Question 1

How are tokens counted?

Accepted Answer

For OpenAI models (GPT-5.5, GPT-4.1, o4-mini), this token counter uses gpt-tokenizer, a pure JavaScript BPE implementation that runs locally in your browser. It supports both cl100k_base (GPT-4.1 Legacy) and o200k_base (GPT-5.5 and variants) encodings. For Claude, Gemini, Llama, DeepSeek, Mistral, and other models, the tool applies a model-specific character-to-token ratio that closely reflects the real tokenizer output — accurate to within a few percent for typical English text.

Question 2

Why do different models have different token counts?

Accepted Answer

Each AI provider trains its own tokenizer, which learns a different vocabulary of subword units from its training data. A word like "tokenization" might be split into two tokens by one model and three by another. This means the same paragraph can produce significantly different token counts depending on the model you select. OpenAI's o200k_base tokenizer, used in GPT-5.5, tends to be more efficient than older encodings, resulting in fewer tokens for the same text.

Question 3

What tokenizer does this tool use?

Accepted Answer

For OpenAI models, the tool uses the gpt-tokenizer npm package — a pure JavaScript BPE tokenizer that runs entirely in your browser. No text is sent to any server. For all other providers, the tool uses character-based ratio estimates derived from each model's published tokenizer behavior.

Question 4

How many tokens is 1000 words?

Accepted Answer

As a general rule, 1000 words is approximately 1300 to 1500 tokens for most English text on OpenAI models. The exact count depends on the model and the content — technical text with many short words or code tends to tokenize differently than flowing prose. Use the token counter above with your actual text for the most accurate result.

Question 5

Does token count affect API cost?

Accepted Answer

Yes. Almost all AI APIs charge per token, so knowing your token count before calling the API lets you estimate costs accurately. Most providers charge separately for input tokens (your prompt) and output tokens (the model's response). Use the Tokens-per-Dollar Calculator to see exactly how far a given budget goes across different models.

Token Counter by Model

Frequently Asked Questions

Related articles

Your AI Is Not Hallucinating Because It Knows Too Little. You Might Be Giving It Too Much.

Stop Writing Prompts Like You Are Texting. Start Writing Them Like You Mean It

Fine-Tuning vs Prompt Engineering: When Each One Actually Makes Sense