DeepSeek complete usage tutorial, 2026 domestic AI assistant from download to advanced gameplay

A Complete DeepSeek Tutorial: The 2026 Guide to the Homegrown AI Assistant, from Download to Advanced Play

Over the past year, if you follow homegrown Chinese AI, there is one name that is nearly impossible to avoid: DeepSeek. This company, called DeepSeek (Hangzhou DeepSeek), has been adopted by many developers and ordinary users as their daily go-to assistant thanks to its continuous open-sourcing, strong reasoning ability, and API pricing renowned as low among Chinese models. Quite a few people were a bit hesitant when they first heard of DeepSeek, wondering whether a homegrown model could only hold its own in Chinese scenarios; after actually trying it, they found its performance in Chinese-English, code, and math reasoning is not bad at all, and on some tasks even pleasantly surprising. This article walks through the entire usage flow from registration to advanced play, catering both to complete beginners and to existing users who can pick up a few tricks they may not know. The content below is written based on the product form publicly available as of this writing; version numbers and specific capabilities will change with official iterations, so refer to the official documentation.

What Is DeepSeek, and Why Do Chinese Developers All Use It?

DeepSeek is a Chinese company focused on developing general-purpose large models, with product forms including a conversational assistant for ordinary users and an API for developers, while also releasing its model weights in open-source form on platforms like Hugging Face. Unlike many vendors that only do closed-source services, DeepSeek chose to run a dual track of open-sourcing plus self-developed services, which is quite friendly to the developer community, because open weights mean it can be deployed locally or in a private cloud, and data does not have to pass through external services. The model's performance in Chinese scenarios has long been widely recognized in the industry, and on English and code tasks it also approaches mainstream levels; according to public reports, on some reasoning tasks it approaches top closed-source model levels. The reasons Chinese developers are willing to use DeepSeek can be summed up in a few points: the model results are good enough, the API price is renowned as low among Chinese models, the docs and community are all in Chinese, and the network environment is friendly with no need to fiddle with a proxy. These pragmatic factors together have made DeepSeek penetrate the Chinese developer community quickly over the past year; whether for product integration, personal projects, or simply daily conversation, DeepSeek is an option worth putting in your toolbox.

Several Ways to Register and Log In: Web, App, API

There are three entry points to DeepSeek; which to choose depends on your use case. The first is the web version: open chat.deepseek.com, register with a phone number or email, complete verification, and you enter the conversation interface, with no complicated profile filling needed throughout. The second is the mobile app: search DeepSeek in the iOS App Store and the Android app stores to find the official version, and after first opening it, log in with the same account; the web and app conversation histories are synced. The third is the API: you need to complete registration on the official open platform platform.deepseek.com, and after generating an API key you can call it in your own program—this path suits developers and those with automation needs. The three approaches are backed by the same account system; you can register on the web and then log in directly on the app, and you can generate multiple API keys under one account to conveniently distinguish projects. For newcomers we recommend first getting familiar with the conversation feature on the web, then considering installing the app once daily use is frequent, and applying for the API only when there are development needs—a fairly smooth onboarding path.

Interpreting the Web Version's Main Interface

The web version's interface design follows a minimalist style; on first entry you see a conversation input box in the center, a conversation-history sidebar on the left, and the ability to switch model types at the top. Above the input box there are usually a few toggles, such as whether to enable deep-thinking mode and whether to enable web search, which determine how the model works when answering. Deep-thinking mode invokes the reasoning-enhanced version of the model, suited to math problems, code problems, and tasks needing step-by-step reasoning; it responds a bit slower but answers more reliably. Web search makes the model first look up information on the internet before answering, suited to questions needing the latest information, such as recent news, industry trends, and product launches. The sidebar's conversation history is saved automatically and can be renamed, pinned, and deleted; for long-term use we recommend keeping conversations on different topics clearly separated, which makes later lookups much more convenient. The settings entry is in the top-right avatar, where you can adjust the interface language, font size, clear all conversation history, and so on—the few items used most in daily use. Overall the web version has few complex options, and getting familiar with those few toggles around the input box is basically enough to get started.

How to Download and Use the Mobile App

The mobile usage experience is basically consistent with the web version, with the main difference being an interaction form better suited to phone operation. For download channels, iOS users search DeepSeek directly in the App Store, making sure to download the version published by the official account DeepSeek, to avoid being misled by knock-off apps with similar names. Android users can search and download from mainstream channels such as the Xiaomi App Store, Huawei AppGallery, OPPO Software Store, and vivo App Store, or enter via the download link provided on the official website deepseek.com. On first opening the app there is a brief onboarding page, and after logging in you can start conversing. A few commonly used phone features are worth mentioning: voice input supports Chinese recognition, suited to when typing is inconvenient; copying and sharing conversation content is very convenient—long-press a message to see the options; and in settings you can turn on message notifications, letting the assistant remind you of things when needed. Compared with the desktop, the phone's advantage is being usable anytime, anywhere, while its disadvantage is a poorer experience for long-text input and code viewing, so use the app for daily commutes and fragmented time, and go back to the desktop for systematic work for a smoother experience.

