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DeepSeek offers AI dialogue, application, and model API services. Users can access the web version or the official app via the official website, while developers can integrate the model through the open platform and documentation.

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What is DeepSeek?

DeepSeek’s official website separates the conversational interface for individual users from the API interface for developers. If you wish to use it directly, you can access the web version or download the official app, where you can submit questions, data, and tasks via chat; if you want to integrate the model into your own product, you should use the open platform and configure calls according to the API documentation.

The official website also publishes model research and version‑update information. The capabilities, context, and invocation methods may vary across versions; therefore, when making your selection, refer to the current open‑platform model documentation and do not treat older version names or third‑party descriptions as fixed capabilities for all entry points. For real‑world business tasks, you should use your own samples to validate the responses and integration results.

The web-based experience and the Developer API follow separate usage paths. For pricing, model parameters, access rules, and service status, please refer to the official pages; do not infer API quotas or pricing based on the web interface’s user experience. When working with professional conclusions, figures, and citations, always verify against the original sources.

Key features

  • Conversation access: Interact with the model via the official web version and the app.

  • Development and Integration: The open platform and API documentation are provided for product integration.

  • Version Information: Check the official website for model research, release notes, and service status.

Use cases and audience

Individual users who need AI-powered conversations, as well as developers and product teams that require model APIs.

  • Clinical辅助 diagnosis
  • Education sector
  • Intelligent Data Quality Monitoring
  • Natural Language Data Query
Input

Questions, task descriptions, and the data supported by the entry points used.

Output

The generated result from the model's response or the API's return.

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