Is DeepSeek free to use?

DeepSeek offers free access to its chat interface at chat.deepseek.com with daily usage limits. Its models are also open-source, meaning developers can download and run them on their own infrastructure at no licensing cost. API access is available at significantly lower prices than OpenAI or Anthropic - roughly 90% cheaper for comparable model capabilities.

How did DeepSeek train models so cheaply?

DeepSeek used innovative training techniques including mixture-of-experts architecture, efficient attention mechanisms, and multi-token prediction. DeepSeek-V3 was reportedly trained for approximately $5.6 million in compute costs - a fraction of the hundreds of millions spent on comparable Western models. These efficiency gains have reshaped industry assumptions about AI training costs.

Does DeepSeek have web search capabilities?

DeepSeek's chat interface includes a search function that can retrieve web results, though it is more limited than Perplexity or ChatGPT Search. The search capability is primarily focused on Chinese-language sources but can access English-language content. For AI search optimization, DeepSeek matters more as a growing platform than as a current primary search tool.

What Is DeepSeek AI?

DeepSeek is a Chinese artificial intelligence research lab that has disrupted the AI industry by building language models that match or approach the performance of leading Western AI systems at a fraction of the training cost. Founded in 2023 and backed by the Chinese quantitative trading firm High-Flyer, DeepSeek gained global attention in January 2025 when its DeepSeek-R1 reasoning model demonstrated performance comparable to OpenAI's o1 model. The DeepSeek app briefly became the most downloaded free app on the US App Store, and the announcement temporarily wiped nearly $1 trillion from US tech stock valuations as markets reassessed AI infrastructure spending assumptions.

How Does DeepSeek Build Its Models?

DeepSeek's approach challenges the prevailing assumption that training frontier AI models requires billions of dollars in compute:

Mixture-of-Experts (MoE) architecture. DeepSeek-V3, its flagship base model, uses a mixture-of-experts approach where only a subset of the model's parameters are activated for each input. The model has 671 billion total parameters but activates approximately 37 billion per query, dramatically reducing compute requirements while maintaining performance.

Efficient training. DeepSeek reported that DeepSeek-V3 was trained using approximately 2,788,000 GPU hours on Nvidia H800 chips, costing roughly $5.6 million in compute. For comparison, Meta's Llama 3.1 (405B) required an estimated 30 million GPU hours. This efficiency gap sent shockwaves through the AI industry.

Multi-token prediction. Instead of predicting one token at a time, DeepSeek trains its models to predict multiple future tokens simultaneously. This improves both training efficiency and inference speed.

Open-source release. DeepSeek publishes its model weights and technical papers openly, allowing the research community to study, replicate, and build on its work. This open approach has accelerated AI development globally.

What Are DeepSeek's Key Models?

DeepSeek-V3: The flagship base model with 671B parameters (37B active). Competitive with GPT-4 on many benchmarks at a fraction of the cost.
DeepSeek-R1: A reasoning model that uses chain-of-thought processing to solve complex math, coding, and logic problems. Comparable to OpenAI's o1.
DeepSeek Coder: Specialized for code generation and programming tasks.
DeepSeek-VL: A vision-language model that can process and reason about images.

Why Does DeepSeek Matter for AI Search and GEO?

Expanding the AI Search Landscape

DeepSeek adds another AI platform where users seek information. While its search capabilities are currently more limited than Perplexity or ChatGPT, the platform's massive user growth means it is an emerging surface for content visibility. Our AI search engines comparison covers how DeepSeek fits into the broader landscape.

Cost Disruption

DeepSeek's efficiency breakthroughs make AI more accessible. Smaller companies and startups can now run powerful AI models on modest infrastructure. This democratization of AI capability means more products and services will integrate AI-powered search and content retrieval - expanding the total surface area where your content needs to be visible.

Open-Source Ecosystem

Because DeepSeek's models are open-source, they power hundreds of derivative applications and research projects. Content that is well-optimized for AI extraction will perform well across any application built on DeepSeek models, not just DeepSeek's own chat interface.

What Are DeepSeek's Limitations?

Data privacy concerns. DeepSeek stores user data on servers in China, subject to Chinese data laws. This has raised concerns among Western businesses and government agencies. Several countries and organizations have restricted or banned DeepSeek use for sensitive work.

Search limitations. DeepSeek's web search is less comprehensive than Google-powered (Gemini) or Bing-powered (ChatGPT) alternatives. For English-language queries, the search results may be less thorough.

Censorship. DeepSeek applies content filters aligned with Chinese regulatory requirements. Certain political and sensitive topics receive filtered or restricted responses, which limits the platform's utility for some research use cases.

Availability. Access to DeepSeek services has occasionally been disrupted by high demand and infrastructure challenges, particularly during peak usage periods following major releases.

For startups building their AI search optimization strategy, DeepSeek represents the broader trend of AI search fragmenting across multiple platforms. The playbook remains the same - structured, authoritative content optimized for machine extraction - but the number of platforms where that content needs to perform continues to grow.