How WordBench counts

What counts as a word

A word is any unbroken run of non-whitespace characters. The implementation is a single regular expression, /[^\s]+/g, applied to the trimmed text.

That definition has consequences worth knowing. can’t is one word. state-of-the-art is one word. A standalone emoji with spaces either side is one word. Two words joined by a dash without spaces are one word here and often two in a word processor. A page number on its own line is one word.

Average word length is measured differently, on purpose: it strips punctuation from each word first, so that the average reflects letters and digits rather than quotation marks.

How sentences, paragraphs and lines are detected

• Sentences. A run of characters ending in a full stop, question mark or exclamation mark, plus any trailing run without one. Abbreviations such as e.g. and Dr. will therefore be over-counted, which is the standard limitation of every rule-based sentence splitter.
• Paragraphs. Blocks separated by one or more blank lines. A single line break inside a paragraph does not start a new one.
• Lines. Every newline, blank ones included, in text that is not entirely whitespace.

How characters are counted, four ways

This is the single largest source of disagreement between character counters, so WordBench shows all four numbers rather than picking one and hoping.

The plain Characters figure on the counter is the UTF-16 length, because that is what most platforms enforce in the field itself. Where a platform counts something else, the limit pagescount in that platform’s own unit instead, and say which one it is. Platform limits were last verified on 23 July 2026.

X is the clearest example of why this matters. It counts weighted units: most Latin text costs 1, every emoji and CJK character costs 2, and any link costs a flat 23 regardless of length. A counter reporting plain characters against the 280 limit is wrong on all three counts.

Reading time, speaking time and word length

Every benchmark figure the site states, with what it rests on. Where a figure is a convention rather than a measurement, the table says so instead of dressing it up as research.

Reading time is word count divided by 238, rendered as minutes and seconds. Speaking time is word count divided by 130. Both scale linearly, so both are estimates and neither accounts for how hard the text is to read.

Words to pages

The words-per-page figures behind the words per page guide assume US Letter with one-inch margins, and vary with typeface, point size and line spacing.

The 250-word double-spaced page is a publishing convention, not a physical constant. Real pages vary with the words you use: a page of dialogue holds far fewer words than a page of solid prose. Every figure in this table is rounded to the nearest 25 and should be read as an estimate. Manuscript format, Wikipedia

Readability

Two published formulas, applied exactly as published. The differentiator is not the score, it is that you can check it.

• Flesch Reading Ease = 206.835 minus 1.015 times (words per sentence) minus 84.6 times (syllables per word). Higher is easier; 60 to 70 is plain English.
• Flesch-Kincaid Grade Level = 0.39 times (words per sentence) plus 11.8 times (syllables per word) minus 15.59. The result is a US school grade.

Syllables are counted with the standard vowel-group heuristic: count runs of vowels, drop a silent trailing e, keep a trailing le after a consonant as its own syllable, and never return less than one. It is a heuristic and not a pronunciation dictionary, so it gets words such as business and queue wrong, exactly like every other implementation that does not ship a dictionary. Under 100 words the scores are marked unreliable, because one long sentence swings them by ten points.

Dale-Chall is deliberately not implemented. It needs the 3,000-word list of familiar words, and shipping a truncated or guessed version of that list would produce a number that looks authoritative and is not.

Keyword density and the full stop-word list

Density is the count of a term divided by the total number of words of two characters or more, as a percentage. Words are lowercased and stripped to letters, digits and apostrophes first. Single characters are excluded.

These 73 words are filtered out. This is the complete list, not a sample:

a about an and are as at be been being but by can could did do does for from had has have he her here his how i if in into is it its me my no not of on or our out she should so than that the their them then there these they this those to up us was we were what when where which who will with would you your

The word-frequency tool can be switched to include these words, because for some purposes, such as checking whether a draft leans on the and that, they are exactly what you want to see.

What never happens to your text

Every function described on this page runs as JavaScript in your own browser. There is no backend, no database, no API endpoint and no logging. Your text is not uploaded, not stored and not sent to a third party, and there is nothing to opt out of because there is nothing collecting anything. Details on the privacy page.

Frequently asked questions

Why does my word count differ from Microsoft Word? Because a word is a definition, not a fact. WordBench counts any unbroken run of non-whitespace characters, so an em-dash between two words without spaces counts as one word here and often as two in Word. Numbers, standalone punctuation and emoji separated by spaces each count as one word here. Neither is wrong; they answer slightly different questions.

Sources

• Brysbaert (2019), Journal of Memory and Language
• WordBench convention, documented on /methodology
• Words per minute, Wikipedia
• Garbe, The average word length in English language is 4.7
• Manuscript format, Wikipedia
• Flesch-Kincaid readability tests, Wikipedia
• UAX 29, Unicode Text Segmentation, the definition of a grapheme cluster