DeepSeek Complete Guide: The Rise of Open-Source AI Models

In 2024, when GPT-4 and Claude 3 dominated the AI market, a Chinese company quietly emerged, breaking the industry landscape with extremely low costs and an open-source strategy. This is DeepSeek. This article provides a detailed introduction to DeepSeek's two flagship models—V3 and R1—and how to fully leverage them in real-world development.

What is DeepSeek?

DeepSeek was founded in 2023 and is a Chinese company focused on artificial general intelligence. Unlike OpenAI and Anthropic, DeepSeek has adopted an open-source + low-price strategy, allowing developers to access GPT-4-level AI capabilities at extremely low costs.

Two Flagship Models Compared

DeepSeek-V3: General-Purpose Model

V3 is DeepSeek's flagship model with 671B parameters (activating 37B per forward pass), using a MoE (Mixture of Experts) architecture. It's designed for general conversation and task processing.

Key Features:

• Multi-modal capabilities (text, code, reasoning)
• 128K context window
• Strong math and logical reasoning
• Function calling and JSON output support

DeepSeek-R1: Reasoning-Focused Model

R1 is DeepSeek's reasoning model, competing with OpenAI's o1. Trained through reinforcement learning, it excels at complex reasoning tasks.

Key Features:

• Chain-of-Thought display
• Math competition-level problem solving
• Code debugging and algorithm optimization
• Ideal for research and complex analysis tasks

How to Use DeepSeek

1. Official Web Interface

The simplest way is to visit chat.deepseek.com and use the V3 model for free. For R1, click the "Deep Think" mode.

2. API Integration

DeepSeek's API is fully compatible with OpenAI, making migration extremely easy:

import openai

client = openai.OpenAI(
    api_key="your-deepseek-api-key",
    base_url="https://api.deepseek.com"
)

response = client.chat.completions.create(
    model="deepseek-chat",  # V3 model
    messages=[
        {"role": "system", "content": "You are a helpful assistant"},
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)

3. Local Deployment

Since DeepSeek has open-sourced the model weights, you can run it locally using Ollama or vLLM:

# Run DeepSeek-R1 14B with Ollama
ollama run deepseek-r1:14b

# Or deploy with vLLM
python -m vllm.entrypoints.openai.api_server \
    --model deepseek-ai/DeepSeek-V3 \
    --tensor-parallel-size 8

Price Comparison: Why is DeepSeek So Cheap?

DeepSeek-V3 is priced at only 1/70th of GPT-4! This is thanks to its efficient MoE architecture and optimized training methods.

Real-World Use Cases

Use Case 1: Code Generation & Review

DeepSeek excels at coding tasks, particularly suitable for:

• Generating complete functions or classes
• Code refactoring suggestions
• Bug identification and fixes
• Algorithm implementation

Use Case 2: Content Creation

Compared to GPT-4, DeepSeek has advantages in certain contexts:

• Technical documentation writing
• Programming tutorials
• API documentation

Use Case 3: Math & Logical Reasoning

Use the R1 model for:

• Math problem solving
• Logic puzzles
• Data analysis
• Research assistance

Important Notes

• Knowledge Cutoff: V3's knowledge extends to June 2024
• Creative Writing: Slightly behind Claude 3.5 for creative writing
• Multimodal: Currently doesn't support image input (coming soon)
• API Stability: May be slower during peak hours

Conclusion

DeepSeek proves that open-source models can compete with closed-source giants. For budget-conscious developers and SMBs, DeepSeek offers a high-value AI solution.

Whether for daily development, content creation, or complex reasoning, DeepSeek is worth trying. Its performance often exceeds expectations, especially in technical scenarios.