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DeepSeek

DeepSeek offers free AI chat and coding models with high-quality responses.
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DeepSeek

What is DeepSeek?

DeepSeek is a free and open-source collection of large language models that includes two main models: DeepSeek Chat and DeepSeek Coder. Users can interact with these models on the official DeepSeek website or run them locally with the model checkpoint files available on Hugging Face. DeepSeek Chat allows for chatting with the AI in a manner similar to other chatbots like ChatGPT and Bard, while DeepSeek Coder is particularly useful for coding-related queries. The models are designed to provide high-quality responses, especially in the context of coding inquiries. The capabilities of DeepSeek-V2 include delivering impressive performance on major large model leaderboards, such as ranking top 3 in AlignBench and providing competitive results in areas like math, code, and reasoning. The API pricing for DeepSeek is set at $0.14 per million input tokens and $0.28 per million output tokens.

Who created DeepSeek?

DeepSeek was created by an individual whose specific details are not provided in the available documents. The platform offers a free and open-source collection of large language models, including DeepSeek Chat and DeepSeek Coder, catering to various AI-related tasks like chat interactions and coding assistance.

What is DeepSeek used for?

  • DeepSeek Chat for interacting and chatting with AI
  • DeepSeek Coder for coding-related questions and responses
  • Specializes in math, code, and reasoning tasks
  • Offers models that can be accessed on the official DeepSeek website or run locally
  • Supports 128K context length
  • Delivers impressive results on major large model leaderboards like AlignBench and MT-Bench
  • Ranks top tier in various benchmarks like AlignBench and surpasses models like GPT-4
  • Used for Chinese General Knowledge, Arithmetic, Math, Reasoning, and Coding tasks
  • AI coding tools and AI writers & assistants are also part of its offerings
  • Competes with other tools like Codestral, HuggingChat, and Code Llama

How to use DeepSeek?

To use Deepseek, follow these steps:

  1. Access Deepseek: Visit the official Deepseek website to interact with the AI models - Deepseek Chat and Deepseek Coder.

  2. Chat with AI: Use Deepseek Chat for general interactions akin to chatbots like ChatGPT and Bard.

  3. Coding Assistance: For coding queries, utilize Deepseek Coder for optimized responses.

  4. Local Run: Alternatively, run the models locally with checkpoint files available on Hugging Face for more control.

  5. Check Capabilities: Deepseek-V2 excels in areas like math, code, and reasoning, supporting a 128K context length.

  6. Impressive Performance: Achieving top rankings in AlignBench and MT-Bench, outperforming models like GPT-4.

  7. Fee Structure: Deepseek API offers competitive pricing at $0.14 per million input tokens and $0.28 per million output tokens.

  8. Utilize Free Models: Deepseek provides access to large language models for various tasks like coding and general knowledge.

  9. Explore Similar Tools: Discover related tools like Codestral and HuggingChat for more AI assistance.

By following these steps, you can effectively utilize Deepseek for various tasks ranging from casual chat to coding support, leveraging its powerful AI capabilities.

DeepSeek Pricing and plans

Paid plans start at $0.14/month and include:

  • Top tier performance
  • Large language models
  • AI coding tools
  • AI writers & assistants
  • Free AI tools
  • Chinese performance

DeepSeek FAQs

What are the main models offered by DeepSeek?
DeepSeek offers two main models - DeepSeek Chat and DeepSeek Coder.
Where can DeepSeek models be accessed?
DeepSeek models can be accessed on the official DeepSeek website or run locally with the model checkpoint files.
What type of responses can be expected from DeepSeek Coder?
For questions relating to coding, DeepSeek Coder will provide much better responses than the standard chat.
What is the pricing structure of DeepSeek API?
The pricing is 0.14$ per million input tokens and 0.28$ per million output tokens.

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