--- 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: ## 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<string,string>_ Custom headers to include in the requests. - **fetch** _(input: RequestInfo, init?: RequestInit) => Promise<Response>_ 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`: `'adaptive' | 'enabled' | 'disabled'` - Enable, disable, or let the model decide (`adaptive`) when to think. See [DeepSeek's thinking mode docs](https://api-docs.deepseek.com/guides/thinking_mode). - `reasoningEffort` _'low' | 'medium' | 'high' | 'xhigh' | 'max'_ Optional. Controls thinking strength for DeepSeek V4 reasoning models. Per DeepSeek's docs, `low` and `medium` are mapped to `high`, and `xhigh` is mapped to `max` server-side for compatibility with other providers. When using the top-level `reasoning` setting, `minimal` is sent as `low`, and `low`, `medium`, `high`, and `xhigh` pass through to DeepSeek's native effort values. ```ts highlight="7-12" import { deepSeek, type DeepSeekLanguageModelChatOptions, } 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' }, reasoningEffort: 'high', } satisfies DeepSeekLanguageModelChatOptions, }, }); ``` ### 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.stream) { 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 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). ## Model Capabilities | Model | Text Generation | Object Generation | Image Input | Tool Usage | Tool Streaming | | ------------------- | ------------------- | ------------------- | ------------------- | ------------------- | ------------------- | | `deepseek-chat` | | | | | | | `deepseek-reasoner` | | | | | | 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.