🔤 LLM Token Count Calculator
Estimate LLM tokens from text length, words, characters, language, code content, and expected output. Check context-window usage and API cost inputs.
Calculate LLM Token Count
What this LLM token count calculator calculates
Estimate tokens when a provider tokenizer is not available. The tool uses adjustable characters-per-token and words-per-token assumptions and reports a range rather than pretending every model tokenizes identically.
Use an official model tokenizer for billing-critical measurements. This page is best for planning prompt size, context usage, and rough API budgets.
LLM Token Count Calculator formula
Assumptions and limitations
The result is an engineering estimate based on the values entered. AI models, tokenizers, runtimes, accelerators, cloud services, and provider billing rules differ. Validate important decisions with measured data from the exact model, hardware, framework, and pricing plan you intend to use.
Worked example
A 4,000-character English prompt at 4 characters per token is approximately 1,000 tokens. Code, non-Latin scripts, and unusual formatting may require more.
How to use the result
Use an official model tokenizer for billing-critical measurements. This page is best for planning prompt size, context usage, and rough API budgets.
- Start with representative production assumptions rather than best-case demos.
- Run a low, expected, and high scenario to understand the range.
- Record model version, pricing date, hardware, precision, and workload details.
- Replace assumptions with observed p50 and p95 measurements after testing.
Common mistakes to avoid
- Assuming one tokenizer works identically across all model families.
- Ignoring system messages, tool schemas, retrieved documents, and prior conversation turns.
- Counting words as tokens without accounting for punctuation, code, or non-English text.
Frequently asked questions
Is one word equal to one token?
No. English averages are often below or above one token per word depending on vocabulary, punctuation, and tokenizer.
Why does code use more tokens?
Code contains punctuation, indentation, identifiers, and uncommon strings that may split into many token pieces.
Is pasted text uploaded?
No. The calculation runs locally in the browser.
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Methodology and privacy
This educational tool uses the formula and assumptions displayed on the page. Calculations run locally in your browser, and the page does not transmit the values you enter. Results are estimates rather than provider quotes, benchmark guarantees, financial advice, or capacity guarantees. Last methodology review: August 2, 2026.
Formula Explorer connections
Interpretation: This formula describes how token load, memory and throughput constrain an online model deployment. Assumption: Tokenizer, model architecture, batching, queueing, runtime, hardware and traffic distribution must match the intended production system.