Model Selection: When to Use the V Series and When to Use the R Series

DeepSeek's models are mainly split into two series, the general-conversation-oriented V series and the reasoning-enhanced R series; for the specific version numbers as of this writing, refer to the official public pages. The difference between the two summed up in one sentence: the V series responds fast and suits daily conversation and most routine tasks, while the R series performs multi-step reasoning before answering and suits problems needing rigorous thinking. As for specific use cases, for everyday chatting, writing copy, translating, looking up information, and writing ordinary scripts, the V series is already enough; for math competition problems, complex algorithm problems, logical analysis needing tight reasoning, and complex code debugging, switching to the R series gives noticeably better results. The price of the R series is a longer response time—sometimes a question takes tens of seconds or even longer, because the model unfolds its thinking process to run—so be mentally prepared for this when in a hurry. On both the web and the app you can generally switch in the conversation interface above; turning on deep-thinking mode invokes the R series. A practical suggestion is not to keep deep-thinking on by default the whole time; the V series is enough for simple questions, and save the R series for problems that truly need it, for a better experience.

Advanced Play: Integrating with Third-Party Clients and Workflows

After getting familiar with basic conversation, DeepSeek can play out more tricks through third-party clients and workflows. One category is desktop clients—multi-model aggregator clients such as Chatbox, Cherry Studio, and NextChat all support configuring the DeepSeek API as a backend, so you can use DeepSeek alongside other models in one unified interface to conveniently compare results. Another category is browser plugins—plugins like Sider and Monica let you select text on a web page and directly invoke the model to explain, translate, or summarize, and connecting DeepSeek as the backend is also possible. Another category is workflow automation tools—low-code platforms such as n8n, Coze, and Dify all support connecting the DeepSeek API, letting you build automated flows for email classification, document summarization, auto-reply, and content moderation. At the developer level there are also official or community adaptations of frameworks such as LangChain and LlamaIndex, making it convenient to integrate DeepSeek into more complex applications such as RAG knowledge bases and agent orchestration. These advanced plays share the trait of all needing a set of API keys as the access credential, suiting users willing to spend some time tinkering and pursuing deeper integration; for ordinary daily conversation, the official web or app is enough.

A Getting-Started API Call Example

If you want to integrate DeepSeek into your own program, an API call is the most direct way. The whole process is three steps: register an account on the open platform, generate an API key, and call the interface per the docs. The DeepSeek API is designed to be OpenAI-compatible, which means a great deal of existing SDKs and sample code can run with slight modification. Below is the simplest Python call example, using only the standard requests library with no extra dependencies needed.

import requests

url = "https://api.deepseek.com/v1/chat/completions"
headers = {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
}
data = {
    "model": "deepseek-chat",
    "messages": [
        {"role": "system", "content": "You are a concise assistant"},
        {"role": "user", "content": "Explain what entropy is in one sentence"}
    ]
}
resp = requests.post(url, headers=headers, json=data, timeout=60)
print(resp.json()["choices"][0]["message"]["content"])

If you prefer the command line, you can make the call with curl just as well—pass the above url, headers, and json data to curl as-is. For the specific model names, parameter descriptions, and billing methods, refer to the official API documentation, which lists each model's latest available name and context-length limit. Overall, the DeepSeek API has a low entry barrier, and any developer familiar with HTTP requests can get their first call working within half an hour.

What to Watch for Regarding Privacy and Data Compliance

Any online AI service must face the question of where data flows, and DeepSeek is no exception. When using the web version and app, the content you input is sent to the server for processing, and the company usually explains the data's purpose, retention period, and whether it participates in model training; this information is listed in the user agreement and privacy policy. A pragmatic suggestion is not to send highly sensitive personal information, internal corporate secrets, or unpublished contracts and code directly to any online AI assistant—this principle applies to all cloud models, not just DeepSeek. If your work involves sensitive data but you still want AI assistance, you can consider two paths: one is to use the open-source version deployed locally or in a private cloud, with data never leaving the network; the other is to redact before handing it to the model, replacing names, company names, and specific numbers with placeholders and letting the model process the logical structure. When procuring AI services, enterprise users should make data compliance a hard evaluation metric, including server location, whether data crosses borders, whether it participates in training, and security certifications; asking clearly before signing the contract is more efficient than remedying afterward. At the regulatory level, China already has the Administrative Measures for Generative AI Services, and service providers need to complete the corresponding filing; these compliance frameworks are still being improved, and users just need to stay basically informed.

