AI Token Calculator & LLM Cost Estimator
Paste your text to instantly count tokens, words, and characters — then estimate API costs across GPT, Claude, and Gemini models. The essential GPT token counter for developers, writers, and AI enthusiasts.
We'll estimate tokens using ~1.33 tokens per word.
Enter a known token count to estimate costs directly.
LLM Token Cost Comparison
What Is an AI Token Calculator?
An AI token calculator is a tool that estimates how many tokens a piece of text contains when processed by large language models (LLMs) like GPT-4, Claude, or Gemini. Since AI providers charge per token for API usage, knowing your token count is essential for budgeting API costs, optimizing prompts, and staying within model context limits.
Tokens are the fundamental units that AI models use to read and generate text. A token isn't always a full word — it can be a sub-word, a single character, or even a piece of punctuation. For example, the word "unbelievable" might be split into "un", "believ", and "able" — three separate tokens.
💡 Quick Rule of Thumb
- • 1 token ≈ 4 characters of English text
- • 1 token ≈ ¾ of a word
- • 100 tokens ≈ 75 words
- • 1,000 words ≈ 1,333 tokens
How Tokenization Works
Modern LLMs use a technique called Byte Pair Encoding (BPE) to convert text into tokens. Here's a simplified breakdown of the process:
Text Splitting
The input text is broken down into individual characters and common byte sequences.
Pattern Matching
The tokenizer merges frequent character pairs into sub-word units using a pre-trained vocabulary of ~100,000+ token patterns.
Token IDs
Each sub-word piece is mapped to a unique integer ID. The model processes these IDs, not the raw text itself.
⚠️ Note: Different models use different tokenizers. OpenAI's GPT-4o uses o200k_base, while Claude and Gemini use their own tokenization schemes. This calculator provides close approximations that work across all models.
Why Use an AI Token Counter?
Estimate API Costs
Calculate exactly how much your prompts and completions will cost before sending them to GPT, Claude, or Gemini APIs. Avoid surprise bills.
Prompt Optimization
Trim unnecessary tokens from your prompts to reduce costs and improve response speed. Every token counts when you're making thousands of API calls.
Context Window Planning
Ensure your input + expected output stays within the model's context limit (e.g., 128K tokens for GPT-4o, 200K for Claude 3.5).
Model Comparison
Compare token costs across providers and models side-by-side. Find the best balance between capability and price for your use case.
Budget Planning
Estimate monthly API spend for your AI-powered application or SaaS product before scaling to production traffic levels.
Content Writing
Writers and content creators can gauge how much text fits within token budgets when using AI assistants for drafting and editing.
Frequently Asked Questions
What is a token in AI?
A token is the basic unit of text that AI language models process. Tokens can be whole words, parts of words (sub-words), punctuation marks, or even spaces. For example, the word "calculator" might be split into "calc", "ul", and "ator" — three tokens.
Most English text averages about 1 token per 4 characters, or roughly 0.75 tokens per word. Non-English languages, code, and special characters typically produce more tokens per word.
How many tokens is 1,000 words?
On average, 1,000 words of standard English text equals approximately 1,333 tokens. However, the exact count varies based on:
- Word complexity (longer, technical words = more tokens)
- Punctuation density
- The specific tokenizer used by each model
- Whether the text contains code, URLs, or special characters
Use our token calculator above to get an accurate estimate for your specific text.
How is token count calculated?
Token count is calculated using a tokenizer algorithm — typically Byte Pair Encoding (BPE). The tokenizer breaks text into sub-word units based on a trained vocabulary. Common words like "the" are single tokens, while unusual words get split into smaller pieces.
This calculator uses an approximation of ~4 characters per token, which closely matches the actual tokenizer output for standard English text. For precise counts, OpenAI provides the tiktoken library.
Why do different AI models have different token costs?
Token pricing varies based on several factors:
- Model size: Larger models with more parameters cost more to run
- Capabilities: Models with better reasoning, coding, or creative abilities are priced higher
- Input vs. Output: Output tokens are generally more expensive than input tokens because generation is more computationally intensive
- Provider pricing strategy: Each AI company sets its own competitive pricing
What's the difference between input tokens and output tokens?
Input tokens are the tokens in your prompt — the text you send to the model. Output tokens are the tokens the model generates in its response.
Most providers charge different rates for each: output tokens typically cost 2-4x more than input tokens because text generation requires more computation than simply reading input.
Is this AI token calculator accurate?
This calculator provides a close approximation of token counts. For standard English text, the estimates are typically within 5-10% of actual tokenizer output. The pricing data is based on publicly listed API prices from OpenAI, Anthropic, and Google as of July 2026.
For exact token counts, you can use provider-specific tools like OpenAI's tiktoken Python library or Anthropic's token counting API endpoint.
AI Model Pricing Reference (Per 1M Tokens)
Prices shown are list prices as of July 2026. Always verify with the provider's official pricing page.
| Model | Input | Cached Input | Output |
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