Estimate LLM tokens using a lightweight heuristic: divide the UTF-8 byte length of your text by four and round up. Agent workflows use this before sending large prompts to language models so they can stay within context-window limits without calling a proprietary tokenizer API.
When to use it
- Budget context before chaining multiple tool results into one prompt
- Compare two draft responses for relative size
- Sanity-check whether a document should be chunked first
How it works
The tool counts UTF-8 bytes and Unicode characters, then applies ceil(utf8Bytes / 4). This matches common English-centric rules of thumb; actual tokenizer counts for GPT, Claude, or Gemini may differ by model and language.
Limitations
This is an estimate, not an exact tokenizer result. Code-heavy or non-Latin text can deviate significantly. Empty or whitespace-only input is rejected.
Example
The phrase hello world reports eleven UTF-8 bytes and an estimated three tokens with the default divisor.