What Is DeepSeek? The Open-Source AI Challenging GPT and Claude

DeepSeek is a Chinese AI research company that became one of the most talked-about names in artificial intelligence after releasing models that matched — and in some cases exceeded — the performance of OpenAI and Anthropic's best, at a dramatically lower cost. Founded in 2023 and based in Hangzhou, DeepSeek has taken an approach rare among frontier AI labs: open-sourcing everything under the MIT License, giving developers, researchers, and businesses free access to world-class AI.

This guide covers what DeepSeek is, the company behind it, its key models, how it compares to competitors, and how you can start using it today — including through Chat Smith, which gives you access to DeepSeek models alongside GPT, Claude, and Gemini in one place.

DeepSeek is an AI research lab that builds and open-sources large language models (LLMs). It was founded in 2023 by Liang Wenfeng, who previously co-founded High-Flyer, one of China's most successful quantitative hedge funds. Unlike most AI labs that monetize through proprietary APIs or subscriptions, DeepSeek's stated mission is to advance Artificial General Intelligence (AGI) by making its research freely available to everyone.

The company first gained international attention in January 2025 when it released DeepSeek R1 — a reasoning model that matched OpenAI o1 on major benchmarks while costing roughly 97% less to train. The DeepSeek app surged to the top of the Apple App Store in the United States, briefly overtaking ChatGPT, and triggered a notable sell-off in U.S. tech stocks as investors reconsidered assumptions about AI infrastructure costs.

DeepSeek is not a consumer product company in the traditional sense. Its primary focus is research and model development. The chat interface at chat.deepseek.com is a showcase for the models, not the main business. The main output is the models themselves — released publicly for anyone to download, run, and build on.

DeepSeek maintains several model families, each targeting a different type of task. Here is a practical overview of the main ones:

The V-series models are DeepSeek's general-purpose line — capable, fast, and designed for everyday tasks like writing, coding, summarization, and Q&A. The current flagship is DeepSeek V4 Pro, released in April 2026 with 1.6 trillion total parameters and support for 128K context. It excels at instruction-following, tool use, and complex analytical writing.

For speed-critical workloads, DeepSeek V4 Flash offers a lighter, faster variant of the same generation — ideal for high-volume applications where latency matters more than maximum depth.

The R-series are DeepSeek's reasoning-specialist models, trained with reinforcement learning to think through complex problems step by step before answering. The current best option is DeepSeek Reasoner v3.2. For background on the original reasoning breakthrough, see our deep dive on DeepSeek R1.

A code-specialized series trained extensively on source code repositories across dozens of programming languages. DeepSeek-Coder models are widely used in developer tools, IDE plugins, and code review workflows — competitive with GitHub Copilot and CodeLlama on most coding benchmarks.

DeepSeek's models use a Mixture of Experts (MoE) architecture, which divides the model into many specialized sub-networks called "experts." Only a small subset of these experts activates for any given input, keeping inference costs low even as total parameter counts grow very large. For example, DeepSeek R1 has 671 billion total parameters but only activates 37 billion per inference pass — making it far more efficient than a dense model of similar size.

What set DeepSeek apart technically is its use of reinforcement learning (RL) to teach models to reason — rather than relying primarily on large amounts of human-annotated chain-of-thought data. The R-series models use a technique called Group Relative Policy Optimization (GRPO), which lets the model discover effective reasoning strategies through trial and reward. This approach is both more scalable and cheaper than supervised fine-tuning at scale.

All major DeepSeek models are released under the MIT License — the most permissive open-source license available. This means you can download the model weights, run them locally, fine-tune them for specific use cases, and build commercial products on top of them without paying licensing fees or seeking approval from DeepSeek. This is in sharp contrast to GPT-4o, Claude, or Gemini, which are proprietary and only accessible through paid APIs.

The AI industry had largely operated on an assumption: frontier performance requires hundreds of millions of dollars in compute, which means only a handful of well-funded US labs can compete at the top. DeepSeek broke that assumption. DeepSeek R1 was reportedly trained for under $6 million — compared to GPT-4's estimated training cost of over $100 million. And it matched or exceeded o1 on benchmarks like MATH-500 and AIME 2024.

This efficiency gap has significant implications. It means: smaller companies and researchers can train competitive AI models without massive budgets; inference costs fall dramatically, making AI more affordable for end users and developers; and the assumption that proprietary, closed models are inherently better than open ones has been challenged.

In June 2026, DeepSeek raised $7.5 billion in its first-ever funding round, valuing the company at approximately $58.9 billion — confirming that the broader market sees it as a long-term force in AI.

