Developer Tools
AI Token Counter
Estimate tokens and API cost for GPT-4o, Claude 4, Gemini and other LLMs.
103 characters · ~23 tokens (estimated)
$2.5/M in · $10/M out · 128K ctx
50200 tokens4,000
Estimated cost
Input tokens
$0.000058
23
Output tokens
$0.0020
200
Cost per call
$0.002058
Cost × 1,000 calls/month
$2.06
Context window usage
Used
23 / 128,000 tokens
0.02%
Why count tokens?
LLM APIs charge per token (input + output have separate rates). For long prompts or high-volume apps, even a few wasted tokens per call add up to hundreds of dollars per month. Counting before sending = saving money + avoiding context overflow errors.
Frequently Asked Questions
What is a token?▾
In LLMs, a token is a unit of text — usually a word fragment of 3-4 characters. "Hello" is 1 token. "Hello, world!" is ~4 tokens. Common English words are usually 1 token; rare words and other languages may use 2-4 tokens each.
Are these counts exact?▾
No — this is a fast approximation (≈4 chars per token for English). For exact counts, use OpenAI's tiktoken library or Anthropic's tokenizer. Our estimate is typically within 5-10% of actual.
Why does token count matter?▾
API providers charge per token (separate input and output rates). Tokens also affect context window limits — exceed the model's max and your call fails. Counting before sending saves money and surprises.
Why are some languages more expensive?▾
English uses fewer tokens per character because tokenizers were trained mostly on English. Mandarin, Japanese, and Arabic typically use 2-4× more tokens for the same idea — making API calls in those languages proportionally more expensive.
How do I reduce token usage?▾
Trim system prompts to essentials, use shorter examples, ask the model to be concise, use cheaper models for simple tasks (GPT-4o-mini, Claude Haiku), and cache reusable context with provider-specific prompt caching APIs.