DeepSeek is a Chinese artificial intelligence company that develops open-weight large language models (LLMs). For marketers and SEO professionals, it represents a cost-effective alternative to proprietary models, offering high-performance reasoning and coding capabilities at a fraction of the traditional computational cost.
What is DeepSeek?
Founded on July 17, 2023, DeepSeek is technically known as Hangzhou DeepSeek Artificial Intelligence Basic Technology Research Co., Ltd. The company is owned and funded by the Chinese hedge fund High-Flyer, which transitioned from traditional stock trading to AI-driven algorithms in late 2017.
DeepSeek focuses on researching general artificial intelligence (AGI) and releases most of its models under the MIT License. Unlike companies that focus exclusively on consumer products, DeepSeek emphasizes foundational research and efficiency, employing approximately 160 employees as of 2025.
Why DeepSeek matters
DeepSeek has shifted the AI industry's focus from massive hardware spending to algorithmic efficiency. This has direct implications for marketing technology costs and the accessibility of high-tier AI for smaller agencies.
- Drastic cost reduction: The company trained its V3 model for US$6 million, which is significantly lower than the US$100 million estimated for OpenAI’s GPT-4.
- Lower hardware requirements: DeepSeek uses approximately one tenth of the computing power consumed by Meta’s Llama 3.1, making it more sustainable for local deployments.
- Market disruption: Following the release of its R1 model, DeepSeek triggered a US$600 billion drop in Nvidia's market value, the largest single-day decline in U.S. stock market history.
- Accessible intelligence: In early 2025, DeepSeek surpassed ChatGPT as the most downloaded freeware app on the iOS App Store in the United States.
How DeepSeek works
DeepSeek uses a combination of proprietary architectural innovations and custom-built hardware clusters.
Architectural Innovations
The company utilizes a variant of the Mixture of Experts (MoE) architecture. This system activates only a small portion of the model’s total parameters for any given task, which keeps processing speeds high and costs low.
Key components include: 1. Multi-head Latent Attention (MLA): This mechanism reduces the KV (key-value) cache size, significantly lowering memory usage during generation. 2. DeepSeek Sparse Attention (DSA): Optimized for long-context scenarios, this reduces computational complexity while maintaining performance. 3. Group Relative Policy Optimization (GRPO): A reinforcement learning variant that improves reasoning without needing a separate, massive reward model.
Infrastructure
DeepSeek operates custom computing clusters called Fire-Flyer. The Fire-Flyer 2 cluster utilized 5,000 Nvidia A100 GPUs and a custom distributed parallel file system known as 3FS, designed for high-speed asynchronous data reads.
Types of DeepSeek models
| Series | Purpose | Notable Feature |
|---|---|---|
| DeepSeek-V3 | General LLM | Trained on 14.8 trillion tokens with mixed-precision arithmetic. |
| DeepSeek-R1 | Reasoning | Optimized for logical tasks, math, and coding through reinforcement learning. |
| DeepSeek-Coder | Programming | Specifically trained on source code and code-related English/Chinese. |
| DeepSeek-Math | Mathematics | Uses a process reward model (PRM) to solve complex equations. |
Best practices
- Adjust sampling parameters: For local deployment of DeepSeek-V3.2, set the temperature to 1.0 and top_p to 0.95.
- Use the correct model for the task: Select the "Speciale" variants for deep reasoning, but note that they do not support tool-calling functionality.
- Leverage thinking tags: Use the
<think>and<answer>tags when working with the R1 series to help the model structure its logical progression. - Utilize the official API: If you require high availability, use the API rather than the free app, as the app may experience login issues during peak traffic or cyberattacks.
Common mistakes
Mistake: Using DeepSeek-R1 for simple, non-reasoning tasks. Fix: Use the V-series (like V2.5 or V3) for creative writing or general Q&A to avoid "overthinking" and excessive output lengths.
Mistake: Expecting Western-centric ideological neutrality. Fix: Be aware that recent models like R1-0528 more tightly follow Chinese Communist Party ideology and censorship guidelines.
Mistake: Assuming all models are fully open source. Fix: Treat them as "open weight." You have access to the parameters, but must follow the DeepSeek License regarding downstream usage.
Examples
- Scenario (Mathematical Excellence): DeepSeek-V3.2 achieved gold-medal performance in the 2025 International Mathematical Olympiad (IMO) and International Olympiad in Informatics (IOI).
- Scenario (Coding): Developers use DeepSeek-Coder to generate and debug scripts, as the model was trained on a 1.8 trillion token dataset consisting of 87% source code.
- Scenario (Cost Optimization): A marketing agency switching from GPT-4 to DeepSeek-V2 for internal tools, benefiting from a price point of 2 RMB for every million output tokens.
DeepSeek vs. OpenAI o1
| Feature | DeepSeek-R1 | OpenAI o1 |
|---|---|---|
| Accessibility | Open-weight (MIT License) | Restricted API/Web |
| Training Cost | Comparatively low (US$6M for V3) | Estimated US$100M+ |
| Reasoning Approach | GRPO Reinforcement Learning | Proprietary reasoning chain |
| Performance | Comparable on AIME and MATH | Faster on some specific AIME problems |
| Availability | Free App and API | Subscription-based and Tiered API |
FAQ
Is DeepSeek free to use? The DeepSeek chatbot is available for free on iOS and Android. Additionally, many of the model weights are released under the MIT License for local download and use without licensing fees.
How does DeepSeek train models so cheaply? The company uses algorithmic efficiencies like Multi-head Latent Attention (MLA) and Mixture of Experts (MoE) to reduce the number of active parameters. They also perform extensive low-level engineering to maximize their existing GPU clusters, avoiding the need for the absolute latest hardware.
Can I use DeepSeek for commercial SEO tools? Yes, DeepSeek models are available via API for integration into third-party applications. Their open-weight nature also allows developers to host the models on their own infrastructure, provided they comply with the specific license terms.
Does DeepSeek support languages other than English and Chinese? Yes. DeepSeek-V3 and later models are trained on multilingual corpora. The official app supports 72 languages, including French, German, Japanese, and Spanish.
What is the "Sputnik Moment" referring to? This is a term used by industry observers to describe how DeepSeek's high-performance, low-cost models shocked Western tech companies. It suggested that China could achieve AI breakthroughs without relying on the massive hardware resources typically used by Silicon Valley.