DeepSeek is often compared directly to OpenAI and Anthropic. Here is a practical breakdown across the dimensions that matter most:

For organizations with data sovereignty concerns, DeepSeek's self-hosting option is a meaningful advantage — you can run the model on your own infrastructure, with no data leaving your servers. For users who want the most polished conversational experience or strong multimodal capabilities, Claude Sonnet 4.6 or GPT-5 remain strong alternatives.

DeepSeek models are general-purpose enough to handle most AI tasks, with particular strength in technical domains:

• Mathematics and science: DeepSeek R1 scores among the highest of any model on competition math benchmarks. Pair it with an AI math solver for step-by-step problem solving.
• Coding and debugging: DeepSeek-Coder and the V-series models are among the strongest available for code generation, debugging, and explanation across Python, JavaScript, Go, Rust, and more.
• Document analysis: With a 128K context window, DeepSeek V4 Pro can process long research papers, contracts, and reports. Use an AI PDF summarizer for even faster extraction.
• Content creation: For writing articles, emails, and social copy, the V-series handles natural language tasks well. Combine it with an AI blog writer workflow for higher throughput.
• Research and education: DeepSeek's transparent reasoning traces (where the model shows its thinking) make it useful for learning, tutoring, and research workflows where you need to verify the logic, not just the answer.

There are four main ways to access DeepSeek:

• DeepSeek chat (chat.deepseek.com): Free web interface. Switch on "DeepThink" for R1-style step-by-step reasoning. Good for personal use but has had intermittent availability issues due to high demand.
• DeepSeek API (platform.deepseek.com): OpenAI-compatible API for developers. Current model IDs are deepseek-v4-pro and deepseek-v4-flash. Very low cost per token.
• Self-hosting: Download weights from Hugging Face and run locally via Ollama or LM Studio. Smaller distilled models (7B–14B) run on consumer GPUs. Full 671B models require serious infrastructure.
• Chat Smith: Access all DeepSeek models alongside GPT, Claude, and Gemini in one app — no API key setup required. Browse the full AI model library and switch between models in a single conversation.

This is a legitimate question. DeepSeek's privacy policy states it may collect prompts, chat history, uploaded files, and device/network data, and that personal data may be stored on servers in China — subject to Chinese data law. For personal use, casual questions, and general research, this is likely a non-issue for most users. For enterprise use involving sensitive business data, legal documents, or proprietary code, it deserves serious consideration.

The self-hosting option addresses this entirely: run DeepSeek on your own servers, and no data ever reaches DeepSeek's infrastructure. For organizations with strict data governance requirements, this is the recommended approach.

Chat Smith gives you access to DeepSeek V4 Pro, V4 Flash, and other DeepSeek models alongside the world's other top AI models — all in one free app. You don't need a DeepSeek account, an API key, or any technical setup. Just open Chat Smith, pick your model, and start.

This is particularly useful when you want to compare DeepSeek against other models on the same task — for example, asking the same coding question to DeepSeek V4 Pro and Claude Sonnet 4.6 side by side. Having everything in one interface makes switching fast and friction-free.

DeepSeek is one of the most consequential developments in AI in recent years — not because it is the most powerful model in every benchmark, but because it proved that frontier-level AI can be built and shared openly, at a cost that challenges the economics of the entire industry. Whether you're a developer, researcher, student, or business user, there's a DeepSeek model worth trying.

The easiest way to get started is through Chat Smith — all DeepSeek models, alongside GPT-5, Claude, and Gemini, in one free app with no setup required.

1. Is DeepSeek free to use?

Yes. DeepSeek's model weights are open-source under the MIT License, meaning anyone can download and run them for free. The chat.deepseek.com interface is also free. API usage is available at low cost through DeepSeek's platform and third-party providers. If you access DeepSeek through Chat Smith, you can use it within Chat Smith's free tier.

2. Is DeepSeek better than ChatGPT?

It depends on the task. DeepSeek R1 matches or beats OpenAI o1 on math and coding benchmarks, while being significantly cheaper. For everyday conversational tasks, image generation, or tasks requiring real-time web access, ChatGPT's broader feature set may serve better. For pure text reasoning at low cost, DeepSeek is highly competitive.

3. Who made DeepSeek and where is it based?

DeepSeek was founded in 2023 by Liang Wenfeng, who previously co-founded High-Flyer, a major Chinese quantitative hedge fund. The company is headquartered in Hangzhou, China. It operates as an independent AI research lab, not as a subsidiary of any of China's large tech companies such as Alibaba, Tencent, or Baidu.