent flooding target URLs with repeated requests

## Supported Models

The tool supports token counting for various OpenAI model families:
- **Reasoning models**: o1, o3, o4-mini
- **Chat models**: gpt-5, gpt-4.1, gpt-4o, gpt-4, gpt-3.5-turbo
- **Embedding models**: text-embedding-ada-002, text-embedding-3-small, text-embedding-3-large
- **Legacy models**: davinci-002, babbage-002

## How It Works

Token counting uses the [tiktoken](https://github.com/openai/tiktoken) library to estimate the number of tokens that would be consumed by different OpenAI models. This is useful for:

- Estimating API costs
- Staying within model token limits
- Optimizing prompts and content
- Comparing token efficiency between HTML and Markdown formats

## Caching

URL responses are cached for 15 minutes to reduce load on target servers. The status message indicates when cached content is being used and how old the cache is.