Text Similarity Checker
Compare two texts to measure how similar they are using cosine similarity and Jaccard index
What is Text Similarity Checker?
A text similarity checker measures how alike two pieces of text are by computing mathematical similarity scores. Unlike a simple diff tool that highlights character-level differences, a similarity checker works at the word or token level to give a meaningful measure of semantic and lexical overlap — even when sentences are reordered or synonyms are used.
This tool computes two widely used metrics. Cosine similarity represents each text as a word-frequency vector and measures the angle between them — a score of 1.0 means the texts are identical in word distribution, while 0 means they share no words at all. The Jaccard index divides the number of shared unique words by the total number of unique words across both texts, giving a straightforward overlap percentage that is easy to interpret.
Text similarity has many practical uses. Educators checking for paraphrased plagiarism can compare a submitted essay against a source. Content marketers can verify that two versions of a page are sufficiently different to avoid duplicate-content penalties. Developers building search engines or recommendation systems use similarity scores to rank results. Customer support teams can find duplicate tickets or match incoming queries to existing FAQs. Understanding how similar two documents are, expressed as a number, is far more useful than simply eyeballing them.
How to Use Text Similarity Checker
- Enter the first text
Paste or type your first document, paragraph, or sentence into the left input area.
- Enter the second text
Paste or type the text you want to compare against into the right input area.
- View similarity scores
Cosine similarity and Jaccard index are calculated instantly, displayed as scores from 0 to 1 with percentage labels.
- Review shared words
A breakdown of shared and unique words helps you understand what is driving the similarity score.
Key Benefits
Cosine similarity and Jaccard index give you complementary perspectives on how similar the texts are.
Scores update as you type — no need to submit a form or wait for a server response.
See exactly which words the two texts share and which are unique, making it easy to interpret the scores.
Both texts are processed in your browser only — they are never sent to a server or stored anywhere.
Frequently Asked Questions
A score of 0.8 means the word-frequency vectors of the two texts point in nearly the same direction — the texts share most of the same words in similar proportions. A score of 1.0 is a perfect match.
The Jaccard index measures the ratio of shared unique words to total unique words, treating each word as either present or absent. Cosine similarity also accounts for how often each word appears.
No. Both metrics are lexical — they compare the actual words used, not their meaning. A sentence rewritten with synonyms will score lower than its literal copy.
Search engines generally consider pages with over 70–80% similarity as potential duplicates. Use this tool as a rough guide, but note that it measures word overlap rather than full semantic meaning.