jeasonstudio/chrome-ai is a community provider that uses Chrome Built-in AI to provide language model support for the Vercel AI SDK.

This module is under development and may contain errors and frequent incompatible changes.


The ChromeAI provider is available in the chrome-ai module. You can install it with:

pnpm install chrome-ai

Enabling AI in Chrome

Chrome's implementation of built-in AI with Gemini Nano is experimental and will change as they test and address feedback.

Chrome built-in AI is a preview feature, you need to use chrome version 127 or greater, now in dev or canary channel, may release on stable chanel at Jul 17, 2024.

After then, you should turn on these flags:

Language Models

The chromeai provider instance is a function that you can invoke to create a language model:

import { chromeai } from 'chrome-ai';
const model = chromeai();

It automatically selects the correct model id. You can also pass additional settings in the second argument:

import { chromeai } from 'chrome-ai';
const model = chromeai('generic', {
// additional settings
temperature: 0.5,
topK: 5,

You can use the following optional settings to customize:

  • modelId 'text' | 'generic'

    Used to distinguish models of Gemini Nano, there is no difference in the current version.

  • temperature number

    The value is passed through to the provider. The range depends on the provider and model. For most providers, 0 means almost deterministic results, and higher values mean more randomness.

  • topK number

    Only sample from the top K options for each subsequent token.

    Used to remove "long tail" low probability responses. Recommended for advanced use cases only. You usually only need to use temperature.


You can use Chrome built-in language models to generate text with the generateText or streamText function:

import { generateText } from 'ai';
import { chromeai } from 'chrome-ai';
const { text } = await generateText({
model: chromeai(),
prompt: 'Who are you?',
console.log(text); // I am a large language model, trained by Google.
import { streamText } from 'ai';
import { chromeai } from 'chrome-ai';
const { textStream } = await streamText({
model: chromeai(),
prompt: 'Who are you?',
let result = '';
for await (const textPart of textStream) {
result = textPart;
// I am a large language model, trained by Google.

Chrome built-in language models can also be used in the generateObject function:

import { generateObject } from 'ai';
import { chromeai } from 'chrome-ai';
import { z } from 'zod';
const { object } = await generateObject({
model: chromeai('text'),
schema: z.object({
recipe: z.object({
name: z.string(),
ingredients: z.array(
name: z.string(),
amount: z.string(),
steps: z.array(z.string()),
prompt: 'Generate a lasagna recipe.',
// { recipe: {...} }

Due to model reasons, toolCall and streamObject are not supported. We are making an effort to implement these functions by prompt engineering.