DeepSeek models explained: what they mean for your brand visibility

The DeepSeek model family explained

DeepSeek builds mixture-of-experts models and has released a new one every few months since late 2024. A mixture-of-experts model stores a very large set of parameters but uses only a small part of them for each word it produces, which makes it cheap to run. DeepSeek-V3 came out on December 26, 2024. DeepSeek-R1 followed on January 20, 2025, built on the same base model. R1 uses 37B of 671B parameters for each token.

R1 drew attention well beyond engineering teams. Marc Andreessen, the venture capitalist whose Netscape Navigator helped open the web to the public, posted that "DeepSeek-R1 is AI's Sputnik moment." Through 2025 DeepSeek kept cutting prices. V3.2-Exp dropped the cost of cached input to $0.028 per million tokens, half what the previous model charged.

The current generation began on April 24, 2026, when DeepSeek previewed V4 Pro and V4 Flash. On September 10, 2026, V4.1 Flash replaced V4 Flash. The legacy `deepseek-chat` and `deepseek-reasoner` endpoints shut down on July 24, 2026. If a tool you use still names one of them, find out which model it actually calls now.

V-series vs R-series models

V-series models answer directly. R-series models write out a chain of reasoning first and then give the answer. R1 was trained from the V3 base with extra reinforcement learning, which is training that rewards correct answers. That training made R1 better at maths and code, but it's slower and uses more tokens per reply. From V3.1 onward, a single model can work either way, and V4 offers both modes behind each model ID.

The visible reasoning matters more for brands than the benchmarks do. In thinking mode, DeepSeek shows how it read the question and which considerations it weighed, which BrightEdge described in its DeepThink chain-of-thought walkthrough. You can read that trace to see why a competitor made the shortlist and you didn't.

Which DeepSeek model is best

For research, the best choice is V4 Pro in thinking mode with Search turned on. It's the largest current model, and it can pull in live sources. The other options fit different jobs. Whether the answer depends on recent facts is one of three considerations for your choice. Also consider how much each call costs and where your data is allowed to go.

For research that needs current facts

V4 Pro scores 53 on Artificial Analysis's Intelligence Index, and it can read 1 million tokens of context in one request. That's enough for long reports or several sources side by side. With Search off, even V4 Pro answers only from its training data. So keep Search on for anything where the date matters.

For high-volume or budget work

V4 Flash, and now V4.1 Flash, costs roughly one-twelfth of V4 Pro's input price. It suits classification and summaries. It also suits prompt monitoring that runs thousands of times. You give up some depth on hard reasoning.

For private or self-hosted use

The full R1 needs 160 GB of memory, even in its most compressed 1-bit build. Most teams run the distilled versions instead, which range from 1.5B to 70B parameters and are built on Qwen and Llama. Use V4 Pro with Search when you need answers you can check. Use Flash when volume matters. Use a distilled model only when your data can't leave your servers.

DeepSeek knowledge cutoff

DeepSeek-V3 and R1 know nothing after July 2024. DeepSeek's R1 paper gives a July 2024 cutoff for V3-Base, the checkpoint both models were built from. Researchers at Knostic, an AI security firm, pulled out the chat app's system prompt and found the same date. The prompt read: "Your knowledge cutoff is July 2024."

V4 is different, because DeepSeek has not published a cutoff for V4 Pro or V4 Flash. Some API resellers advertise April 2026 for V4 Pro, but that date doesn't appear in DeepSeek's own material. The gap matters when the model runs without Search. A rebrand or a product launched after the cutoff simply isn't in R1's memory. To check, turn Search off and ask about a recent change your company made. If the model doesn't know about it, its training data ends before that change.

When DeepSeek searches the web

DeepSeek searches the web only when Search is switched on. In the consumer app, you enable Search before sending a prompt. Search works separately from Deep Thinking mode and from the model's trained knowledge. Developers get the same ability through DeepSeek's Search and Fetch API, which includes a localization field for results. That field lets results reflect a chosen region.

