Master LLM Utils

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Frequently Asked Questions

What is a token in LLM context?

A token is a chunk of text that LLMs process. In English, one token is roughly 4 characters or 0.75 words. Different models use different tokenizers.

How accurate is the token estimate?

Our estimate uses a ~4 characters/token approximation which is accurate within ±10% for English text. Code and non-English text may vary more.

Why do different models have different token counts?

Each model uses a different tokenizer vocabulary. GPT-4o and Claude have different ways of splitting text into tokens. Our estimate uses a universal approximation.

How is cost calculated?

Cost = (tokens / 1,000,000) × price per million tokens. We use the model's published input price. Output tokens are typically 2-4x more expensive.

What's the cheapest LLM for my use case?

Check our Price Comparator tool. For simple tasks, Gemini Flash or GPT-4.1 nano are most cost-effective. For complex reasoning, GPT-4.1 or Claude Sonnet offer best value.

Do images count as tokens?

Yes, in multimodal models. Images are converted to tokens — typically 170-1,500 tokens per image depending on resolution and the model's vision tokenizer.

What's the difference between input and output tokens?

Input tokens are your prompt. Output tokens are the model's response. Most providers charge differently for each — output tokens cost 2-5x more.

Is my text stored or sent anywhere?

No. All processing happens locally in your browser. Your text never leaves your device. We don't use any APIs for token counting.

What is context window?

The context window is the maximum number of tokens a model can process in a single request (input + output combined). GPT-4o has 128K, Gemini has 1M+.

Is this tool free?

Yes. Token counting runs entirely in your browser — no API calls, no sign-up, and no data collection.