What it is: DeepSeek is a Chinese AI lab whose open-weight models reached frontier-level performance at dramatically lower training costs. Their DeepSeek-R1 release in early 2025 shocked the industry and shifted expectations about what training a top model actually requires.
Who it is for: Developers, researchers, and anyone following the geopolitics + economics of frontier AI.
Best if: You want to understand why “China caught up faster than expected” was the AI story of 2025.
Skip if: You’re a casual user — DeepSeek’s chat product is fine, but you won’t notice meaningful differences from ChatGPT or Claude for everyday tasks. Want one practical AI workflow every morning? Subscribe to our free daily newsletter.
What is DeepSeek?
DeepSeek is an AI lab based in Hangzhou, China, founded in 2023 by High-Flyer (a Chinese hedge fund). It became globally famous in January 2025 when it released DeepSeek-R1, an open-weight reasoning model that matched OpenAI‘s o1 on key benchmarks while reportedly costing a small fraction to train.
Why does DeepSeek matter?
That release reshaped the AI industry’s economic assumptions almost overnight. If frontier-level capability could be achieved without billion-dollar training runs, the moat that US labs had assumed they were building looked thinner. DeepSeek-R1’s release contributed to a roughly $1 trillion drop in US AI-related stocks in the days that followed.
The company has continued releasing competitive models (DeepSeek-V3, R2) throughout 2025 and 2026. For developers wanting capable AI without paying OpenAI or Anthropic per-token rates, DeepSeek is one of the leading alternatives. The geopolitical dimension is real too — DeepSeek demonstrated that frontier AI is no longer a US-only club.
How do you use DeepSeek?
DeepSeek’s models are open-weight and available three ways:
- DeepSeek Chat (chat.deepseek.com) — the consumer chatbot, free with high usage limits.
- DeepSeek API — production access at fraction of OpenAI/Anthropic cost.
- Self-hosted — download from Hugging Face and run with Ollama, vLLM, or other inference engines. Note: the full models are large and need real hardware.
Related terms
Learn more on Beginners in AI
Sources and further reading
Last reviewed: May 2026. AI terminology evolves quickly — verify specifics on the official source pages above.
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