Token Counter
Count tokens and estimate API costs for GPT-4o, Claude, Gemini and more. Free, private, runs in your browser.
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Characters
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Words
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Tokens
Model
Cost Estimate
Input (0 tokens)
$2.5/1M tokens
Output (~0 tokens)
$10/1M tokens
Total estimated cost
input + output
Token counts are estimates. Actual counts may vary slightly from the model's native tokenizer. Prices sourced from official documentation and may change — always verify before production use.
About Token Counter
Language model APIs charge by the token — typically a unit roughly equivalent to four characters or three quarters of a word in English. Understanding token counts before submitting text to an API helps you estimate costs, ensure your input fits within a model's context window, and optimize prompts to reduce unnecessary length without losing effectiveness.
Our Token Counter calculates the approximate token count for any text using tokenization rules consistent with the major model providers, and provides cost estimates based on published per-token pricing for GPT-4o, GPT-4 Turbo, Claude Haiku, Claude Sonnet, Claude Opus, Gemini Pro, and Gemini Ultra. The estimates update as you type, giving you a real-time view of how prompt engineering decisions affect cost.
Different models tokenize text differently — GPT models use the tiktoken BPE tokenizer, Claude and Gemini use similar but distinct approaches. The counts shown are estimates that closely approximate the actual token counts these models report, accurate enough for budgeting and planning purposes. All processing runs locally — your text, prompts, or proprietary data never leaves your browser.
How to Use Token Counter
- 1Paste or type your text, prompt, or document into the input field.
- 2The token count and word count update in real time as you type.
- 3Select your target model from the model dropdown to see the cost estimate for that specific API.
- 4Compare token counts across different models using the multi-model comparison table.
- 5Use the cost estimate to inform prompt optimization before running expensive production queries.
Use Cases
- →Estimate the API cost of a prompt template before running it at production scale
- →Check whether a large document fits within a model's context window before submitting it
- →Compare token counts for the same text across GPT-4o, Claude, and Gemini for budget planning
- →Optimize a system prompt to reduce token count without losing essential instructions
- →Audit input length in batch processing workflows to identify unexpectedly large inputs
- →Understand how formatting (markdown, code blocks, line breaks) affects token consumption
Tips
- ✓Token counts differ between models — GPT-4o and Claude tokenize the same text slightly differently
- ✓Code, URLs, and technical content often use more tokens per character than plain prose
- ✓Shorter, clearly structured prompts with less formatting use fewer tokens and cost less to run
- ✓System prompts count toward total token usage in most API implementations — include them in estimates
- ✓Markdown formatting (headers, bullet points, bold) adds tokens — weigh it against the clarity benefit
- ✓At scale, even small prompt optimizations compound: saving 50 tokens per call × 10,000 calls = 500k tokens
Frequently Asked Questions
A token is the basic unit that language models use to process text. On average, 1 token ≈ 4 characters or ¾ of a word in English.
The counts are close approximations, typically within 2–5% of the real count for English text.
Cost = (input tokens / 1,000,000) × input price + (output tokens / 1,000,000) × output price. Input and output are billed separately by all major providers.
The context window is the maximum number of tokens a model can process in a single request. Once the context window is full, the model cannot process additional tokens.
Prices shown are sourced from official provider documentation. AI model pricing changes frequently — always verify current pricing on the official provider pages.
No. All token counting and cost calculation happens entirely in your browser. Your text is never sent to any server.