Model & Token Cost Calculator

Count prompt tokens, estimate context usage, and compare costs across GPT-5.6, Claude 5, Gemini 3, DeepSeek V4, and Grok 4.5.

Tool Guide

Model & Token Cost Calculator: What It Does

Estimates token counts and API costs for text prompts across frontier models (GPT-5.6 Sol, Claude 4.5 Sonnet, Gemini 2.5 Flash, DeepSeek V3). It visualizes context window consumption and prompt pricing updated from published list rates.

Example

Input
Sample 100-word prompt
Output
~130 tokens, estimated cost: $0.0003

Calculates BPE token estimates and multiplies by published API pricing tiers.

How to Use

  1. Paste prompt text or system instructions into the editor.
  2. Select one or more LLM models from the comparison matrix.
  3. Review estimated token volume, context window percentage, and input cost.

Limitations

  • Different model families use distinct tokenizers; figures are close estimates rather than exact provider counts.
  • API pricing tracks official list rates and excludes enterprise volume discounts.

Frequently Asked Questions

Why do token counts differ between English text and other languages?

Tokenizers are optimized primarily for common English syllables. Non-Latin scripts or code with heavy indentation consume more tokens per character.

What is the typical ratio of words to tokens in English text?

In standard English text, 1 token roughly corresponds to 0.75 words, meaning 1,000 words typically consume around 1,300 to 1,400 tokens.

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