Character Counter
Paste any text and see characters, words, lines, and reading time at once — plus whether it fits Twitter, SMS, and meta-description limits.
How long will this take to read? Estimate reading time from word count at a pace you choose — the "5 min read" label, calculated.
The "5 min read" badge on an article is just word count divided by reading pace, and readers use it to decide whether to start. This loads a blog-length post and estimates its reading time at a selectable pace — slow, average, or fast — because a technical piece reads slower than a casual one. Reading time is the metric that turns a word count into a reader's decision; speaking time, also shown, does the same for anything read aloud.
Paste the article
A post or page you want a reading-time estimate for.
Pick the pace
Slow, average, or fast — technical content reads slower.
Read the estimate
The "X min read" label, plus speaking time for narration.
Switch the pace selector before you trust the number. The report defaults to 'Average (~200 wpm)', which gave '2 min 38 sec' for this 528-word sample, but slow and fast settings divide the same word count by a different rate and the figure updates in the browser as you change it. Lower the pace when a 'min read' badge should feel less optimistic.
They answer two different questions from one word count. Reading time uses ~200 wpm ('2 min 38 sec' here) for silent readers deciding whether to start an article; speaking time uses the slower ~130 wpm ('4 min 4 sec') for anything read aloud, like narration or a script. The speaking line is always longer because talking pace trails reading pace. Both are estimates, not per-person guarantees.
The report prints the raw figure — '2 min 38 sec' — so you can see the exact word-count-over-pace math before you decide how to round it for a badge. A '3 min read' label rounds that up; a '2 min' one rounds down. Seeing the seconds lets you round on purpose rather than guessing. The Character Counter measures the text in your browser; the final label is your call.
Paste any text and see characters, words, lines, and reading time at once — plus whether it fits Twitter, SMS, and meta-description limits.
Count words in any text, with sentence and paragraph structure and reading time — for essays, articles, and anything with a word target.
A character is what you type; a token is what a model reads. This shows when to count which, from the character side.
Know how many tokens a job will consume before you send it — input plus an assumed response, costed per call and at scale.
Token budget planning for real workloads: how much of the window a transcript actually consumes, what is left for the answer, and how much headroom remains.
A set of before-and-after examples showing exactly what prompt cleanup removes — and what it deliberately leaves alone.
Count characters, words, lines, and reading time — with live platform-limit checks for Twitter, SMS, meta descriptions, and more.