AI Token Counter
Estimate token count and API cost for GPT-5, Claude, Gemini, DeepSeek, Mistral, Grok and Llama models with live counting.
AI Token Counter
Estimate token count and cost for GPT, Claude, Gemini, DeepSeek and other AI models.
OpenAI · ~4 chars/token · 1M context · verified 2026-08-11
What is an AI Token Counter?
An AI token counter is a tool that estimates how many tokens a piece of text will consume when sent to large language model APIs like OpenAI's GPT-4, Anthropic's Claude, or Google's Gemini. Tokens are the fundamental billing unit for AI APIs: each API call is priced per token, and understanding token usage is essential for cost optimization and staying within context window limits.
CodeHelper's AI Token Counter provides instant token estimates for all major models, calculates API costs for both input and output, and shows context window usage as a visual progress bar.
Key Features
- Multi-Model Support: Estimates for the current GPT-5, Claude Opus, Sonnet and Haiku, Gemini 3, DeepSeek V4, Mistral, Grok, Llama and Kimi models, grouped by provider, each with its verification date.
- Cost Estimation: See the estimated API cost for both input (prompt) and output (completion) pricing.
- Context Window: Visual progress bar showing what percentage of the model's context window your text uses.
- Live Counting: Token count updates as you type for real-time feedback.
- Text Statistics: Word count, character count, and line count alongside token estimates.
How to use the AI Token Counter
- Select the AI model you are using.
- Paste your prompt, system message, or any text.
- View the estimated token count, cost, and context window usage instantly.
Why tokens matter: context windows and cost
- Context window limits: Every model has a maximum token count for a single request (1M tokens for most frontier models, 128K to 200K for smaller ones). Exceeding the limit causes errors.
- Input vs output pricing: Input tokens (your prompt) are usually cheaper than output tokens (the model's response). Use the counter to estimate both.
- Tokens vs words: A typical English word is about 1.3 tokens. Numbers, punctuation, and non-English text can use more tokens per word.
- Prompt optimization: Reducing your system prompt by 100 tokens saves cost on every single API call at scale.
Whether you are optimizing prompts for cost, checking context window limits, or estimating API budgets, this free token counter helps you manage AI API usage effectively.
Frequently Asked Questions
How accurate is the token count?
It is an estimate based on the average characters per token of each family (about 4 for GPT, Gemini and most models, 3.5 for Claude), with CJK characters counted one token each. For English prose it lands within a few percent of the real tokenizer; code, numbers and rare languages can differ by 10 to 20 percent. Use it for budgeting and context checks, and the provider tokenizer for exact billing.
How many tokens is a word?
Roughly 1.3 tokens per English word, or 4 characters per token. Short common words are one token, long or unusual words split into several, and punctuation and spaces often count too. Chinese, Japanese and Korean text is close to one token per character.
Why is the output cost higher than the input cost?
Providers charge more for generated tokens than for prompt tokens, typically 3 to 6 times more. The two boxes show the same text priced as a prompt and as a completion, so you can see both ends of a call. For a monthly budget with cache hits, use the LLM Cost Calculator.
What is the context window?
The maximum number of tokens a single request can hold, prompt and answer together. The bar shows what share of the selected model window your text uses; if it is near 100 percent the request will be rejected or the answer truncated.
Where do the prices come from?
From a pricing file maintained on CodeHelper with a verification date per model, shown under the model selector. Prices are per million tokens in US dollars and are checked against the provider pages roughly once a month.
Related
Free forever, no ads, no tracking. Support the project