AI Token Counter

Universal AI Token Counter

Our AI token counter supports all major AI providers and models, giving you accurate token counts and cost estimates for any AI application.

Supported Providers

• OpenAI: GPT-5 series, GPT-4o, o3 models
• Anthropic: Claude Opus, Sonnet, and Haiku models
• Google: Gemini 3 series, Gemini 2.5 Pro, Flash models
• xAI: Grok 4 series, reasoning and non-reasoning variants
• Meta: Llama 4 Maverick, Scout, and Llama 3 series
• Cohere: Command A, Command R, and Command R7B
• Mistral: Large 2, Codestral 2, Devstral 2
• Perplexity: Sonar Pro, Reasoning Pro, Deep Research
• Together AI: Hosted open source models

How Token Counting Works

Different AI providers use different tokenization methods:

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

Why Accurate Token Counting Matters

• Predict API costs before making requests
• Optimize prompts to reduce token usage
• Stay within context window limits
• Budget for AI applications effectively
• Compare costs across different models

Token Optimization Tips

• Remove unnecessary words and redundant instructions
• Use abbreviations and concise language
• Structure prompts efficiently
• Consider context window limits for long conversations
• Test different phrasings to find the most token-efficient approach