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AI Token Calculator

Estimate AI tokens, words, characters, context usage, and per-request cost for popular AI models.

Token counts are estimates. Actual tokenization varies by model.

Override the response estimate with a fixed whole-number output token count for planning.

Estimated tokens

78

42 input + 36 output

Estimated cost

$0.000074

Input $0.000017 + output $0.000058

Context usage

0.0%

Of 1,047,576 token window

Words

48

26 prompt + 22 response

Characters

312

Prompt + response, includes whitespace.

Input tokens

42

From prompt text.

Output tokens

36

From response sample.

Selected model

GPT-4.1 Mini

OpenAI

Input cost

$0.000017

$0.40 / 1M input tokens

Output cost

$0.000058

$1.60 / 1M output tokens

Context window

1,047,576 tokens

Maximum prompt + response size.

Context Window Usage

78 of 1,047,576 tokens used for this request.

0.0% used

Live token estimates

Tokens, words, characters, and per-request cost update as you type.

Model presets

OpenAI, Anthropic, Gemini, and custom pricing presets are included.

Local processing

Prompts never leave your browser. No API key required.

Dynamic Cost Insights

Your prompt is about 42 input tokens (168 characters).
Your response sample is about 36 output tokens (144 characters).
GPT-4.1 Mini charges $0.40/M input and $1.60/M output.
Estimated total cost for this single request is $0.000074.
You are using about 0.0% of the 1,047,576 token context window.
Token counts are estimates. Actual tokenization varies by model, language, code, emoji, and formatting.

What Is an AI Token?

A token is the smallest unit of text a large language model processes.

One token usually corresponds to roughly 4 English characters or about 3/4 of a word.

Common words are a single token. Rare words, code, emoji, and non-Latin scripts often split into multiple tokens.

Providers bill per million tokens for both input prompt tokens and output response tokens.

How This Calculator Works

Token count is estimated from character count using a 4-characters-per-token heuristic.

Input tokens come from the prompt field. Output tokens come from the response field, or from the expected output override if set.

Cost is computed per million tokens using the price stored for the selected model.

Context usage compares total tokens against the model's published context window.

Token Estimation Formula

estimatedTokens = Math.ceil(characterCount / 4)
cost = (tokens / 1,000,000) × pricePerMillion
totalCost = inputCost + outputCost
contextUsage % = (totalTokens / contextWindow) × 100

Why Token Counts Vary

Each model uses its own tokenizer, such as BPE, SentencePiece, or tiktoken-style vocabularies.
English prose tokenizes more efficiently than code, JSON, or non-Latin scripts.
Emoji and special symbols often count as multiple tokens.
System prompts, tool definitions, retrieved context, and JSON schemas add tokens you may not have authored.

Input vs Output Tokens

Input tokens are everything the model reads: system prompt, user message, retrieved context, and tool definitions.

Output tokens are everything the model writes back. Output rates are often higher than input rates.

Long retrieval-augmented prompts can make input the dominant cost. Long generations make output dominate.

Caching, batching, and prompt compression can reduce costs, but this calculator uses standard non-cached pricing only.

Understanding Context Windows

The context window is a hard limit on prompt + response tokens for a single request.
Going over the window causes an error, truncation, or a failed request depending on the provider.
Long-context models use more memory and may have different limits or pricing tiers.
Track usage to avoid surprise overages on long agent traces.
Streaming responses still count against the total window.
Reserve headroom for the response; never plan to fill the entire window.

Limitations

Token estimates use a 4-character heuristic, not the model's real tokenizer.
Vendor pricing changes frequently. Verify against live docs before procurement.
Image, audio, video, and tool-use pricing are not included in this text estimate.
Cache hits, batch discounts, free tiers, regional pricing, and provisioned throughput are not modelled.
Fine-tuned models may use different pricing than the base model.
No prompt content is uploaded. All calculations run locally.

Frequently Asked Questions

A token is a chunk of text that a large language model processes, typically a short word, a piece of a word, punctuation, or whitespace. Models are billed and limited by token count, not by character or word count.
Token counts and costs are estimates. Real tokenization varies by model, language, code, and formatting. Vendor pricing changes frequently. Verify against live provider documentation before relying on these numbers for billing, procurement, or production cost planning.

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