DeepSeek is the engine almost nobody works and that, at the same time, is everywhere. It's the AI from the Chinese lab of the same name, founded in 2023, and it carries an oddity none of the big players share: its model is open. Anyone can download it, deploy it or drop it inside their own app — and thousands do. So «showing up in DeepSeek» isn't one surface: it's a model that, per public usage data, had 131.5 million monthly users on its own app in January 2026, and that also runs inside third-party products that aren't even called DeepSeek. It answers in two different ways and reasons before it replies. Each of those changes how you work it. Here's the map.
Why DeepSeek isn't just another engine: it's a model running in a thousand places
Every other engine you've worked is a closed product: ChatGPT lives at OpenAI, Gemini at Google, Grok inside X. DeepSeek doesn't. It published the weights of its reasoning model, R1, under the MIT license — commercial use included — and distilled it into small versions anyone can run on their own server. The consequence for you is huge: you're not optimizing for an app, you're optimizing for a model that replicates. What that model learned about your category travels to every deployment, every fork and every third-party tool that runs it underneath.
Translated to your work: the layer that weighs most in DeepSeek is trained knowledge. If the model knows you as a clear, well-described entity — who you are, what you do, why you're a reference — that signal doesn't show up in one place: it shows up everywhere that model runs. It's the engine with the biggest multiplier of the six.
The two ways DeepSeek answers (and how to get into each)
DeepSeek answers in two ways, and each is worked differently.
- By default, from what it knows. Like ChatGPT, its first deck is the knowledge it learned in training. There's no live link here: either you're in what the model learned, or you're not. You get in by being a recognizable entity corroborated off your own site — press, Wikipedia, forums, reviews — so the model learned you well.
- With search on, from the live web. DeepSeek has a search mode (and the DeepThink reasoning mode) that retrieves fresh results from the internet and cites them. Here you do compete to be retrievable: answer up front, fresh content, sourced data. It's the deck that looks like Perplexity.
Most people only think about the second one. But in DeepSeek the first — trained knowledge — is the one that multiplies across every deployment. Work both.
The model reasons: what an engine that 'thinks' before answering rewards
R1 isn't a model that blurts out the first answer it lands on: it reasons in steps before replying. That changes what content survives. An engine that chains logic discards along the way whatever contradicts itself, whatever asserts without backing, and whatever wraps the idea in three paragraphs of filler. What it rewards is the opposite: a clear claim, the explicit why right behind it, and the proof — a data point, a source, an example — next.
The levers that actually get you into DeepSeek's answers
With the two decks and the reasoning in mind, the game is five things.
- Be a clear, corroborated entity. This is lever number one here, because it feeds the trained layer that replicates across every deployment. Make sure who you are and what you do reads the same on and off your site.
- Answer up front, with data and quotes. Front-load the answer in the first lines of each section and back it. It's what lifts visibility most and what holds up under the model's reasoning.
- Make the logic explicit. Claim, why, proof. An engine that thinks in steps rewards content also built in steps, not content that asks for faith.
- Be retrievable and fresh for search mode. Visible date, updated content, crawl access. The second deck is won like Perplexity's.
- Don't trust your robots.txt. DeepSeek doesn't publish a crawler user agent: its requests look like normal browser traffic. You can't reliably detect or block it by name, so assume that if your content is public, it can read it.
Measure it: 15-25 questions, and a crawler that doesn't announce itself
Like every other engine, DeepSeek gives you no citation dashboard. The method is the usual one: define 15 to 25 questions your customers would ask it, run them once a month — with search on and off, because they're two different decks — and note whether you show up in the text or among the sources. The trend over months is what counts.
And the technical detail worth being clear on: unlike almost everyone else, DeepSeek doesn't document a crawler with its own name. Its fetches show up in your logs as just another browser, so user-agent robots.txt rules don't reach it. You don't block or «allow» DeepSeek with your robots.txt: if your content is public, count on it getting in. Verify real access, not theoretical access.