Alibaba Provider

Alibaba Cloud Model Studio provides access to the Qwen model series, including advanced reasoning capabilities.

API keys can be obtained from the Console.

Setup

The Alibaba provider is available via the @ai-sdk/alibaba module. You can install it with:

pnpm add @ai-sdk/alibaba

Provider Instance

You can import the default provider instance alibaba from @ai-sdk/alibaba:

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import { alibaba } from '@ai-sdk/alibaba';

For custom configuration, you can import createAlibaba and create a provider instance with your settings:

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import { createAlibaba } from '@ai-sdk/alibaba';
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const alibaba = createAlibaba({
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  apiKey: process.env.ALIBABA_API_KEY ?? '',
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});

You can use the following optional settings to customize the Alibaba provider instance:

• baseURL string

  Use a different URL prefix for API calls, e.g. to use proxy servers or regional endpoints. The default prefix is https://dashscope-intl.aliyuncs.com/compatible-mode/v1.

• apiKey string

  API key that is being sent using the Authorization header. It defaults to the ALIBABA_API_KEY environment variable.

• headers Record<string,string>

  Custom headers to include in the requests.

• fetch (input: RequestInfo, init?: RequestInit) => Promise<Response>

  Custom fetch implementation.

• includeUsage boolean

  Include usage information in streaming responses. When enabled, token usage will be included in the final chunk. Defaults to true.

Language Models

You can create language models using a provider instance:

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import { alibaba } from '@ai-sdk/alibaba';
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import { generateText } from 'ai';
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const { text } = await generateText({
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  model: alibaba('qwen-plus'),
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  prompt: 'Write a vegetarian lasagna recipe for 4 people.',
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});

You can also use the .chatModel() or .languageModel() factory methods:

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const model = alibaba.chatModel('qwen-plus');
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// or
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const model = alibaba.languageModel('qwen-plus');

Alibaba language models can be used in the streamText function (see AI SDK Core).

The following optional provider options are available for Alibaba models:

• enableThinking boolean

  Enable thinking/reasoning mode for supported models. When enabled, the model generates reasoning content before the response. Defaults to false.

• thinkingBudget number

  Maximum number of reasoning tokens to generate. Limits the length of thinking content.

• parallelToolCalls boolean

  Whether to enable parallel function calling during tool use. Defaults to true.

Thinking Mode

Alibaba's Qwen models support thinking/reasoning mode for complex problem-solving:

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import { alibaba } from '@ai-sdk/alibaba';
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import { generateText } from 'ai';
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const { text, reasoning } = await generateText({
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  model: alibaba('qwen3-max'),
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  providerOptions: {
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    alibaba: {
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      enableThinking: true,
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      thinkingBudget: 2048,
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    },
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  },
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  prompt: 'How many "r"s are in the word "strawberry"?',
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});
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console.log('Reasoning:', reasoning);
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console.log('Answer:', text);

For models that are thinking-only (like qwen3-235b-a22b-thinking-2507), thinking mode is enabled by default.

Tool Calling

Alibaba models support tool calling with parallel execution:

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import { alibaba } from '@ai-sdk/alibaba';
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import { generateText, tool } from 'ai';
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import { z } from 'zod';
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const { text } = await generateText({
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  model: alibaba('qwen-plus'),
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  tools: {
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    weather: tool({
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      description: 'Get the weather in a location',
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      parameters: z.object({
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        location: z.string().describe('The location to get the weather for'),
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      }),
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      execute: async ({ location }) => ({
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        location,
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        temperature: 72 + Math.floor(Math.random() * 21) - 10,
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      }),
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    }),
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  },
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  prompt: 'What is the weather in San Francisco?',
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});

Prompt Caching

Alibaba supports both implicit and explicit prompt caching to reduce costs for repeated prompts.

Implicit caching works automatically - the provider caches appropriate content without any configuration. For more control, you can use explicit caching by marking specific messages with cacheControl:

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import { alibaba } from '@ai-sdk/alibaba';
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import { generateText } from 'ai';
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const { text, usage } = await generateText({
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  model: alibaba('qwen-plus'),
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  messages: [
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    {
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      role: 'system',
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      content: 'You are a helpful assistant. [... long system prompt ...]',
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      providerMetadata: {
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        alibaba: {
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          cacheControl: { type: 'ephemeral' },
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        },
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      },
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    },
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    {
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      role: 'user',
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      content: 'What is the capital of France?',
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    },
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  ],
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});

Model Capabilities

Please see the Alibaba Cloud Model Studio docs for a full list of available models. You can also pass any available provider model ID as a string if needed.