# DiceBear: deterministic SVG avatars from a seed string in seven languages

> DiceBear turns a username or email into an SVG avatar in one of 63 styles, with byte-identical output across JavaScript, PHP, Python, Rust, Go, Dart and C#. Here is how the library works, how to install it, and where it stops being the right tool.

**dicebear/dicebear** — DiceBear is an avatar library for designers and developers. 🌍

- Repository: https://github.com/dicebear/dicebear
- Website: https://www.dicebear.com
- Stars: 9,742 · Forks: 420
- Language: Vue
- License: MIT
- Published: 2026-09-21 · Updated: 2026-09-21 · Language: en
- Canonical page: https://hysenlabs.com/projects/dicebear-dicebear

## The problem DiceBear solves: no upload, no storage, no broken image links

Most applications need a picture next to a name. The usual answer is an upload form, a bucket, a resize pipeline and a default image for the users who never upload anything. DiceBear replaces that with a string. You take a username, an email address or any other stable identifier, pass it to the library, and get back an SVG. The same seed always produces the same avatar, so the database column holds text, not a file, and there is nothing to garbage-collect when an account is deleted.

The audience is developers who need placeholder or identity avatars at scale: comment threads, admin dashboards, team pages, seeded demo data, test fixtures. The README frames it as a library for designers and developers, and the 63 styles range from hand-drawn characters to abstract patterns, which matters because a geometric pattern reads differently from a cartoon face in a settings page. Designers get a Figma route to author styles; developers get a function call.

## How the seed becomes an SVG: styles as JSON definitions

The core object is a Style, and a style is a plain JSON definition. In JavaScript you import a definition file, wrap it in a Style, and hand it to an Avatar together with options such as seed and size. The Avatar instance then exposes the result as a string or as a data URI. That is the whole data flow: definition plus options in, SVG out.

The definitions live in the separate dicebear/styles repository and ship as a package per language, so the drawing instructions are data rather than code compiled into the library. The shared test suite is the interesting part of the design. According to the README, every port must produce byte-identical SVG to the JavaScript reference. That constraint is what makes the multi-language story usable: you can render in the browser and regenerate the same bytes later in a Go or PHP backend without storing the image. It also means the ports cannot drift into dialect-specific rendering, which is a real restriction on contributors but a benefit for anyone mixing runtimes.

Customization happens through style options: colors, backgrounds, rotation, and individual features such as hair or glasses. Because those options are part of the definition schema, the same option names apply across languages.

## Installing dicebear/core and rendering a first avatar

The JavaScript package installs from npm. The README gives the command and the import names exactly as below.

```bash
npm install @dicebear/core
```

The quickest path to a rendered avatar is the CLI, which needs no project setup. It prints an avatar to the terminal or writes files in bulk, and the README shows this invocation for the lorelei style.

```bash
npx dicebear create lorelei -o ./avatars --count 10
```

After that runs, the ./avatars directory should contain ten generated files. If you are wiring the library into an application instead, the README's example imports the core package and a style definition, constructs an Avatar, and calls toString() for an SVG string or toDataUri() for an embeddable data URI.

```js
import { Avatar, Style } from '@dicebear/core';
import definition from '@dicebear/styles/lorelei.json' with { type: 'json' };

const avatar = new Avatar(new Style(definition), {
  seed: 'John',
  size: 128,
});

avatar.toString(); // SVG string
avatar.toDataUri(); // data:image/svg+xml;charset=utf-8,...
```

If you would rather not write code at all, the HTTP API takes a plain URL and needs no account. The README's example is https://api.dicebear.com/10.x/lorelei/svg?seed=Felix, and the same page points at a self-hosting recipe that runs the API as a single Docker container. For other runtimes, the install table covers composer require dicebear/core, pip install dicebear-core, cargo add dicebear-core, go get github.com/dicebear/dicebear-go/v11, dart pub add dicebear_core and dotnet add package DiceBear.Core.

## Where DiceBear stops being the right tool

The output is SVG, and the styles are illustrated or abstract by construction. If your product needs a photorealistic face, a likeness of a real person, or anything generated by a model, this library does not do that and no option will make it. The README describes a fixed catalogue of 63 styles, so the visual range is bounded by what style authors have published.

