AI Token Cost Calculator

How AI Token Cost Is Calculated

An AI token cost converter estimates how much you will pay to use a large language model (LLM) API such as GPT, Claude, or Gemini. These APIs charge by the token, not by the request, and prices are usually quoted per million tokens.

The basic formula is:

• Cost = (Tokens ÷ 1,000,000) × Price per million tokens

For example, if a model costs $3 per million input tokens and you send 250,000 tokens, the cost is (250,000 ÷ 1,000,000) × 3 = $0.75. Because most providers price in US dollars, you can convert the result to ₹ using the current exchange rate if you need a rupee figure.

Prices differ widely between models and providers and change over time, so always check the current rate card from your provider before relying on an estimate.

Tokens vs Words

A token is a chunk of text, often a word or part of a word. Models break text into tokens before processing it, so token count is not the same as word count.

A useful rule of thumb for English is:

• 1 token ≈ 0.75 words, or about 4 characters
• 1,000 tokens ≈ 750 words

So roughly 100 words is about 133 tokens. Punctuation, numbers, code, and non-English text can change this ratio, so treat it as an estimate. The table below shows approximate token counts for common text sizes.

Text size	Approx. words	Approx. tokens
Short reply	100	~133
One page	500	~667
Long article	1,500	~2,000
Short book chapter	7,500	~10,000

For an exact count, providers offer tokenizers, since each model family tokenizes text slightly differently.

Input vs Output Pricing

Most LLM providers charge different rates for input and output tokens. Input tokens are what you send (your prompt, instructions, and any context); output tokens are what the model generates back.

• Input (prompt) tokens - usually the cheaper rate.
• Output (completion) tokens - often priced higher, sometimes several times the input rate.

So the total cost of a call is the input cost plus the output cost:

• Total = (Input tokens ÷ 1M × Input price) + (Output tokens ÷ 1M × Output price)

The example below uses illustrative prices only - real prices vary by model and change often, so check your provider's current pricing.

Part	Tokens	Price / 1M	Cost
Input	500,000	$3.00	$1.50
Output	100,000	$15.00	$1.50
Total	600,000	-	$3.00

Some providers also offer discounts for cached or batched tokens, which can lower costs further.

Tips for Estimating and Reducing Costs

To get a realistic estimate and keep your AI bills under control:

• Estimate input and output separately, since output is usually the pricier part.
• Remember that long conversations resend earlier messages as context, which adds up input tokens on every turn.
• Use shorter, focused prompts and ask for concise answers to cut output tokens.
• Pick a smaller or cheaper model when high quality is not essential.
• Look for prompt caching, batch pricing, or volume discounts if your usage is large.
• Multiply your per-call estimate by expected daily volume to forecast monthly spend.

This converter gives a quick estimate, but actual billing depends on exact token counts and the live prices set by your provider. Always confirm against your provider's current pricing page before budgeting.