Professional Text Token Counter

Text Token Calculator & Tokenizer

Paste your text or code below to instantly calculate tokens across multiple tokenizers in real-time. Optimize your prompts and estimate your LLM costs.

Text Token Calculator
Type or paste your prompt to estimate token counts across different tokenizers in real-time

Token ↔ Word & Cost Converter

Estimate how many words, pages, and cost this token count represents across models

750,000
English Words
500,000
CJK Characters
1,500
A4 Pages
Official API Cost$30.00 / $180.00
Kie.ai Cost$18.00 / $108.00
Input Rate: $30.00 | Output Rate: $180.00Save 40% ($42.00)
Save 30%-50% with Kie.ai Gateway
Total Words0
Total Chars0
Estimated CJK Chars0
English Word Ratio0%
TokenizerToken Count
GPT-5.5 / GPT-4o / o3 o200k_baseDedicated tokenizer for latest OpenAI models
0
DeepSeek V3 / V4 / R1 deepseekDedicated highly efficient tokenizer for DeepSeek models
0
Claude 3.7 / 3.5 / Opus claudeApproximate estimation for Anthropic Claude series
0
Gemini 3.5 / 3.1 / 2.5 geminiSentencePiece tokenizer estimation for Google flagship series
0
GPT-4 / GPT-3.5 cl100k_baseCommon tokenizer for legacy OpenAI models
0
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Unbeatable Prices

LLM (GPT-5.5, Claude, DeepSeek) calling costs are 30% - 50% lower than official APIs. Multimodal (Veo 3.1, Flux Pro) costs are 60%+ lower!

Full Multimodal Support

Single key aggregates text, image, video generation (Runway, Veo, Kling), music generation (Suno), and speech recognition. No multiple accounts needed.

Standard Compatible

Fully compatible with OpenAI / Anthropic request formats. Simply update base_url and api_key in your code to migrate seamlessly.

Developer Integration Guides (Cursor, Claude Code, SDK)

Frequently Asked Questions

Q: What is a Token?

Tokens are the basic building blocks of text processed by Large Language Models. Models don't read word-by-word like humans; instead, they split text into smaller chunks called tokens (sub-words). Typically, 1 token equals about 4 characters or 0.75 English words. For non-English scripts like Chinese or Japanese, one character can cost 1 to 2 tokens depending on the tokenizer.

Q: Why do token counts differ between models?

This is because each model family uses a different Tokenizer and vocabulary list. For instance, OpenAI's o200k_base (used in GPT-4o/o1/o3) has a much larger vocabulary than cl100k_base (used in GPT-4), meaning it can compress non-English languages and code much more efficiently, yielding fewer tokens.

Tokenizer Tech Overview

In prompt engineering, optimizing token usage is the most direct way to cut API expenses. Here is a brief review of the mainstream tokenizers:

  • o200k_base: Used in GPT-5.5, GPT-4o, o1, o3 series. Provides 30%-50% better compression for non-English scripts, saving on contextual costs.
  • DeepSeek Tokenizer: Tailored for code and multilingual text. Possesses a vocabulary of 129,280 and highly compact segmentations.
  • Claude / Gemini: Based on Byte-Pair Encoding (BPE) and SentencePiece respectively, offering superior parsing of mathematical expressions and programming structures.