🧮 Token Counter: Precise Counting Without Missing a Character! 🔍
A must-check before AI requests! This tool precisely analyzes not only the character count but also Korean, English, and spaces to help you optimize input without wasting tokens. 🚀
🔹 What is a Token? 🔹
**Token** refers to the smallest unit of text used in Natural Language Processing (NLP).
AI models, especially GPT-based models, process text in token units.
🧩 What Counts as a Token?
A token can be composed of the following units:
✅ **Word** → 'Hello' → 1 token
✅ **Space** → Spaces are also counted as tokens
✅ **Punctuation** → Symbols like commas (,) and periods (.) are treated as independent tokens
✅ **Character** → In some languages, each individual character can be treated as a token
📊 Difference Between Korean and English Tokens
Token counts vary significantly by language.
**English** → 'Hello World!' = 4 tokens (Hello / Space / World / !)
**Korean** → '안녕하세요 세상아!' = 9 tokens (안 / 녕 / 하 / 세 / 요 / Space / 세 / 상 / 아 / !)
🔎 **Why the Difference?**
English is divided by words, while Korean often recognizes each character as a separate token.
🚨 Understanding AI Token Limits
AI language models have token limits.
For example: GPT-4 has a maximum limit of **8,192 tokens**.
🔹 **1,000 tokens ≈ 750 English words**
🔹 **1,000 tokens ≈ 350-400 Korean characters**
Thus, long Korean sentences can consume more tokens than English sentences.
💡 Tips for Saving Tokens
1️⃣ Summarize long sentences concisely.
2️⃣ Remove repetitive words.
3️⃣ Use abbreviations and shorter expressions to save tokens.
4️⃣ Removing unnecessary spaces or special characters can also be helpful.
🚀 Maximize Your AI Efficiency!
By understanding and managing tokens effectively, you can maximize your AI usage efficiency. 😊