How are list items detected?

Each non-empty line is one item. Leading bullet markers (-, *, +, or 1.) and surrounding whitespace are stripped before comparison, so '- set up CI' and 'set up CI' are treated the same.

What is fuzzy matching and when should I use it?

Fuzzy matching uses Levenshtein edit distance to collapse items that are nearly identical — 'set up CI' versus 'set up CI/CD'. Use it when different LLM runs phrase the same point slightly differently. Leave it off when small wording differences matter.

Does deduplication ignore case?

By default comparison is case-insensitive and whitespace-normalised, so 'Set Up CI' and 'set up ci' are duplicates. The first occurrence's original casing is kept in the output.

What order does the merged list come out in?

First-seen order across box 1, then box 2, then box 3. The earliest occurrence of each unique item is kept and later duplicates are dropped, which preserves the most natural reading order.

How many lists can I merge?

Up to three at once, which covers the common case of combining a few LLM runs or model outputs. Each box is optional — leave the extras blank to dedupe a single list.

AI List Deduplicator & Merger

Merge and dedupe AI lists

Ask the same question to two models, or run one model twice, and you get two overlapping bullet lists. Combining them by hand means scanning for repeats. This tool merges up to three lists, strips the duplicates, and optionally collapses near-duplicates so you end up with one clean, deduplicated list.

How it works

Each line becomes an item; bullet markers and whitespace are stripped, and comparison is case-insensitive. In exact mode, items that normalise to the same string are collapsed to their first occurrence. In fuzzy mode, the tool also computes the Levenshtein edit distance between items and merges any pair whose similarity exceeds your threshold.

List A: set up CI, write tests
List B: write tests, set up CI/CD

fuzzy ->  set up CI, write tests   (CI/CD merged into CI)

Tips and notes

Use exact mode when wording precision matters and fuzzy mode when different runs just phrase the same idea differently — start the similarity threshold around 85% and adjust. First-seen order is preserved, so the earliest phrasing of each point wins. To compare two responses line by line instead of merging them, use the AI Output Diff tool.