DeepSeek

AI Glossary

DeepSeek is a Chinese AI lab that builds large language models — and their work has been making waves because they’re producing results that rival the big names in the US, often at a fraction of the cost.

What it really means

DeepSeek is a research lab based in China that builds what are called “open-weights” AI models. That means they publish the actual trained model files — the weights — so anyone can download them, run them on their own hardware, and even fine-tune them for specific tasks. This is different from companies like OpenAI or Anthropic, which keep their models behind paid APIs and don’t let you peek under the hood.

The reason DeepSeek has gotten so much attention is simple: their models score competitively on benchmarks against GPT-4, Claude, and other top-tier models, but they cost far less to run. Some estimates suggest DeepSeek’s latest models can be 10 to 50 times cheaper per query than comparable US models. For a small business owner in Orlando, that could mean the difference between an AI tool that’s affordable and one that’s not.

I’ve been watching DeepSeek since their V2 release in early 2024, and what stands out to me isn’t just the price — it’s that they’re innovating on architecture. Their models use a “mixture of experts” design, which means only parts of the model activate for any given query. That’s how they keep costs low without sacrificing quality. It’s smart engineering, not just a race to the bottom on pricing.

Where it shows up

You won’t find DeepSeek as a consumer product like ChatGPT or Claude.ai. They don’t have a polished app or a marketing team. Instead, DeepSeek shows up in two main places:

• Open-source model repositories — sites like Hugging Face where developers download model files. DeepSeek’s models are some of the most downloaded there.
• Third-party tools and platforms — companies build products on top of DeepSeek’s models, often without advertising that fact. If you’re using an AI writing assistant or a code generator that seems surprisingly cheap, there’s a chance it’s running on DeepSeek under the hood.

DeepSeek also offers a paid API, but it’s aimed at developers, not end users. If you’re a business owner who wants to use DeepSeek, you’d typically work with a consultant or developer to integrate it into your existing software.

Common SMB use cases

For small and mid-market businesses in Central Florida, DeepSeek’s models are most useful in scenarios where cost matters and you don’t need the absolute highest accuracy. Here’s where I’ve seen them work well:

• Customer service chatbots — A Maitland HVAC company could run a DeepSeek-powered chatbot on their own server for a few dollars a month, handling common questions about appointment scheduling and pricing.
• Internal knowledge base search — A Winter Park dental practice could use DeepSeek to let staff search through patient records and treatment protocols without paying per-query fees.
• Drafting emails and documents — A downtown Orlando law firm might use DeepSeek to generate first drafts of routine correspondence, then have a paralegal review and edit. The cost savings add up fast when you’re sending hundreds of emails a week.
• Data extraction from PDFs — A Lake Nona restaurant could use DeepSeek to pull order data from scanned invoices, saving hours of manual data entry.

The key is that DeepSeek is good enough for many business tasks — not perfect, but good enough at a price that makes it practical to use for high-volume, low-stakes work.

Pitfalls (what gets oversold)

Let me be direct about what DeepSeek isn’t. First, it’s not a replacement for OpenAI or Anthropic in every scenario. DeepSeek’s models can struggle with nuanced reasoning, complex instructions, and tasks that require up-to-date knowledge (their training data has a cutoff). If you’re building a tool that needs to give legal advice or medical diagnoses, you should not use DeepSeek.

Second, “open-weights” doesn’t mean “free to use commercially without restrictions.” DeepSeek’s models come with a license that may limit how you can use them in a business context. I’ve seen small business owners assume open-weights means no strings attached, and that can lead to compliance headaches later.

Third, there’s the geopolitical angle. DeepSeek is a Chinese company, and their models are subject to Chinese regulations. That raises questions about data privacy and security — especially if you’re handling customer information. I always advise clients to run DeepSeek models on their own infrastructure, not through a third-party API, if they’re dealing with sensitive data.

Finally, the hype around DeepSeek’s low cost sometimes overshadows the fact that you need technical skills to use it effectively. This isn’t a plug-and-play product. You’ll likely need a developer or a consultant like me to set it up properly.

Related terms

• Open-weights model — A model where the trained parameters are published, allowing anyone to download and run it. DeepSeek is one of the most prominent open-weights labs.
• Mixture of experts (MoE) — The architecture DeepSeek uses, where only relevant parts of the model activate per query. This is why their costs are low.
• Fine-tuning — The process of taking a pre-trained model like DeepSeek and training it further on your own data. This is how you adapt it for specific business tasks.
• Inference cost — The cost of running a model to generate a response. DeepSeek’s main selling point is dramatically lower inference costs compared to closed models.
• Closed model — Models like GPT-4 or Claude that are only accessible through paid APIs and can’t be downloaded or inspected. The opposite of DeepSeek’s approach.