Word to Token Counter
Calculate tokens for all major AI models and estimate API costs
Text Input
Enter or paste your text to analyze
Words
0
Characters
0
No Spaces
0
Sentences
0
Paragraphs
0
Lines
0
Reading Time
0 min
Speaking Time
0 min
Token Visualization
See how your text is split into tokens
Enter text to see token visualization
TOKENS
0
0 tokens / 100 chars
TOKENS USED
0.00%
0 / 128,000 tokens
ESTIMATED COST
$0.0000
Input channel - live estimate
Cost breakdown (per request)
Input
$0.0000
Output
$0.0000
Cached input
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Cached output
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OpenAI Model Comparison
| Model | Context Window | Input Cost | Output Cost |
|---|---|---|---|
| GPT-4 | 8,192 tokens | $30/1M | $60/1M |
| GPT-4 Turbo | 128,000 tokens | $10/1M | $30/1M |
| GPT-4o | 128,000 tokens | $5/1M | $15/1M |
| GPT-4o Mini | 128,000 tokens | $0.15/1M | $0.6/1M |
| GPT-3.5 Turbo | 16,385 tokens | $0.5/1M | $1.5/1M |
| O1 Preview | 128,000 tokens | $15/1M | $60/1M |
| O1 Mini | 128,000 tokens | $3/1M | $12/1M |
Understanding Tokens
What are Tokens?
Tokens are the basic units that AI language models use to process text. They can be as short as one character or as long as one word. For example, "ChatGPT" might be one token, while "chat" and "GPT" might be two separate tokens. Understanding tokenization is crucial for optimizing API usage and managing costs.
Why Token Counting Matters
Cost Management:
Most AI APIs charge based on token usage
Context Limits:
Models have maximum token limits per request
Performance:
Fewer tokens mean faster response times
Optimization:
Helps optimize prompts and reduce waste
Tokenization Methods
BPE (Byte Pair Encoding):
Used by GPT models. Merges frequently occurring character pairs.
WordPiece:
Used by BERT and similar models. Breaks words into subword units.
SentencePiece:
Language-agnostic tokenization used by many multilingual models.
Pro Tips
- Use this tool to estimate costs before making API calls
- Different models tokenize text differently - always check for your specific model
- Shorter, clearer prompts often work better and cost less
- Consider using cheaper models for simpler tasks
- Monitor your token usage to optimize your AI application budget