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LLM Token Counter

Count tokens for GPT-5.6, Claude, Gemini, and other current LLMs. Estimate API costs based on your text input.

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Model

Output Length Multiplier

Monthly Call Volume

How LLM Token Counting and Pricing Works

Large language models (LLMs) like GPT-5, Claude, and Gemini process text as "tokens" rather than words or characters. A token is roughly 4 characters or about 0.75 words in English. Understanding tokenization is critical for managing API costs, because you are billed per token for both the text you send (input/prompt tokens) and the text the model generates (output/completion tokens).

Why Token Counts Matter for Your Budget

LLM API pricing is expressed as cost per million tokens. Different models have vastly different price points: a single API call with Claude Fable 5 might cost dozens of times more than the same call with GPT-5.6 Luna or DeepSeek V4 Flash. Choosing the right model for each task is one of the biggest levers for controlling costs. Many production applications use a tiered approach — a cheap, fast model for simple tasks and a premium model only when quality demands it.

Tips to Reduce LLM Token Costs

Trim your prompts: Remove unnecessary instructions, examples, and whitespace. Every character in your system prompt is billed on every single request.
Use caching: If your system prompt is static, providers like Anthropic offer prompt caching that can reduce input costs by up to 90%.
Limit output length: Set a max_tokens parameter to prevent the model from generating more text than you need.
Route by complexity: Use a small, cheap model for classification, extraction, and simple Q&A. Reserve expensive models for creative writing, complex reasoning, or coding tasks.
Batch requests: Many providers offer batch APIs at 50% discounts for non-time-sensitive workloads.

Input vs. Output Token Pricing

Most providers charge significantly more for output tokens than input tokens — often 3-5x more. This is because generating text requires more compute than reading it. When estimating costs, pay close attention to how much output you expect. A summarization task (long input, short output) will be cheaper than a generation task (short input, long output) even at the same total token count.

About This Estimator

This tool uses the standard approximation of 1 token per 4 characters. Actual token counts vary by model and tokenizer — some models use byte-pair encoding (BPE), others use SentencePiece. For precise counts, use the official tokenizer libraries (like OpenAI's tiktoken). However, the characters-divided-by-4 rule is accurate enough for cost estimation and budget planning. Prices shown are reference API rates and should be checked against the provider's live pricing page before purchase decisions. DeepSeek estimates use its conservative peak cache-miss rates; official off-peak rates are half the displayed token prices.

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How to Use the LLM Token Counter

1
Enter your values
Open the LLM Token Counter and fill in the required input fields with your numbers or selections.
2
Review the calculation
The tool automatically computes the result as you type. Double-check your inputs to ensure accuracy.
3
Interpret your results
Review the calculated output along with any breakdowns, charts, or explanations provided to understand what the numbers mean for your situation.

Sources & Verification

OpenAI API Models and Pricing Anthropic Claude API Pricing Google Gemini API Pricing xAI API Pricing Mistral API Pricing DeepSeek API Pricing

Published by ConvertCrunch Editorial Team | Our Methodology

Frequently Asked Questions

What is the LLM Token Counter?

The LLM Token Counter is a free browser-based tool on ConvertCrunch. Count tokens for GPT-5.6, Claude, Gemini, and other current LLMs. Estimate API costs based on your text input. It requires no downloads, installations, or account signups. Simply enter your values and get instant, accurate results. The tool is designed for quick calculations and informed decision-making, whether you are a professional, student, or everyday user looking for reliable answers.

How do I use the LLM Token Counter?

Using the LLM Token Counter is straightforward. Enter your values into the input fields provided on the page, then calculate or adjust parameters to explore scenarios. Most processing happens locally in your browser. If a feature uses a third-party service, the tool identifies that connection and the privacy policy explains it. Most users get the answers they need in under a minute.

Is the LLM Token Counter free to use?

Yes, the LLM Token Counter is completely free to use with no account signup, email requirement, or premium tier. Most calculations run locally in your browser. Features that depend on live data or a third-party service require a network connection and are identified in the tool. You can use it as many times as you need for personal, educational, or professional purposes.

How accurate is the LLM Token Counter?

The LLM Token Counter uses current publicly available pricing data from major AI providers and industry benchmarks. AI pricing changes frequently as providers update their models and pricing tiers, so costs shown reflect rates at the time of calculation. Actual costs may vary based on usage volume, negotiated enterprise agreements, and provider-specific discounts. Check provider pricing pages for the most up-to-date rates.

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How LLM Token Counting and Pricing Works

Why Token Counts Matter for Your Budget

Tips to Reduce LLM Token Costs

Trim your prompts: Remove unnecessary instructions, examples, and whitespace. Every character in your system prompt is billed on every single request.
Use caching: If your system prompt is static, providers like Anthropic offer prompt caching that can reduce input costs by up to 90%.
Limit output length: Set a max_tokens parameter to prevent the model from generating more text than you need.
Route by complexity: Use a small, cheap model for classification, extraction, and simple Q&A. Reserve expensive models for creative writing, complex reasoning, or coding tasks.
Batch requests: Many providers offer batch APIs at 50% discounts for non-time-sensitive workloads.