About LLM Tokenizer

What is LLM Tokenizer?

LLM Tokenizer is a free, comprehensive online tool designed to help developers, researchers, and AI enthusiasts understand and optimize their interactions with Large Language Models (LLMs). Our platform provides accurate token counting, cost estimation, and model comparison across all major AI providers including OpenAI, Google, Meta, Anthropic, and more.

Why Token Counting Matters

LLM providers charge based on tokens, not words or characters. Understanding token counts helps you optimize costs, stay within context limits, and design more efficient prompts.

Understanding Tokenization

What Are Tokens?

Tokens are the fundamental units that Large Language Models use to process text. A token can be as short as one character or as long as one word. For example, the word "tokenization" might be split into multiple tokens like ["token", "ization"], while common words like "the" or "is" are typically single tokens.

Token Examples:

  • "Hello, world!" → 4 tokens: ["Hello", ",", " world", "!"]
  • "ChatGPT" → 2 tokens: ["Chat", "GPT"]
  • "AI" → 1 token: ["AI"]
  • "🚀" → 1-3 tokens (varies by tokenizer)

Different Tokenization Methods

Full Multi-Provider Tokenizer Support

We now support accurate tokenization for all major LLM providers: OpenAI (tiktoken), Meta/Llama (SentencePiece), Google/Gemini (SentencePiece), Anthropic/Claude, and Groq. Each model automatically uses its native tokenizer for maximum accuracy.

BPE (Byte Pair Encoding)

Used by OpenAI's GPT models and many others. Breaks text into subword units based on frequency, balancing vocabulary size with representation efficiency.

OpenAI, GPT-4, GPT-3.5

SentencePiece

Used by Google's models and Meta's Llama. Language-independent tokenization that treats text as a raw input stream, supporting multiple languages efficiently.

Gemini, Llama, T5

WordPiece

Similar to BPE but uses a different scoring method. Commonly used in BERT and other transformer models for natural language understanding tasks.

BERT, DistilBERT

Tiktoken

OpenAI's fast BPE tokenizer library. Provides exact token counts for GPT models and is the standard for OpenAI API usage calculation.

GPT-4, GPT-3.5-turbo

Key Features

Accurate Token Counting

Uses official tokenizers (tiktoken for OpenAI models) to provide exact token counts, ensuring your estimates match actual API usage.

Cost Calculation

Calculate costs for both input and output tokens across different models. Get min/max estimates and bulk pricing for 100, 1K, 10K, and 100K requests.

Model Comparison

Compare costs across all available models instantly. See which model offers the best value for your specific use case and token requirements.

Token Visualization

See exactly how your text is tokenized with visual highlighting. Toggle between token text and token IDs to understand the tokenization process.

Context Window Tracking

Monitor how much of a model's context window you're using. Avoid exceeding limits and optimize your prompt design for maximum efficiency.

Privacy First

Your text is processed in real-time and never stored on our servers. All tokenization happens securely and your data remains private.

Supported Models

We support token counting and cost calculation for all major LLM providers:

Provider Models Tokenizer
OpenAI GPT-4, GPT-4 Turbo, GPT-3.5, GPT-3.5 Turbo, Davinci, Curie tiktoken (BPE)
Google Gemini Pro, Gemini Ultra, Gemini Flash, PaLM 2 SentencePiece
Meta Llama 2, Llama 3, Code Llama SentencePiece
Anthropic Claude 3 Opus, Claude 3 Sonnet, Claude 3 Haiku, Claude 2 Custom tokenizer
Groq Mixtral, Llama models on Groq infrastructure Model-specific

Who Should Use This Tool?

Developers

Optimize API costs, debug token limits, and design efficient prompts for your applications.

Researchers

Analyze tokenization patterns, compare model behaviors, and estimate research costs.

Businesses

Calculate LLM integration costs, compare providers, and optimize AI spending.

Why Choose LLM Tokenizer?

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100% Free: No registration, no limits, no hidden fees. Use as much as you need.
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Always Up-to-Date: We regularly update our pricing database to reflect the latest model costs.
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Accurate: Uses official tokenizers for precise token counts that match API billing.
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Privacy-Focused: Your text is never stored. All processing happens in real-time.
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Fast & Responsive: Built with modern web technologies for instant results.
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Comprehensive: Supports all major LLM providers in one convenient tool.

Our Mission

Our mission is to make LLM development more accessible, transparent, and cost-effective. We believe that understanding tokenization and costs shouldn't require complex calculations or guesswork. By providing accurate, real-time token counting and cost estimation, we help developers and businesses make informed decisions about their AI implementations.

Ready to Get Started?

Try our tokenizer now and see exactly how your text is processed by different LLM models.

Try the Tokenizer Learn How It Works