What is an LLM Token Counter?

An LLM Token Counter is a tool that helps you count how many tokens your text or prompt uses in models like GPT-3.5, GPT-4, Claude, or Llama. It helps estimate cost and token limits for LLMs.

How can I count tokens for GPT-4 or Claude?

You can use this free LLM Token Counter by Asad Faizee. Just paste your text or prompt, select the model (GPT-3.5, GPT-4, Claude, Llama), and the tool instantly shows the token count, words, and characters.

Is this LLM Token Counter free to use?

Yes, the LLM Token Counter is 100% free and open to everyone. It helps prompt engineers, developers, and AI enthusiasts optimize their token usage for large language models.

LLM Token Counter

Accurately estimate token counts for GPT-3.5, GPT-4, Claude, and Llama 2 in real-time

Estimated Tokens

Characters

Words

Paste Your Prompt or Text

Real-time counting as you type

Total Length: 0 characters

Language Model Settings

Select Target LLM

Tokens per Character Ratio

Rule of thumb: 1 token ≈ 4.0 characters

Estimation Disclaimer

This tool calculates an estimate based on character count ratios. Exact tokenization (like BPE used by OpenAI) depends on the specific API. Always refer to your provider's dashboard for billing.

Try with Sample Texts:

Frequently Asked Questions (FAQ)

What is an LLM Token?

In Large Language Models (LLMs) like ChatGPT, Claude, or Llama, a "token" is the basic unit of data processed by the AI. A token is not always a full word; it can be a single character, a chunk of a word, or an entire word depending on the language and context. A helpful rule of thumb for standard English text is that 1 token is approximately 4 characters or 0.75 words.

Why do I need a Token Counter?

AI APIs charge based on token usage (input and output). Additionally, every model has a maximum context window (e.g., GPT-4 has up to 128k tokens). Using an LLM Token Calculator helps prompt engineers and developers estimate API costs, ensure their prompts fit within the model's limits, and optimize their text before sending expensive API calls.

Are tokens calculated differently across models?

Yes. OpenAI's models (GPT-3.5, GPT-4) use a specific tokenizer called tiktoken (using Byte-Pair Encoding). Anthropic's Claude and Meta's Llama use their own distinct tokenization dictionaries. While the exact count may vary slightly between them, the ratio-based estimation provided in this tool offers a very close approximation for general text.