Word Counter

Count words, characters, sentences and paragraphs - updates as you type.

Stays in your browser · Always free
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Words
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Characters
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Chars (no spaces)
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Reading time

The counter updates in real time as you type or paste - words, characters with and without spaces, sentences, paragraphs, and an estimated reading time. Useful for hitting hard length limits (tweets, essay quotas, ad copy character caps), tracking draft progress, or estimating how long something will take to read aloud or on screen. Everything stays in your browser.

How counts and reading time are computed

Words. Counted by splitting on whitespace and removing empty results. Hyphenated terms ("self-aware," "well-being") count as one word. Numbers, abbreviations, and standalone punctuation also count if surrounded by whitespace. This matches how Word and Google Docs count.

Characters. Two figures are shown: with spaces (the literal length of the text) and without spaces (non-whitespace characters only). Different platforms measure differently - Twitter counts everything; many academic style guides exclude spaces; SMS counts everything including newline bytes.

Sentences. Counted by splitting on terminal punctuation (., !, ?) and discarding empty splits. This works well for normal prose; it can misfire on text with abbreviations like "Dr." or "U.S.A." and on lists.

Paragraphs. Counted by blank lines (one or more line breaks separating blocks).

Reading time is estimated at 200 words per minute, a common figure for adult silent reading on screen. Speaking aloud is closer to 130–150 wpm; technical or dense material reads slower. So a 1,000-word piece is about 5 minutes silent, 7 minutes spoken.

Common length references
Social media

Twitter/X: 280 characters · Instagram caption: 2,200 characters but only 125 visible · LinkedIn post: 3,000 characters · Facebook post: technically 63,206 but engagement drops sharply past 80–100 words.

Web copy and SEO

Meta description: 150–160 characters · Title tag: 50–60 characters · Blog post (long-tail SEO): 1,500–2,500 words · Quick answer post: 300–600 words.

Writing and academic

Standard double-spaced page: ~250 words · Single-spaced page: ~500 words · College essay (5 pages): 1,250 words · NaNoWriMo target novel: 50,000 words · A typical novel: 70,000–100,000.

Speaking

5-minute talk: ~700 words · 10-minute talk: ~1,400 words · 20-minute keynote: ~2,800 words. Slow down for technical content; aim for the lower end of the range.

Frequently asked questions
How does the word counter work?
Type or paste text into the input box. The counter updates in real time, showing words, characters with and without spaces, sentences, paragraphs, and estimated reading time.
How are words counted?
By splitting the text on whitespace and discarding empty results. Hyphenated terms count as one word. This matches the convention used by Word and Google Docs.
Does the word counter show characters with and without spaces?
Yes. Both are shown so you can match whichever your platform uses. Twitter counts everything (including spaces); many academic standards exclude spaces; the difference matters at the limits.
How is reading time calculated?
At 200 words per minute, a common figure for adult silent reading on screen. A 1,000-word article takes about 5 minutes to read silently, ~7 minutes spoken aloud.
Is my text saved or sent anywhere?
No. The counter runs entirely in your browser. Nothing is transmitted to any server. Safe for drafts, confidential text, or anything you don't want logged.
What is a good word count for a blog post?
For SEO and depth, 1,500–2,500 words tends to perform well for evergreen topics. Quick "how do I do X" posts can be 300–600 words. Pillar guides and definitive-resource posts often run 2,500–4,000+ words. Quality and intent match more than length.
Why does my count differ from Microsoft Word's?
Mostly hyphenation and treatment of standalone punctuation. The differences are usually within 1–2%. For hard length limits, use whichever counter your reviewer or platform uses.
Can it count words in non-English text?
Yes for languages that use whitespace word boundaries (most European languages). Languages without whitespace word boundaries (Chinese, Japanese, Thai) need a tokenizer designed for that language; the whitespace approach undercounts dramatically.