Open-weight copies are another story. Open-weight models such as Llama and DeepSeek run without internet access unless the company deploying them adds a search tool. The language of the question changes what gets searched, too. In one FixAEO test, asking a CRM question in Chinese led DeepSeek to read twelve web pages and reply in Chinese. If you sell in more than one language, test in each one.

How DeepSeek cites sources

DeepSeek cites pages its search step has already found and read. A page retrieved and opened for that question gets cited only if it's judged relevant to the answer. Which pages make it into that pool depends on the question's wording and language. The region it's set to also affects the pool. Searched answers can show numbered citations and a count of the pages read.

A citation doesn't promise that every word around it is accurate. FixAEO warns that one citation may back only part of the sentence next to it. DeepSeek's own Terms of Use qualify Search's accuracy improvements with the phrase "to some extent". A page that search can't reach never gets cited, and the DeepSeek Search API finds only public pages. A page that states facts plainly also gives the model a clean sentence to lift. When it's quoted wrong, the error usually starts in a vague or out-of-date line on your own site.

Where open weights are deployed

DeepSeek's weights run in places that never show the DeepSeek name. Microsoft added R1 to Azure AI Foundry, a catalog of over 1,800 models. Amazon Bedrock offers DeepSeek-V3.1 as a hybrid model. Perplexity retrained R1 on thousands of prompts on topics the original avoided and released the result as R1 1776.

Each of these copies is fixed at the moment it was released. It keeps the July 2024 knowledge of its base model unless someone retrains it or connects a search tool. And if a company fine-tunes it, the way it talks about your category can change. So a customer's chatbot built on these weights describes you differently from the DeepSeek app itself.

Where DeepSeek is restricted

Most restrictions on DeepSeek apply to government devices and public-sector work. Consumers can still use it almost everywhere. The main rules in force:

• Italy: the regulator ordered the consumer app removed from app stores.
• Australia: every government entity had to remove DeepSeek products from February 2025, though local open models are exempt when mitigations are in place.
• Taiwan: the ban covers agencies and state-owned enterprises.
• South Korea: ministries blocked the chatbot on government devices in February 2025.
• Czech Republic: state administration has been barred from all DeepSeek products since July 2025.
• United States: a defence law signed on 18 December 2025 bars DeepSeek AI from Defense Department systems and contracts, wherever the model runs.

Where the users are tells you who sees DeepSeek's answers. In August 2026, 51.43% of desktop traffic to deepseek.com came from China. Russia accounted for 8.27% and the US for 5.86%. If you sell to government buyers, DeepSeek barely reaches them. If you sell into Chinese-speaking markets, it's a main channel.

What brands should audit now

Brands should check DeepSeek's memory and its search results separately, because they fail in different ways. A wrong answer with Search off comes from old training data. A wrong answer with Search on points to a page on the web. Check these:

• Your core prompts, run with Search off and then on
• The same prompts in every language you sell in
• Facts that have changed since July 2024, such as names and prices; check product lines too
• Whether crawlers can reach your key pages without a login
• The reasoning trace, for why a competitor was picked over you
• Answers from partner tools built on DeepSeek weights

Run these checks every time DeepSeek releases a new model. V4 Flash was generally available for only six weeks before V4.1 Flash replaced it.

When this matters for you

If your buyers are in China or Russia, or the tools they use run on open weights, add DeepSeek to the AI assistants you already monitor. Use two test schedules, with a recheck after every DeepSeek release because a new model can change answers overnight. Then keep running the same prompts in between, because Search results move even when the model stays the same. Correct your pages for the retrieval errors, and expect the memory errors to last until the next model.

Snoika audits websites and tracks brand visibility in Google and AI assistants. Its team adds human review to the results. To see what DeepSeek models and other assistants say about your brand, get a free AI visibility report.