DeepSeek
Definition
DeepSeek is a Chinese AI lab known for the DeepSeek V3 model and the R1 reasoning model. Its models use a mixture-of-experts architecture, are released under permissive MIT licensing, and are positioned as competitive with frontier systems while emphasizing strong performance at lower training and inference cost.
Overview
DeepSeek develops large language models with a focus on efficiency and openness. Its DeepSeek V3 is a general-purpose model, while R1 is a reasoning model that works through problems step by step before answering, targeting strong performance on math, coding, and complex tasks.
A defining trait of DeepSeek's models is the mixture-of-experts (MoE) architecture, which activates only a subset of the model's parameters per token. This lets the models reach high capability while keeping inference cost lower than dense models of comparable size.
DeepSeek releases models under the permissive MIT license, making them attractive for self-hosting, fine-tuning, and building derivative systems. This open posture has made DeepSeek a notable reference point in the open-source LLM landscape.
Why it matters for AI visibility
DeepSeek's open, low-cost models lower the barrier to building AI products, which means more assistants and search tools may be powered by DeepSeek-derived models. As those products ground answers in web content, the same GEO principles apply — accessible, authoritative content is more likely to be surfaced.
For teams evaluating which models to build on or optimize for, DeepSeek's permissive licensing and efficient architecture make it a common choice, so understanding its behavior helps anticipate where and how a brand might be cited in AI answers.
Frequently asked questions
What is DeepSeek?
DeepSeek is a Chinese AI lab known for the DeepSeek V3 model and the R1 reasoning model. Its models use a mixture-of-experts architecture and are released under the permissive MIT license.
What is the DeepSeek R1 model?
DeepSeek R1 is a reasoning model that works through problems step by step before answering, aiming for strong performance on math, coding, and complex multi-step tasks while remaining openly licensed.
Why is DeepSeek considered cost-efficient?
DeepSeek's models use a mixture-of-experts architecture that activates only part of the model per token, reaching high capability with lower inference cost than comparably sized dense models. Efficient training methods also help reduce overall cost.
Are DeepSeek models open source?
DeepSeek releases models under the permissive MIT license, which allows self-hosting, fine-tuning, and building derivative systems. This makes it a notable option in the open-source LLM ecosystem.
Open source LLMs
Open source LLMs are large language models whose weights are publicly available for download, allowing anyone to self-host, fine-tune, and inspect them. Families such as Llama, Mistral, Qwen, and DeepSeek give organizations control over deployment, customization, and data privacy, in contrast to closed models accessible only through a provider's API.
Reasoning models
Reasoning models are language models trained to solve complex problems by thinking step by step before answering, spending extra computation at inference to work through a problem rather than responding immediately. Examples include OpenAI's o-series, DeepSeek-R1, and reasoning-tier Gemini and Claude modes. The approach trades latency and cost for stronger performance on math, coding, science, and multi-step planning.
Large language model (LLM)
A large language model is an AI system trained on vast amounts of text to understand and generate human language. Built on transformer architecture and containing billions of parameters, LLMs predict the next token in a sequence, enabling them to answer questions, write, summarize, and reason. They power modern chat assistants, AI search, and autonomous agents.
AI fine-tuning
AI fine-tuning is the process of taking a pre-trained model and training it further on a smaller, specialized dataset so it adapts to a specific task, domain, tone, or format. It adjusts the model's existing weights rather than training from scratch, producing outputs that better match a brand's requirements or a narrow use case at lower cost than full training.
Foundation models
Foundation models are large-scale AI models trained on broad, diverse data that serve as a general-purpose base adapted for many downstream applications. Rather than building a model per task, organizations fine-tune or prompt a single foundation model for translation, summarization, coding, search, and more. Large language models and multimodal models are common examples.
OpenAI
OpenAI is an AI research and deployment company best known for ChatGPT, the GPT family of large language models, the o-series reasoning models, and the DALL·E image models. It operates a widely used consumer assistant alongside an API and enterprise products, making it a dominant force in both consumer and business AI.