AI Token Counter
Count tokens for GPT-4, Claude, Gemini and estimate API costs
| Model | Tokens | Context Used | Input Cost | Context Window |
|---|---|---|---|---|
| GPT-4o | 0 | 0.0% | $0.000000 | 128K |
| GPT-4 Turbo | 0 | 0.0% | $0.000000 | 128K |
| GPT-3.5 Turbo | 0 | 0.0% | $0.000000 | 16K |
| Claude 3.5 Sonnet | 0 | 0.0% | $0.000000 | 200K |
| Gemini 1.5 Pro | 0 | 0.0% | $0.000000 | 1000K |
* Claude and Gemini token counts are approximate. Pricing as of 2025 — verify at provider sites.
What is AI Token Counter?
The AI Token Counter lets you instantly count tokens in any text for GPT-3.5, GPT-4o, Claude, and Gemini models — all in your browser with no data sent to any server. Tokens are the units AI models use to process text, and knowing your token count helps you stay within context limits and estimate API costs before you send a single request.
Why Use DevBench AI Token Counter?
DevBench AI Token Counter runs entirely in your browser — your data never leaves your device. No sign-up, no limits, no watermarks, completely free forever.
How to Use AI Token Counter
- Paste your prompt, system message, or any text into the input box
- Token count updates instantly as you type
- View the comparison table to see token counts and estimated costs across all major models
- Click a row to select a model and see its estimated input cost highlighted
- Scroll down to see the individual token IDs breakdown for GPT tokenizer
Examples
- Paste a ChatGPT system prompt to check if it fits within GPT-4o context limits
- Count tokens in a long document before sending it to Claude 3.5 Sonnet
- Estimate the API cost of processing 1000 customer support messages
- Check how many tokens a code file uses before including it in a prompt
- Compare token counts between GPT and Claude for the same text
Use Cases
- Estimating OpenAI API costs before building a production feature
- Checking if a document fits within a model context window
- Optimizing prompts to reduce token usage and lower API bills
- Comparing cost efficiency across GPT-4o, Claude, and Gemini for a use case
- Debugging why an API call is hitting context length limits
- Planning token budgets for multi-turn conversation applications
- Validating that a fine-tuning dataset entry is within token limits
- Teaching developers how tokenization works in LLMs
Frequently Asked Questions
What is a token in AI models?
A token is the basic unit of text that AI language models process. Tokens are not exactly words — they are chunks of characters determined by the model tokenizer. In English, one token is roughly 4 characters or about 3/4 of a word. Common words like "the" are one token, while longer or rare words may be split into multiple tokens.
Are token counts the same across all AI models?
No. GPT models use the tiktoken tokenizer (cl100k_base for GPT-4/3.5). Claude and Gemini use their own tokenizers which produce slightly different counts for the same text. This tool uses the GPT tokenizer for exact counts and applies a small approximation multiplier for Claude and Gemini.
Is my text sent to any server?
No. All tokenization runs entirely in your browser using the gpt-tokenizer JavaScript package. Your text never leaves your device.
Why does the token count matter for API costs?
OpenAI, Anthropic, and Google charge per token — both for input (your prompt) and output (the model response). Knowing your token count lets you estimate costs accurately. For example, GPT-4o charges $5 per 1 million input tokens, so a 1,000-token prompt costs $0.005 per API call.
What is a context window?
The context window is the maximum number of tokens a model can process in a single request, including both your input and the model output. GPT-4o has a 128K token context window, Claude 3.5 Sonnet has 200K, and Gemini 1.5 Pro has 1 million tokens.