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Version: 3.1.0

Developed by Heliconia Solutions Pvt. Ltd.
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  3. /LLM Token Counter
AI Tools

LLM Token Counter

Free LLM token counter — estimate token usage for GPT, Claude, Gemini, and Llama prompts in real time.

Token counter

Approximation only. For exact counts use the official tokenizer (tiktoken, Anthropic SDK, etc.).

0
Characters
0
No spaces
0
Words
0
Lines
0
UTF-8 bytes
OpenAI GPT-4 / GPT-4o
≈ 4 chars / token
0
Anthropic Claude 3 / 4
≈ 4 chars / token
0
Google Gemini 1.5 / 2
≈ 3.8 chars / token
0
Meta Llama 3
≈ 3.5 chars / token
0
Mistral / Mixtral
≈ 3.6 chars / token
0

Why approximations differ

Each LLM family uses its own BPE vocabulary. Real token counts depend on punctuation, language, and special characters. Use these numbers for budgeting, not billing.

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Overview

About LLM Token Counter


The QuickToolz LLM Token Counter estimates how many tokens your text uses across the major model families — OpenAI GPT-4 / GPT-5, Anthropic Claude, Google Gemini, Meta Llama, and Mistral. Paste a prompt and see token count, character count, and approximate cost live.

Why tokens matter

LLMs price, rate-limit, and context-window everything in tokens, not characters or words. As a rough rule, 1 token ≈ 4 characters of English (or ¾ of a word) — but the real number depends on the tokenizer (BPE vs. SentencePiece vs. Tiktoken). Counting tokens before sending prevents context overflow and cost surprises.

Tokenization differs by model

  • OpenAI: tiktoken (cl100k_base for GPT-4, o200k_base for GPT-4o/5)

  • Claude: a proprietary BPE close to cl100k

  • Llama / Mistral: SentencePiece (BPE)

  • Gemini: SentencePiece with a custom vocab

Features

What makes LLM Token Counter great

Everything you need, nothing you don’t. Built for speed and simplicity.


  • Multi-model

    Tokenizers for OpenAI, Anthropic, Google, Meta, and Mistral.

  • Cost estimate

    Approximate USD cost based on current API pricing.

  • Live

    Updates as you type — no submit button.

How to use

Get started with the LLM Token Counter in just seconds.

Everything you need, nothing you don’t. Built for speed and simplicity.


  1. 01

    Paste your prompt

    Drop in any text — system prompt, user message, or document.

  2. 02

FAQ

Frequently asked questions about LLM Token Counter.

Got questions? We’ve got answers. Common questions about LLM Token Counter.


English averages ~4 characters per token. Code and non-Latin scripts are denser (often 2–3 chars/token).

No — the same text produces different token counts on different models. Always re-count when switching providers.

For chat APIs (OpenAI, Anthropic), each message adds a small fixed overhead. We include it in the displayed total.

Pick a model

Switch between GPT, Claude, Gemini, and Llama tokenizers.

  • 03

    See token count + cost

    Live token count and approximate cost at current pricing.