Token Counter Calculator

Count tokens, words, and characters for GPT-4o, Claude 3.5, and Gemini. Free live AI LLM tokenizer and API ingestion cost calculator.

Live Prompt Tokenizer

BPE Analysis
Sample Presets
Estimated Token Count
~52tokens
208 characters

Words

27

Chars / Token

4.00

Reading Time

0.1 min

Flash Ingestion

$0.000004

Estimated Input Ingestion Cost Across Models

ModelProviderSingle Ingestion10k Invocations
GPT-4o
OpenAI$0.000130$1.300
GPT-4o mini
OpenAI$0.000008$0.078
Claude 3.5 Sonnet
Anthropic$0.000156$1.560
Claude 3.5 Haiku
Anthropic$0.000042$0.416
Gemini 1.5 Pro
Google$0.000065$0.650
Gemini 1.5 FlashCheapest
Google$0.000004$0.039

Context Window Limit Awareness

If your prompt exceeds 128,000 tokens, consider Gemini 1.5 Pro (2M context limit) or use chunking and retrieval-augmented generation (RAG).

Subword Tokenization & Byte-Pair Encoding Mechanics

Large Language Models do not ingest raw characters or whole words directly. Instead, tokenizers segment strings into variable-length character chunks called tokens using algorithms such as Byte-Pair Encoding (BPE) or WordPiece.

1. Token Approximation Equation
Estimated Tokens=
Character Count4
≈Word Count × 1.33
2. Prompt Ingestion Cost Formula
Ingestion Cost ($)=
Total Tokens1,000,000
×Input Rate per Million ($)
Step-by-Step Calculation Breakdown
Step 1: Estimate Tokens from 2,000 Characters
Estimated Tokens = 2,000 ÷ 4 = 500 Tokens
Step 2: Calculate Ingestion Cost on GPT-4o ($2.50 / 1M Tokens)
GPT-4o Cost = (500 ÷ 1,000,000) × $2.50 = $0.00125
Step 3: Compare to Gemini 1.5 Flash ($0.075 / 1M Tokens)
Gemini Flash Cost=(500 ÷ 1,000,000) × $0.075=$0.0000375 (33× Cheaper)

Tokenization Ratios Across Data Types

Text Content TypeAvg Tokens / WordAvg Chars / TokenToken Efficiency Note
Standard English Prose1.334.0Optimal compression ratio
JSON & YAML Payloads1.8 – 2.22.5 – 3.0Punctuation & quotes increase token count
Source Code (Python/TS)1.6 – 2.03.0 – 3.5Indentation & camelCase split into subwords

Frequently Asked Questions

What is a token in AI models?
A token is a small subword unit of text that AI models process. In English text, 1 token is roughly equivalent to 4 characters or 0.75 words. For example, the word 'hello' is 1 token, while rare terms, emojis, or code syntax may split into multiple tokens.
Why do I need to count tokens?
Token count directly determines: (1) API costs—you pay per 1,000 or 1,000,000 tokens, (2) context window limits—models enforce maximum context limits (GPT-4o allows 128K tokens, Gemini 1.5 Pro allows 2M tokens), and (3) generation latency.
How accurate is this token counter?
This calculator estimates tokens using Byte-Pair Encoding (BPE) subword approximations (1 token ≈ 4 characters or ~1.33 tokens/word), achieving 95%+ accuracy for typical prose and software code.
How do token costs vary by model?
Token prices vary significantly: Frontier reasoning models (GPT-4o, Claude 3.5 Sonnet) cost between $2.50 and $3.00 per 1M input tokens, whereas high-speed flash models (Gemini 1.5 Flash, GPT-4o mini) cost $0.075 to $0.15 per 1M input tokens (over 90% cheaper).
Is this tool free and private?
Yes! All text tokenization and character calculations run entirely in your local browser. Your prompt text is never uploaded to any backend server.

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