Skip to main content
Crowdfunding
Python + AI for Geeks
Practice

Comparison of GPT, Claude, and DeepSeek Models

With the release of various AI language models, strong contenders such as Anthropic's Claude and DeepSeek AI's DeepSeek are gaining attention alongside GPT.

In this session, we will compare the features of these three models and examine which situations are most suitable for each.


GPT (OpenAI)​

GPT is a prominent language model developed by OpenAI, and it is currently the most widely used model.

Features​

  • Evolved through various versions (GPT-3.5, GPT-4, GPT-4o), combining versatility with performance.
  • Capable of carrying out diverse linguistic tasks based on large-scale pre-trained data.
  • Widely utilized in real-world services like ChatGPT, Copilot, etc.

Advantages​

  • Natural conversation and sentence construction capabilities.
  • Versatile use in coding, summarization, translation, etc.
  • Includes multimodal capabilities (as of GPT-4o).

Disadvantages​

  • High usage cost for high-performance models (like GPT-4) compared to other models.

Claude (Anthropic)​

Claude, developed by Anthropic, is designed with a focus on ethical safety and long context processing.

It is generally evaluated as a suitable model for tasks that require long context, such as coding and documentation.

Features​

  • The latest version (Claude 3) naturally handles long inputs over 200K tokens.
  • Clearly understands user intent, with fewer cases of excessive imagination or fiction generation.

Advantages​

  • Excellent understanding of long-term context (suitable for document analysis, paper summarization, etc.).
  • Consistently stable and cautious responses.

Disadvantages​

  • Responses may appear conservative and monotonous.
  • May lack expressiveness in certain applications (e.g., creative writing).

DeepSeek (DeepSeek AI)​

DeepSeek is an open-source high-performance language model developed by the namesake Chinese company, specializing in coding tasks and logical reasoning.

Features​

  • Various purpose-specific models released, such as DeepSeek-Coder, DeepSeek-VL, etc.
  • Outstanding performance in code generation, document summarization, numerical calculation, etc.

Advantages​

  • Comparable or superior results to GPT in code writing capability.
  • Open-source availability (beneficial for developers).

Disadvantages​

  • May be sensitive to political or cultural issues.
  • Requires further validation concerning the diversity of training data.

Each model has clear strengths, so it's important to choose the appropriate model according to the intended use and context.

In the next session, we will tackle a simple quiz based on what we've learned today.

Want to learn more?

Join CodeFriends Plus membership or enroll in a course to start your journey.