How to Count Tokens Accurately

Accurate token counting is essential for predicting AI API costs and staying within budget limits. Different models use different tokenization methods, so understanding these differences is crucial.

Token Counting Methods

Each AI provider uses their own tokenization approach:

• OpenAI: Uses tiktoken library with model-specific encodings
• Anthropic: Claude models use their own tokenization system
• Google: Gemini models have unique token counting rules

Best Practices

• Use official tokenization libraries when available
• Test with sample text before large deployments
• Account for both input and output tokens in cost calculations
• Consider context window limits for long conversations