Find the most frequent letter in text
In Mississippi River the winner is i, with 5 of its 16 letters, and the tool also tells you that 7 different letters appear. Uppercase and lowercase count together, and ties are listed rather than settled at random. Free in your browser.
- Free
- Runs in your browser
- No sign-up
- Your data stays on your device
Run — free
Worked example
- Text
- Mississippi River
- Letters
- i
- Quantity
- 5
- Total letters
- 16
- Unique letters
- 7
The most frequent letter finder counts every letter in the text without treating uppercase and lowercase forms as different entries. It ignores spaces, numbers, punctuation, emoji, and other non-letter characters, then reports the highest count and every letter that shares it. That makes ties visible instead of selecting an arbitrary winner. The tool supports letters from Unicode writing systems, works deterministically, and returns useful totals alongside the winning letters for quick checking or automated analysis.
How to find the most frequent letter
Paste or send the text you want to examine in the text field. The tool walks through the input one Unicode character at a time and keeps only characters classified as letters. Spaces, line breaks, numbers, punctuation marks, currency signs, mathematical symbols, and emoji do not enter the calculation.
Each accepted letter is converted to lowercase before its frequency is updated, so an uppercase A and a lowercase a contribute to the same result. When counting is complete, the response provides the winning letters, the frequency shared by those winners, the total number of letters examined, and the number of distinct case-folded letters. The letters array is important because ordinary prose can have more than one winner.
If three letters each occur five times and no letter occurs more often, all three appear rather than one being chosen arbitrarily. Winners retain their first-appearance order, making repeated calls with identical input stable and easy to compare in tests, scripts, or stored reports.
Understand case, Unicode, and ties
Case-insensitive counting sounds simple, but reliable text analysis must distinguish letters from bytes and visual glyphs. This capability iterates over Unicode code points rather than splitting raw UTF-16 code units, so supplementary-plane letters are not accidentally cut in half. It recognizes the Unicode letter category, which includes Latin, Greek, Cyrillic, Arabic, Han, and many other scripts.
After recognizing a letter, it applies locale-independent lowercase conversion. This produces consistent results regardless of the server region or the reader’s browser settings. It does not remove accents or transliterate scripts: e and é remain distinct letters, just as Latin a and Greek alpha remain distinct.
That choice preserves what the source actually contains. A tie is reported whenever multiple normalized letters have the same maximum count.
What you can do with it
Build a letter-frequency lesson
Show students which letter leads in a passage and demonstrate honest tie handling without manually cleaning punctuation.
Check puzzle and game text
Measure whether a clue, pangram exercise, or word-game passage relies too heavily on one letter.
Add a content quality signal
Record the dominant letter, its count, and alphabetic totals as deterministic metadata in a text-processing workflow.
FAQ
Does uppercase count separately from lowercase?
No. Letters are converted to lowercase before counting, so A and a contribute to the same frequency.
What happens when several letters tie?
Every tied winner is returned in the letters array, ordered by its first appearance in the input.
Are spaces, numbers, and punctuation counted?
No. Only Unicode letters are counted; whitespace, digits, punctuation, symbols, and emoji are ignored.
Are accented and non-Latin letters supported?
Yes. Unicode letters across writing systems are supported. Accented letters remain distinct rather than being stripped or transliterated.
What do the total and distinct letter counts tell me?
The total is how many letters were examined, a handy yardstick for the winning count, and the distinct figure shows how varied the text is. In Mississippi River, i appears 5 times among 16 letters, and 7 different letters are used.
Related tools
For developers — API access
Everything on this page is available programmatically. This section is for teams who want to wire it into their own systems; everyone else can just use the tool above.
API endpoint
Prefer to automate it? One authenticated POST creates the task; the result comes back by webhook or a signed link. The same capability also runs here on the web, by email and from Telegram — and soon from our app too.
Call it from your stack
curl -X POST https://api.kit.forhosting.com/text/most-common-letter \
-H "Authorization: Bearer $KIT_KEY" \
-H "Content-Type: application/json" \
-d '{"text":"Mississippi River"}'const res = await fetch("https://api.kit.forhosting.com/text/most-common-letter", {
method: "POST",
headers: {
"Authorization": `Bearer ${process.env.KIT_KEY}`,
"Content-Type": "application/json"
},
body: JSON.stringify({
"text": "Mississippi River"
})
});
const { task_id } = await res.json();import os, requests
res = requests.post(
"https://api.kit.forhosting.com/text/most-common-letter",
headers={"Authorization": f"Bearer {os.environ['KIT_KEY']}"},
json={
"text": "Mississippi River"
},
)
task_id = res.json()["task_id"]<?php
$res = file_get_contents("https://api.kit.forhosting.com/text/most-common-letter", false, stream_context_create([
"http" => [
"method" => "POST",
"header" => "Authorization: Bearer " . getenv("KIT_KEY") . "\r\nContent-Type: application/json",
"content" => '{"text":"Mississippi River"}',
],
]));
$task = json_decode($res, true);body := bytes.NewBufferString(`{"text":"Mississippi River"}`)
req, _ := http.NewRequest("POST", "https://api.kit.forhosting.com/text/most-common-letter", body)
req.Header.Set("Authorization", "Bearer "+os.Getenv("KIT_KEY"))
req.Header.Set("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)Example request
{
"text": "Mississippi River"
}Example response
{
"task_id": "tsk_a1b2c3d4e5f6a1b2c3d4e5f6",
"type": "text.most_common_letter",
"status": "queued",
"_links": {
"result": "/tasks/tsk_…/result"
}
}The API is asynchronous: the call returns a task_id immediately and the result arrives by webhook. Polling is capped at 1 req/s per task.
Pricing
Published price — no tokens, no invented credits. A failed task is never charged.
Limits
max_chars | 500000 |
Errors
| HTTP | Code | Meaning |
|---|---|---|
401 | unauthorized | Missing or invalid API key. |
402 | insufficient_balance | Your balance doesn't cover the task price. |
404 | unknown_type | That task type doesn't exist. |
429 | rate_limited | Too many requests. Use the webhook instead of polling. |
Technical notes
Understand case, Unicode, and ties
The count field applies to every member of the letters array, while total_letters provides a useful denominator. The unique_letters value tells you how varied the alphabetic content is without forcing you to request a complete frequency table.
Use the result in writing and data workflows
A most-common-letter result is useful for classroom exercises, puzzle construction, lightweight corpus inspection, typography samples, and validation of generated text. A teacher can demonstrate frequency analysis without asking students to strip punctuation manually. A puzzle author can check whether a clue or passage overuses a particular letter, while a developer can add a deterministic content statistic to a quality-control pipeline. If the array contains several values, present them as equal winners and use count as the frequency for each. For API automation, send one text value and read the letters array before displaying or storing the answer; never assume that it contains only one item. The endpoint rejects input containing no letters because punctuation-only or number-only content has no meaningful winning letter. It also rejects missing or non-string text instead of silently coercing objects into misleading phrases. Processing is local to the deterministic parse engine, requires no external network service, and uses the same pure algorithm for browser and API execution. Browser use is free, while an API request uses the published base price of $0.002.
Technical questions
What if the text contains no letters?
The request returns an invalid_input error because there is no meaningful most common letter.