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PromptTokenizer

Visualize and analyze how LLMs tokenize text. Count tokens, compare models, optimize your prompts.

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Overview

PromptTokenizer is a powerful tool that allows you to visualize and analyze how leading Large Language Models (LLMs) such as GPT-4, Claude, and Llama tokenize your text. Understanding tokenization is crucial for optimizing prompts, managing costs, and staying within model context limits. With PromptTokenizer, you can see exactly how your input is broken down into tokens, compare tokenization across different models, and refine your prompts for maximum efficiency.

  • Real-time token visualization with color-coded token boundaries
  • Token count and character count for any text input
  • Side-by-side comparison of tokenization across multiple LLMs
  • Advanced analytics including token frequency and distribution

Key Features

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Visualize token boundaries with color-coded highlights

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Count tokens and characters for any text input

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Compare tokenization across GPT-4, Claude, and Llama

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Optimize prompts by analyzing token efficiency

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Export tokenization reports for documentation

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API access for programmatic token analysis

Pros & Cons

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Pros

  • arrow_right + Intuitive visual representation of tokenization
  • arrow_right + Supports multiple leading LLMs for comparison
  • arrow_right + Helps reduce token usage and API costs
  • arrow_right + Fast performance with real-time feedback
  • arrow_right + Useful for both developers and content creators
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Cons

  • arrow_right - Free tier has a token limit per query
  • arrow_right - Limited to text-based analysis (no image tokens)
  • arrow_right - Requires understanding of tokenization concepts for full benefit

Pricing Details

Free Tier: Basic token counting and visualization for single models (up to 1000 tokens per query).
Pro Tier ($9/month): Unlimited token analysis, multi-model comparison, export reports, API access, priority support.

FAQ

What is tokenization?

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Which models are supported?

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Is my data secure?

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Can I use PromptTokenizer for large texts?

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How accurate is the token count?

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Overview Visualize and analyze how LLMs tokenize text. Count tokens, compare models, optimize your prompts. Manage local and cloud AI agents from your editor. Plan, delegate, review, and ship code without context switching. Spawn background coding agents in the cloud. Hand off tasks from Slack, Linear, or GitHub and get a PR back. Ship API integrations instantly. Forward deploys AI agents into your customers' repos, auto-writing and testing integrations in minutes.
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