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Text Similarity Checker

Measure how similar two texts are as a percentage.

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Only in the first

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In both

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Only in the second

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Quick Tool Overview

The Text Similarity Checker reports four established similarity measures at once — Levenshtein, Jaccard, cosine and Dice — because each answers a different question, and where they disagree the disagreement is itself the useful finding.

What it does
Scores how similar two texts are, four different ways
You give it
Two texts or documents
You get back
Four percentage scores plus the shared and unique content
Best for
Fuzzy matching, deduplication and comparing drafts
Text Tools Free, unlimited use No sign-up Runs in your browser

About the Text Similarity Checker

"How similar are these?" needs a number, and the honest answer is that it depends which kind of similarity you mean. Two texts can share every word in a different order, or differ by one character in every word. Those are opposite results under different measures, and a single percentage hides that.

So this reports four: Levenshtein similarity, which counts the single-character edits needed to turn one into the other; Jaccard similarity, which compares the sets of words they use; cosine similarity over word frequencies, which is what search engines use; and Dice coefficient over character pairs, which is good at catching near-matching names. Each measures something real, and where they disagree the disagreement is the useful information.

Key features of the Text Similarity Checker

Four real algorithms

Levenshtein for near-identical strings, Jaccard and cosine for documents, Dice for fuzzy name matching.

Explains what each measures

So you can pick the score that fits your question rather than trusting a single number blindly.

Shared and unique words listed

The vocabulary each text has to itself, alongside what they hold in common.

Interpretation guidance

What a 90 per cent means versus a 40 per cent, so the figure translates into a decision.

Handles any length

From two product names to two full articles, with the expensive edit-distance calculation capped so long texts stay responsive.

How to use the Text Similarity Checker

  1. 1

    Paste both texts

    The two versions or documents you want compared.

  2. 2

    Read the four scores

    Levenshtein, Jaccard, cosine and Dice each measure similarity differently and are shown together.

  3. 3

    Check the shared content

    The words both texts use and the words unique to each are listed below the scores.

  4. 4

    Interpret the spread

    Where the four scores disagree, the reason is explained — that is usually the most useful finding.

Frequently asked questions

It depends on the question. Levenshtein for near-identical strings such as names or SKUs. Jaccard or cosine for documents, where word choice matters more than order. Dice for fuzzy name matching. The page explains what each one is measuring.

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What people who use the Text Similarity Checker think of it. Reviews come from visitors and are posted as written.

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