# DeepSeek

Published 2025-05-06

Positioning and Usage:

This is the version used for dialogue applications on the DeepSeek platform, mainly for real-time chat and information exchange.

Features and Advantages:

Efficient Dialogue Generation: The model is based on the DeepSeek-V3 architecture, supporting long contexts (such as 64K tokens), capable of handling complex multi-turn conversations.
Open Interface: Users can use it for free without registration, and the interface is user-friendly, suitable for daily communication and routine queries.
Resource Conservation and Cost Advantages: Compared to some Western models, DeepSeek-chat has significant advantages in computational resources and usage costs.
Privacy and Data Policy: Currently, DeepSeek-chat's data is stored in China, which has certain controversies, but its open-source nature provides high technical transparency, facilitating researcher review.

Positioning and Usage:

Focuses on complex problem-solving and logical reasoning, serving as the reasoning model of the DeepSeek platform.

Features and Advantages:

Chain-of-Thought: Before generating a final answer, the model outputs a detailed reasoning process (CoT), allowing users to see the model's "thinking" process, increasing trust and explainability.
Reinforcement Learning Training: The model is primarily trained through reinforcement learning (RL), naturally exhibiting self-verification and reflection behaviors, applicable to tasks such as mathematics, coding, and logical reasoning.
Output Consistency and Controllability: Provides access to generated reasoning content (reasoning_content) in the API, facilitating user understanding and debugging of the model's decision-making process.
Long Context and Efficient Reasoning: Supports inputs with contexts up to 64K, maintaining high accuracy in complex tasks while reducing computational costs through optimization strategies.