Nanoid is a compact, secure, URL-friendly unique string ID generator. It uses crypto.getRandomValues and a custom alphabet, letting you control the character set and ID length for your specific needs.

How does the alphabet affect collision probability?

The total number of possible IDs is alphabet.length ^ length. A larger alphabet or longer length exponentially increases the number of possible combinations, making collisions astronomically unlikely.

Is the distribution truly uniform?

Yes. This implementation uses a rejection sampling algorithm that discards biased bytes, ensuring every character in your alphabet has exactly equal probability of appearing at each position.

Nanoid Generator

Generate Nanoid identifiers with a fully customizable alphabet, configurable length, batch mode, and collision probability stats.

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AlphabetLengthCount

Nanoids

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How to use Nanoid Generator

Customize the alphabet (or keep the default A-Za-z0-9_-).
Set your desired ID length (1-64) and count (1-100).
Click Generate, review the collision stats, and copy your Nanoids.

What is Nanoid Generator?

Nanoid is a tiny, secure, URL-friendly unique string ID generator. Unlike UUID it lets you define your own alphabet and length, producing shorter IDs with the same collision resistance as UUIDs when configured with a large enough alphabet.

This tool runs fully in your browser using crypto.getRandomValues with uniform distribution. You can customize the character set (default includes A-Z, a-z, 0-9, underscore and hyphen), set any length from 1 to 64, generate up to 100 IDs at once, and see the total possible combinations and collision probability for your configuration.

FAQ

What is Nanoid?: Nanoid is a compact, secure, URL-friendly unique string ID generator. It uses crypto.getRandomValues and a custom alphabet, letting you control the character set and ID length for your specific needs.
How does the alphabet affect collision probability?: The total number of possible IDs is alphabet.length ^ length. A larger alphabet or longer length exponentially increases the number of possible combinations, making collisions astronomically unlikely.
Is the distribution truly uniform?: Yes. This implementation uses a rejection sampling algorithm that discards biased bytes, ensuring every character in your alphabet has exactly equal probability of appearing at each position.

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Author

Marcus Webb"The DevTool Craftsman"

Full-Stack Developer & Tools Architect

Marcus has been writing code since the dial-up era. He's contributed to open-source developer tools and built CI/CD pipelines for startups.

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