---
title: DeepSeek
description: Learn how to use DeepSeek's models with the AI SDK.
---

# DeepSeek Provider

The [DeepSeek](https://www.deepseek.com) provider offers access to powerful language models through the DeepSeek API.

API keys can be obtained from the [DeepSeek Platform](https://platform.deepseek.com/api_keys).

## Setup

The DeepSeek provider is available via the `@ai-sdk/deepseek` module. You can install it with:

<Tabs items={['pnpm', 'npm', 'yarn', 'bun']}>
  <Tab>
    <Snippet text="pnpm add @ai-sdk/deepseek" dark />
  </Tab>
  <Tab>
    <Snippet text="npm install @ai-sdk/deepseek" dark />
  </Tab>
  <Tab>
    <Snippet text="yarn add @ai-sdk/deepseek" dark />
  </Tab>
  <Tab>
    <Snippet text="bun add @ai-sdk/deepseek" dark />
  </Tab>
</Tabs>

## Provider Instance

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

```ts
import { deepseek } from '@ai-sdk/deepseek';
```

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

```ts
import { createDeepSeek } from '@ai-sdk/deepseek';

const deepseek = createDeepSeek({
  apiKey: process.env.DEEPSEEK_API_KEY ?? '',
});
```

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

- **baseURL** _string_

  Use a different URL prefix for API calls.
  The default prefix is `https://api.deepseek.com`.

- **apiKey** _string_

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

- **headers** _Record&lt;string,string&gt;_

  Custom headers to include in the requests.

- **fetch** _(input: RequestInfo, init?: RequestInit) => Promise&lt;Response&gt;_

  Custom [fetch](https://developer.mozilla.org/en-US/docs/Web/API/fetch) implementation.

## Language Models

You can create language models using a provider instance:

```ts
import { deepseek } from '@ai-sdk/deepseek';
import { generateText } from 'ai';

const { text } = await generateText({
  model: deepseek('deepseek-chat'),
  prompt: 'Write a vegetarian lasagna recipe for 4 people.',
});
```

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

```ts
const model = deepseek.chat('deepseek-chat');
// or
const model = deepseek.languageModel('deepseek-chat');
```

DeepSeek language models can be used in the `streamText` function
(see [AI SDK Core](/docs/ai-sdk-core)).

The following optional provider options are available for DeepSeek models:

- `thinking` _object_

  Optional. Controls thinking mode (chain-of-thought reasoning). You can enable thinking mode either by using the `deepseek-reasoner` model or by setting this option.

  - `type`: `'enabled' | 'disabled'` - Enable or disable thinking mode.

```ts highlight="7-11"
import { deepseek } from '@ai-sdk/deepseek';
import { generateText } from 'ai';

const { text, reasoning } = await generateText({
  model: deepseek('deepseek-chat'),
  prompt: 'How many "r"s are in the word "strawberry"?',
  providerOptions: {
    deepseek: {
      thinking: { type: 'enabled' },
    },
  },
});
```

### Reasoning

DeepSeek has reasoning support for the `deepseek-reasoner` model. The reasoning is exposed through streaming:

```ts
import { deepseek } from '@ai-sdk/deepseek';
import { streamText } from 'ai';

const result = streamText({
  model: deepseek('deepseek-reasoner'),
  prompt: 'How many "r"s are in the word "strawberry"?',
});

for await (const part of result.fullStream) {
  if (part.type === 'reasoning') {
    // This is the reasoning text
    console.log('Reasoning:', part.text);
  } else if (part.type === 'text') {
    // This is the final answer
    console.log('Answer:', part.text);
  }
}
```

See [AI SDK UI: Chatbot](/docs/ai-sdk-ui/chatbot#reasoning) for more details
on how to integrate reasoning into your chatbot.

### Cache Token Usage

DeepSeek provides context caching on disk technology that can significantly reduce token costs for repeated content. You can access the cache hit/miss metrics through the `providerMetadata` property in the response:

```ts
import { deepseek } from '@ai-sdk/deepseek';
import { generateText } from 'ai';

const result = await generateText({
  model: deepseek('deepseek-chat'),
  prompt: 'Your prompt here',
});

console.log(result.providerMetadata);
// Example output: { deepseek: { promptCacheHitTokens: 1856, promptCacheMissTokens: 5 } }
```

The metrics include:

- `promptCacheHitTokens`: Number of input tokens that were cached
- `promptCacheMissTokens`: Number of input tokens that were not cached

<Note>
  For more details about DeepSeek's caching system, see the [DeepSeek caching
  documentation](https://api-docs.deepseek.com/guides/kv_cache#checking-cache-hit-status).
</Note>

## Model Capabilities

| Model               | Text Generation     | Object Generation   | Image Input         | Tool Usage          | Tool Streaming      |
| ------------------- | ------------------- | ------------------- | ------------------- | ------------------- | ------------------- |
| `deepseek-chat`     | <Check size={18} /> | <Check size={18} /> | <Cross size={18} /> | <Check size={18} /> | <Check size={18} /> |
| `deepseek-reasoner` | <Check size={18} /> | <Check size={18} /> | <Cross size={18} /> | <Check size={18} /> | <Check size={18} /> |

<Note>
  Please see the [DeepSeek
  docs](https://api-docs.deepseek.com/quick_start/pricing) for a full list of
  available models. You can also pass any available provider model ID as a
  string if needed.
</Note>