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ToolItFast Zero Friction
REALTIME · TEXT & LLM ANALYSIS

Word & LLM Token Counter

Count words, characters, sentences, paragraphs, lines and estimated LLM tokens in real time. Analyze text density, reading length and prompt size without sending your text anywhere in local mode.

# Exact Text Counts Words, characters, lines and paragraphs
AI Token Intelligence Understand prompt size and text efficiency
⚡ Live Analysis Updates instantly while you type
TEXT INPUT

Paste or write your text.

Analyze text locally or use AI for deeper clarity, structure and token-efficiency guidance.

Live
Your text stays in the browser when using the local counter. 0 characters

REALTIME ANALYSIS

Text metrics at a glance.

Exact text measurements and practical model-dependent token estimates update as your content changes.

Waiting for text
WORDS 0 Exact count
EST. LLM TOKENS 0 Model-dependent estimate
CHARACTERS 0 Including spaces
NO SPACES 0 Characters excluding whitespace
SENTENCES 0 Structural estimate
PARAGRAPHS 0 Non-empty blocks
LINES 0 Including single lines
UTF-8 SIZE 0 B Approximate encoded size
READING TIME 0 min Based on selected speed
TOKEN / WORD 0.00 Estimated density ratio
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Why is the token count estimated?

Different AI models use different tokenizers, so the same text can produce slightly different token counts. This tool provides a useful planning estimate rather than claiming one universal exact count.

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TEXT BLUEPRINT

Content structure at a glance.

Deterministic measurements
CONTENT TYPE Waiting
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TOKEN PROFILE Auto Detect
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TEXT SCALE Empty
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READING LENGTH 0 min
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TEXT & TOKEN CHECKS

Practical deterministic signals.

No AI required
TEXT VOLUME Waiting Add text to evaluate overall content size.
TOKEN DENSITY Waiting Evaluates the estimated token-to-word relationship.
STRUCTURE Waiting Reviews paragraph and sentence distribution.
PROMPT SCALE Waiting Provides a practical size classification for LLM planning.
01

Words and tokens are different

A token may represent a whole word, part of a word, punctuation or another text fragment. Tokenization depends on the model and tokenizer.

02

Use estimates for planning

The local token estimate is useful for comparing prompt size and content density, but exact billing or context-window calculations should use the tokenizer for the specific model.

03

Concision can reduce token usage

Clearer, less repetitive prompts often require fewer tokens while preserving the information an AI system actually needs.

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WORDS, TOKENS & LLM INPUTS

Word & LLM Token Counter FAQ

What does the Word & LLM Token Counter measure?

It measures words, characters, characters without spaces, sentences, paragraphs, lines, UTF-8 size and reading time. It also provides an estimated LLM token count for planning prompts and other AI inputs.

Is the LLM token count exact?

No universal token count exists because different models and tokenizers can split the same text differently. The local counter provides a planning estimate rather than claiming an exact count for every AI model.

Is my text sent to a server?

The normal counter runs locally in your browser. Your text is only submitted to the ToolItFast AI service if you deliberately choose Analyze with AI.

Why can token counts differ between AI models?

Each model can use a different tokenizer or vocabulary. Spaces, punctuation, code, numbers, languages and uncommon words may also be split differently, which changes the final token count.

Can AI help reduce token usage?

Yes. The optional AI analysis can identify repetition, unnecessary wording and structural inefficiencies and can suggest a more concise version while preserving the main meaning.