Chrome's Built-In AI APIs allow applications to perform selected AI workloads directly within the browser.
Unlike traditional AI integrations, developers do not need to deploy or operate model infrastructure.
This guide walks through the major APIs currently available.
Chrome's Built-In AI APIs are at different stages of maturity. Some APIs are available in stable Chrome, while others remain experimental.
The required setup therefore depends on the API you want to test.
The following APIs are available in stable Chrome on supported desktop devices:
These APIs do not require experimental flags for normal use in supported Chrome versions.
The Prompt API has different availability requirements depending on whether it is used from a web page or a Chrome Extension. Check the current Chrome documentation for the environment you are targeting.
The Writer, Rewriter, and Proofreader APIs remain experimental and may require developer trials, origin trials, or Chrome flags for local development.
Because these APIs are evolving, refer to the official Chrome documentation for the current setup requirements rather than relying on a static list of flags.
Engineering recommendation:Use feature detection andavailability()
checks at runtime rather than relying on Chrome version numbers or assuming that a particular flag is enabled.
Use cases:
const detector = await LanguageDetector.create();
const result = await detector.detect("Bonjour tout le monde");
console.log(result);
Complete runnable example:[Language Detector API on GitHub Gist]
Use cases:
const translator = await Translator.create({
sourceLanguage: "en",
targetLanguage: "ar"
});
Translation is one of the strongest candidates for browser-managed inference because it benefits from reduced latency and improved privacy.
Complete runnable example:[Translator API on GitHub Gist]
Use cases:
const summarizer = await Summarizer.create({
type: "key-points",
length: "short"
});
Summarization workloads should be evaluated against document size, latency expectations, and browser support requirements.
Complete runnable example:[Summarizer API on GitHub Gist]
The Prompt API provides access to Gemini Nano for general-purpose inference.
const session = await LanguageModel.create();
const result = await session.prompt(
"Extract structured data from this text."
);
Complete runnable example:[Prompt API on GitHub Gist]
The Writer API generates new content.
const writer = await Writer.create({
tone: "neutral",
length: "short"
});
Complete runnable example:[Writer API on GitHub Gist]
The Rewriter API transforms existing content.
const rewriter = await Rewriter.create({
tone: "more-formal"
});
Complete runnable example:[Rewriter API on GitHub Gist]
Streaming UI example:[Rewriter Streaming on GitHub Gist]
The Proofreader API focuses on grammar and correction workflows.
const proofreader = await Proofreader.create();
Complete runnable example:[Proofreader API on GitHub Gist]
Always:
Example:
const status = await LanguageModel.availability();
if (status === "unavailable") {
// fallback
}
The location of inference does not change the trust model.
AI-generated output should be validated using the same rigor applied to any other untrusted external input.
Do not:
without validation.
Begin with:
Always provide:
Local AI
↓
Cloud AI
fallback paths.
Track:
For complete runnable examples covering:
refer to the companion GitHub repository or the original article source.
Chrome's Built-In AI APIs are a practical way to experiment with browser-managed inference.
The strongest production candidates today are focused workloads such as translation, language detection, rewriting, and summarization. Larger reasoning workloads will continue to rely heavily on cloud-hosted models, leading to a hybrid future where local and remote inference coexist.