Word Count Tool Free
Count words, characters, sentences, paragraphs, and lines instantly as you type. Calculates reading time and speaking time, identifies top keywords, and tracks unique word count. Live updates — no button needed. Runs entirely in your browser.
Type or paste your text — stats update live
Pro — custom WPM speed, flesch readability score, keyword density, batch file analysis
API access · Priority queue · Team workspace
How It Works
Type or Paste Text
Type directly in the text area or paste any content — a blog post draft, an essay, a cover letter, an email, a social media caption, or a product description. The tool handles text of any length and any language that uses whitespace to separate words. Click Sample to load a demonstration passage that shows all metrics populating with realistic values.
Stats Update Live
All nine metrics update instantly with every keystroke — no button to press. Words, characters (with and without spaces), sentences (counted by terminal punctuation), paragraphs (separated by blank lines), and lines all update in real time. Reading time uses 200 words per minute (average adult reading speed) and speaking time uses 130 wpm (average conversational speaking pace).
Review Top Keywords
The Top Keywords section shows the most frequent words, excluding common stop words (a, the, is, and, etc.) so you can see your actual content terms. This is useful for checking keyword density in SEO content, ensuring you are hitting target words in an essay, or spotting unintentional repetition in a piece of writing. Words are shown with their frequency count, sorted by most frequent first.
Word Count Features
Live text analysis with reading time, unique words, and keyword frequency
Real-Time Counting
All metrics update with every keystroke using a fast JavaScript listener on the textarea's input event. There is no submit button or debounce delay — the counts are always current. Word counting splits on whitespace sequences (multiple spaces and newlines count as one separator), so irregular spacing in pasted content is handled correctly without double-counting.
Reading & Speaking Time
Reading time is calculated at 200 words per minute, the average silent reading speed for an adult. Speaking time uses 130 words per minute, typical for conversational speech and presentations. Times are shown in minutes and seconds for short texts and hours and minutes for long ones. Useful for podcast scripts, presentation slides, video scripts, speeches, and articles with time limits.
9 Metrics in One View
Words, total characters, characters excluding spaces, sentences (detected by . ! ? followed by whitespace or end of text), paragraphs (separated by blank lines), lines, reading time, speaking time, and unique word count — all displayed simultaneously. No need to run separate tools for each metric. Useful for meeting platform character limits, Twitter/X character caps, essay word limits, and SEO meta description lengths.
Top Keyword Frequency
The top keywords section shows the 10 most frequent words after removing common stop words (articles, prepositions, conjunctions, auxiliary verbs). This reveals the actual content terms you are emphasizing. Each keyword badge shows the word and its count. Useful for checking SEO keyword density, identifying unintentional repetition in academic writing, and verifying that key terms appear with the right frequency.
Unique Word Count
Counts the number of distinct words in the text (case-insensitive). This is the lexical diversity metric — a high ratio of unique words to total words indicates varied vocabulary, while a low ratio may indicate repetitive writing or deliberate keyword emphasis. Academic style guides and content quality tools often use lexical diversity as a writing quality signal.
100% Private
All text analysis runs locally in your browser. Nothing is transmitted to any server, logged, or stored. Safe for counting words in confidential documents, proprietary reports, draft articles before publication, legal briefs, medical notes, and any sensitive written content that should not be processed by external services or cloud APIs.
Free vs Pro
| Feature | Free | Pro |
|---|---|---|
| All 9 live metrics | ||
| Top keyword frequency | ||
| Custom reading speed (WPM) | — | |
| Flesch-Kincaid readability score | — | |
| Batch file analysis | — | |
| REST API access | — |
Frequently Asked Questions
Words are counted by splitting the text on one or more consecutive whitespace characters (spaces, tabs, and newlines) and counting the resulting non-empty segments. This matches the behavior of the Unix wc -w command. Hyphenated words like "well-known" count as one word. Numbers count as words. Punctuation attached to a word (like a trailing period or comma) is included with that word token but does not create a separate word.
Reading time divides the word count by 200 words per minute, which is the typical silent reading speed for an adult reading general-interest content. Technical content with unfamiliar terms is read more slowly (100–150 wpm) and easy fiction can be read faster (250–350 wpm). The 200 wpm baseline is used by most publishing and content tools. For slide presentations or video scripts, use the speaking time figure (130 wpm) instead.
Sentences are counted by detecting terminal punctuation — a period, exclamation mark, or question mark followed by whitespace or end of text. This is an approximation: abbreviations with periods (Dr., U.S.A., etc.) and decimal numbers may be counted as sentence boundaries. For most prose this gives a close estimate, but exact sentence counting requires a natural language parser that understands grammatical structure.
Characters is the total length of the text including all spaces, tabs, newlines, and punctuation. Characters without spaces is the count after removing all whitespace characters — spaces, tabs, and newlines. Some platforms impose limits using one measure or the other: Twitter's character limit counts spaces, while some academic submission systems count characters excluding spaces. Check which metric your target platform uses.
The tool tokenizes words (converts to lowercase, strips punctuation), filters out a built-in list of ~50 common English stop words (a, the, is, and, of, in, to, etc.), then counts occurrences of each remaining word. The top 10 by frequency are displayed as badge tags with counts. This gives a keyword cloud that reflects your actual content terms rather than grammatical function words, making it useful for SEO density checks and content review.
Yes — all analysis runs entirely in your browser. Nothing is transmitted to a server. You can verify by opening developer tools, switching to the Network tab, then typing in the text area and confirming no requests appear. This makes it safe to analyze confidential documents, legal briefs, medical notes, proprietary business content, and draft articles that must not be transmitted to external services before publication.