Free Tool
AI Token Calculator
Count tokens for any major LLM before sending your prompt. Avoid context limit errors and estimate costs accurately.
Prompt Metrics
You have 200,000 tokens remaining for system messages and model completions.
Estimates are computed using Byte Pair Encoding (BPE) algorithms resembling Anthropic & OpenAI rules. Raw counts may fluctuate.
What is token counting?
LLMs don't process text word-by-word — they work with tokens, which are chunks of characters roughly corresponding to 0.75 words on average. Every model has a maximum context window measured in tokens, and every API call is priced per token.
Understanding token counts lets you:
- Avoid truncation: Know when you're approaching the context limit before your request fails
- Estimate costs: Calculate exact API costs before submitting requests
- Optimize prompts: Trim unnecessary content to reduce costs without losing quality
- Plan context: Budget tokens across system prompts, conversation history, and your actual query
How tokenization works
Different models use different tokenizers. GPT models use the cl100k_base tokenizer (tiktoken),
Claude uses a similar BPE tokenizer, and open-source models like Llama use SentencePiece. This means the same
text may have a different token count across models.
As a rough rule of thumb, 1 token ≈ 4 characters or 0.75 words in English. Code and non-English text typically uses more tokens per character.
Related tools
- Context Window Calculator — Visualize how much of your context window you're using
- LLM Cost Calculator — Calculate exact API costs across providers