Get Started with Vercel AI SDK

What is Vercel AI SDK?

The Vercel AI SDK is a powerful TypeScript toolkit for building AI-powered applications with React, Next.js, Vue, Svelte, and more. It provides a unified interface for working with different AI providers, streaming responses, and building interactive AI experiences. Learn more at sdk.vercel.ai. By integrating Cerebras with the Vercel AI SDK, you can leverage ultra-fast inference speeds while using familiar AI SDK patterns and components.

Prerequisites

Before you begin, ensure you have:

Cerebras API Key - Get a free API key here
Node.js 22 or higher - Required by the current AI SDK packages
npm, yarn, or pnpm - Package manager for installing dependencies

Configure Vercel AI SDK with Cerebras

Install required dependencies

Install the Vercel AI SDK and its native Cerebras provider:

npm install ai @ai-sdk/cerebras zod

yarn add ai @ai-sdk/cerebras zod

pnpm add ai @ai-sdk/cerebras zod

Configure environment variables

Create a .env.local file in your project root to store your Cerebras API key securely:

CEREBRAS_API_KEY=your-cerebras-api-key-here

If you’re using Next.js, avoid prefixing with NEXT_PUBLIC_ to keep your API key private and prevent browser exposure.

Create a Cerebras provider instance

Create a provider instance with your Cerebras API key:

import { createCerebras } from '@ai-sdk/cerebras';

const cerebras = createCerebras({
  apiKey: process.env.CEREBRAS_API_KEY,
});

You can also import the default cerebras provider directly when CEREBRAS_API_KEY is available in the environment.

Generate streaming text responses

Use the streamText function to generate streaming text responses. This is perfect for chat interfaces where you want to show responses as they’re generated:

import { streamText } from 'ai';
import { createCerebras } from '@ai-sdk/cerebras';

const cerebras = createCerebras({
  apiKey: process.env.CEREBRAS_API_KEY,
});

const result = await streamText({
  model: cerebras('gpt-oss-120b'),
  prompt: 'Explain the concept of quantum computing in simple terms.',
});

// Stream the response
for await (const textPart of result.textStream) {
  process.stdout.write(textPart);
}

The streamText function returns an async iterable that yields text chunks as they’re generated, providing a smooth user experience with Cerebras’s ultra-fast inference.

Generate text responses

Use the generateText function for non-streaming text generation:

import { generateText } from 'ai';
import { createCerebras } from '@ai-sdk/cerebras';

const cerebras = createCerebras({
  apiKey: process.env.CEREBRAS_API_KEY,
});

const result = await generateText({
  model: cerebras('gpt-oss-120b'),
  prompt: 'Write a haiku about programming.',
});

console.log(result.text);

The generateText function returns the complete response at once, which is useful for batch processing or when you don’t need streaming.

Available Models

You can use any of the following Cerebras models with the Vercel AI SDK:

Model	Description	Best For
`gpt-oss-120b`	120B production model	General text, coding, and tool use
`gemma-4-31b`	31B preview multimodal model	Text and image input
`zai-glm-4.7`	355B preview reasoning model	Reasoning workloads before its scheduled deprecation on August 17, 2026

Example usage:

import { createCerebras } from '@ai-sdk/cerebras';

const cerebras = createCerebras({
  apiKey: process.env.CEREBRAS_API_KEY,
});

const model = cerebras('gpt-oss-120b');

Advanced Features

Tool Calling

The Vercel AI SDK supports tool calling (function calling) with Cerebras models. This allows the model to call external functions and use their results:

import { generateText, tool } from 'ai';
import { createCerebras } from '@ai-sdk/cerebras';
import { z } from 'zod';

const cerebras = createCerebras({
  apiKey: process.env.CEREBRAS_API_KEY,
});

const result = await generateText({
  model: cerebras('gpt-oss-120b'),
  tools: {
    weather: tool({
      description: 'Get the weather in a location',
      inputSchema: z.object({
        location: z.string().describe('The location to get the weather for'),
      }),
      execute: async ({ location }) => ({
        location,
        temperature: 72 + Math.floor(Math.random() * 21) - 10,
      }),
    }),
  },
  prompt: 'What is the weather in San Francisco?',
});

console.log(result.text);

Troubleshooting

API Key Not Found

If you see an error about missing API keys:

Verify your .env.local file contains CEREBRAS_API_KEY
Restart your development server after adding environment variables
In production, ensure environment variables are set in your deployment platform (Vercel, AWS, etc.)
Check that you’re not accidentally using NEXT_PUBLIC_ prefix

Model Not Found

If you receive a “model not found” error:

Check that you’re using a current Cerebras model name such as gpt-oss-120b or gemma-4-31b
Ensure you’re using the correct format: cerebras('model-name')
Verify your API key has access to the requested model
Try a different model to isolate the issue

Streaming Not Working

If streaming responses aren’t displaying:

Ensure you’re using streamText instead of generateText for streaming
Check that your API route returns result.toDataStreamResponse()
Verify your client component uses the useChat or useCompletion hook correctly
Check browser console for network errors
Ensure your hosting platform supports streaming responses

TypeScript Errors

If you encounter TypeScript errors:

Make sure you have @types/node installed: npm install -D @types/node
Verify your tsconfig.json includes the necessary compiler options
Check that all AI SDK packages are up to date: npm update ai @ai-sdk/cerebras
Ensure you’re using Node.js 22 or higher

Rate Limiting or Timeout Errors

If you experience rate limiting or timeouts:

Check your Cerebras API key quota and usage limits
Implement retry logic with exponential backoff
Reduce unnecessary output tokens and retry only transient failures
Monitor your request patterns and optimize batch processing

Next Steps

Explore the Vercel AI SDK documentation for more features and examples
Try different Cerebras models to find the best fit for your use case
Check out example applications built with the AI SDK

Integrations

Agentic Frameworks

AI Development Kits

Coding Tools

Containerization

Observability & Evaluation

LLM Integration Tools

LLM Application Frameworks

Document Processing

Real-Time Audio

Multi-LLM Management

No-Code/Low-Code Platforms

What is Vercel AI SDK?

Prerequisites

Configure Vercel AI SDK with Cerebras

Available Models

Advanced Features

Tool Calling

Troubleshooting

Next Steps

​What is Vercel AI SDK?

​Prerequisites

​Configure Vercel AI SDK with Cerebras

​Available Models

​Advanced Features

​Tool Calling

​Troubleshooting

​Next Steps

What is Vercel AI SDK?

Prerequisites

Configure Vercel AI SDK with Cerebras

Available Models

Advanced Features

Tool Calling

Troubleshooting

Next Steps