AI Token Counter for GPT, Claude & Popular LLMs
The AI Token Counter is a powerful utility designed to help developers, researchers, and AI enthusiasts accurately count tokens for popular language models including GPT, Claude, Gemini, and other LLMs. Understanding token usage is critical for estimating API costs, optimizing prompt engineering, and managing rate limits. Our tool provides instant, precise token calculations to help you maximize efficiency and minimize expenses.
GPT-4o
OpenAI
0 tokens
GPT-4o mini
OpenAI
0 tokens
Claude 3.5 Sonnet
Anthropic
0 tokens
Claude 3 Haiku
Anthropic
0 tokens
Gemini 1.5 Pro
0 tokens
Gemini 1.5 Flash
0 tokens
Llama 3 70B
Meta
0 tokens
Mistral 7B
Mistral
0 tokens
Estimates are ±10%. No content is logged.
How to Use AI Token Counter
AI Token Counter is designed to make token counting effortless. Follow these simple steps to get started:
- Paste Your Text: Copy and paste your prompt, message, or API request into the input field
- Select Your Model: Choose from GPT-4, GPT-3.5, Claude, Gemini, or other popular LLMs from the dropdown menu
- Instant Calculation: The tool automatically calculates and displays the exact token count in real-time
- View Token Breakdown: See detailed statistics including input tokens, output tokens, and estimated costs
- Copy Results: Export your token count data for documentation or API planning purposes
When to Use AI Token Counter
Token counting is essential for anyone working with language models. Here are the most common scenarios:
- API Cost Management: Calculate exact costs before sending requests to OpenAI, Anthropic, or Google APIs
- Prompt Optimization: Identify ways to reduce token usage and improve efficiency without sacrificing quality
- Context Window Planning: Ensure your prompts fit within model limitations (e.g., GPT-4's 8K or 32K token window)
- Batch Processing: Estimate total tokens needed for processing multiple documents or conversations
- Budget Forecasting: Plan monthly API spending based on expected token consumption
- Model Comparison: Compare token efficiency across different LLMs before choosing one for your project
Hosting, VPS, SSL, domains — infrastructure for every project
Technical Information
Understanding how tokens work is crucial for effective API usage and cost optimization.
What Are Tokens?
- Token Definition: A token is a small unit of text that language models process. One token typically equals 4 characters or about 0.75 words in English
- Tokenization Process: Different models use different tokenization algorithms, which is why token counts vary between GPT, Claude, and Gemini
- Special Tokens: Formatting markers, system prompts, and function calls consume additional tokens beyond visible text
Model-Specific Tokenization
- GPT Models: Use cl100k_base encoding (GPT-4, GPT-3.5-turbo) with consistent token pricing
- Claude: Employs its own tokenizer resulting in different token counts than OpenAI models
- Gemini: Uses SentencePiece tokenization, typically producing more tokens per text unit
- Custom Models: Fine-tuned models may have unique tokenization requirements