The determinism is also a constraint in the other direction. Because the same seed always yields the same avatar, changing a user's look means changing the seed or the options you pass, and if you change them in one place and not another you get two different avatars for the same account. Teams that render in the browser and in a backend job need to keep the style name, the style version and the option set in sync; the byte-identical guarantee only holds while those match.

Finally, the public HTTP API is a third-party dependency on the request path. The README offers self-hosting with a single Docker container for what it calls full control and privacy, which is a fair description of the trade-off: the convenience endpoint means the seed string leaves your infrastructure.

## DiceBear compared with a hand-rolled SVG generator

The obvious alternative is writing your own generator: a small function that hashes the seed into a palette and emits a few shapes. The difference is in what you inherit. A hand-rolled generator gives you total control over the visual language and no dependency, but you own the cross-language problem yourself. The moment a second runtime needs to produce the same avatar, you are reimplementing the hash and the drawing rules and hoping they agree.

DiceBear's approach is to make the drawing instructions portable data and to enforce agreement with a shared test suite. That buys you the seven-language parity described in the README, at the cost of adopting a definition format and a catalogue you did not design. If your avatars only ever render in one JavaScript frontend, a hand-rolled generator is genuinely lighter. If they render in more than one place, or you want 63 ready-made styles without commissioning art, the library is doing work you would otherwise repeat.

## Maintenance, upgrades and what the licences actually cover

The repository is not archived, and the last push was on 2026-09-19. Releases have been frequent: v10.5.0 on 2026-08-09, v10.6.0 on 2026-08-17 and v10.7.0 on 2026-08-26. The default branch is 11.x while the published releases are 10.x, and the README's HTTP API example uses the 10.x path segment, so an upgrade to 11.x is a version boundary worth reading the release notes for rather than assuming.

The monorepo is an npm workspace driven by turbo, with build, test and type-check scripts that fan out across src/js/* and apps/*. The seven core libraries, the CLI, the SVG-to-raster converter, the documentation site and the editor all live here, while styles, schema, the HTTP API and the Figma plugin sit in their own repositories. That split means a style change and a library change are separate upgrade decisions.

On licensing: the code is MIT, which the README notes includes commercial use. The styles are the exception. They are the work of their respective creators and carry their own licences, and the license overview page lists them all; the README says many only ask for attribution. That distinction matters if you ship a specific style, because the MIT grant on the library does not automatically cover the artwork. Check the overview for the styles you actually use.

## Conclusion

Adopt DiceBear if you want to store a seed string instead of a profile picture and need the same avatar to come out of a browser, a Go service and a PHP job. Do not adopt it if you need photographic or AI-generated likenesses, or if you cannot accept that the default HTTP API sends your seed to someone else's server. Before you commit, check the license overview page for the specific styles you plan to ship, and decide whether you need the self-hosted API container or can live with the public endpoint.

## FAQ

### Is DiceBear free to use?

The code is MIT licensed, which the README says includes commercial use, and the HTTP API is described as free and without an account. The avatar styles are separate: they are the work of their respective creators and carry their own licences, listed on the license overview page.

### Is the DiceBear API free?

The README describes the HTTP API as free and without an account, returning avatars from a plain URL such as https://api.dicebear.com/10.x/lorelei/svg?seed=Felix. For full control and privacy it points to a recipe that self-hosts the API with a single Docker container.

### How do I use DiceBear?

Install @dicebear/core with npm, import a style definition, and construct an Avatar with a seed and options; the instance returns an SVG string via toString() or a data URI via toDataUri(). The CLI is an alternative: npx dicebear create lorelei -o ./avatars --count 10 writes files in bulk.

### What is api.dicebear.com?

It is the HTTP API that returns avatars from a plain URL, free and without an account, for example https://api.dicebear.com/10.x/lorelei/svg?seed=Felix. The README also documents self-hosting it as a single Docker container.

## Sources

- [dicebear/dicebear on GitHub](https://github.com/dicebear/dicebear)
- [License: MIT](https://github.com/dicebear/dicebear/blob/11.x/LICENSE)
- [Project website](https://www.dicebear.com)
- [README](https://github.com/dicebear/dicebear/blob/11.x/README.md)
- [Releases](https://github.com/dicebear/dicebear/releases)

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Hysen Labs editorial analysis, written from the project's own repository and release notes. Cite the canonical page: https://hysenlabs.com/projects/dicebear-dicebear