Common Use Cases Suited to DeepSeek

In actual use, where is DeepSeek smoothest? Here are several common ones listed by frequency of use. The first category is Chinese writing assistance—from public-account articles, marketing copy, and email replies to thesis polishing, all usable, with more stable naturalness of Chinese expression than many overseas models. The second category is Chinese-English translation—whether everyday email translation or technical document translation, term handling is more nuanced than general translation tools. The third category is code assistance—everyday script writing, bug troubleshooting, algorithm implementation, and SQL generation are all handled, with good support for mainstream languages such as Python, JavaScript, and Go. The fourth category is math and logical reasoning—this is the R series' strong suit, fairly reliable for olympiad problems, interview problems, and complex business-logic analysis. The fifth category is study assistance—having it explain a concept you do not understand, translate and explain a thesis passage you cannot read, or translate complex legal provisions into plain language—scenarios very practical for both students and professionals. The sixth category is everyday knowledge Q&A—it answers life questions on cooking, fitness, home renovation, and personal finance fairly reliably, and with web search the timeliness is not bad either. DeepSeek can give satisfying answers in all of these categories, and using it as your go-to assistant in a daily workflow is no problem.

Frequently Asked Questions

Is DeepSeek free?

The web version and mobile app are basically free for individual users; after logging in you can converse directly, with no core feature requiring forced payment. The free version may have response-speed or concurrency limits during peak hours, which is the common practice for most free AI services. If you are a developer who needs to integrate DeepSeek into your own program via API calls, this part is billed by token usage, renowned as low-priced among Chinese models, with the specific unit price subject to the official open platform's public page. Overall, ordinary users can get by entirely on the free web and app, and only large-scale integration involves payment—a pricing strategy friendly to individual users.

Which is stronger, DeepSeek or ChatGPT?

This question has no one-size-fits-all answer; it depends on the specific task and specific version. In Chinese scenarios, DeepSeek's naturalness of expression is widely praised, and the industry generally believes it is very close to top closed-source models in Chinese writing, Chinese translation, and Chinese knowledge Q&A. On code and math reasoning tasks, according to public reports DeepSeek's reasoning-enhanced version approaches top closed-source levels, with the specific strengths depending on task type. In English scenarios and multimodal scenarios, leading closed-source models have iterated longer and still hold an edge on some tasks. The pragmatic judgment is that for a mostly-Chinese daily workflow, DeepSeek is fully up to the job, and you can supplement with other tools when you need English academic writing or advanced multimodal features—using two assistants together is more worthwhile than fighting to stick with one.

Can DeepSeek be used directly within China?

DeepSeek is a Chinese company's product, with servers and services all deployed within China; the web version, app, and API can all be accessed directly within China, with no VPN and no fiddling with a proxy needed. This is one of the real reasons many Chinese users choose DeepSeek, as stability and access speed are both stronger than overseas services. The account system also uses a phone number for registration, fitting Chinese users' habits. If your workflow needs a stable, reliable AI assistant and you do not want to worry about the network environment, DeepSeek is a fairly suitable choice. Note that the coverage of some features such as web search may differ from overseas search engines; you will not feel it in daily use, and for academic research involving foreign material you can pair with other tools.

Can DeepSeek be deployed locally?

Yes. DeepSeek releases its model weights in open-source form on platforms like Hugging Face, allowing download and running on your own hardware; we recommend carefully reading the specific license terms before downloading—commercial use is usually permitted, but you must follow the corresponding attribution and compliance requirements. The prerequisite for local deployment is that you have sufficient hardware resources; the full large-parameter model has very high video-memory requirements that ordinary consumer-grade graphics cards struggle to run directly, but the company also offers versions of different parameter scales, with the small-parameter versions runnable on consumer-grade graphics cards or even a high-spec Mac. Common local-deployment tools include Ollama, vLLM, and llama.cpp; after downloading the model weights locally, configure it and it runs. Local deployment is mainly aimed at users with data-privacy needs or who want to do deep research; for ordinary users the official online service is already enough.

Is DeepSeek good for writing code?

Yes, and it is one of DeepSeek's more prominent capabilities. For everyday programming tasks such as writing scripts, looking up API usage, explaining others' code, debugging errors, refactoring functions, and generating unit tests, DeepSeek gives usable answers, with good support for mainstream languages such as Python, JavaScript, TypeScript, Java, Go, and Rust. For complex algorithm problems or multi-file collaboration scenarios, switching to the reasoning-enhanced version shows noticeable improvement. Pairing DeepSeek with an IDE coding tool that has project-comprehension ability lets you handle both everyday completion and complex-task consultation. When writing code, still maintain critical judgment of the AI output—code that should be reviewed must be reviewed, and code that should be tested must be tested; this principle holds for all AI coding assistants.