What Is DeepSeek AI? A Complete Beginner’s Guide

DeepSeek is an AI company and model developer whose products include a hosted chatbot, developer APIs and downloadable model weights. It is not one single app or model. A visitor may use DeepSeek Chat, a developer may call the DeepSeek API, and a researcher may download an older or open-weight model for local study.

Quick answer

• DeepSeek was founded in China in 2023 and develops large language models.
• Official access routes include the web chat, mobile apps, API platform and open repositories.
• As verified on 2026-07-30, the first-party API listed DeepSeek V4 Flash and V4 Pro.
• DeepSeek R1, V3, Coder and VL remain important model families, but they do not all represent current API product names.
• AI output can be wrong. Sensitive, regulated or confidential information needs additional safeguards.

What the name DeepSeek can mean

People use “DeepSeek” for four related things. First, it is the company, Hangzhou DeepSeek Artificial Intelligence Co., Ltd. Second, it is a family of language and multimodal research models. Third, it is the free hosted chat at chat.deepseek.com↗ — official external destination. Fourth, it is the paid, token-metered developer service at platform.deepseek.com↗ — official external destination.

Keeping those meanings separate prevents common mistakes. A model that can be downloaded from GitHub or Hugging Face is not automatically the model served by the current API. Likewise, free access to the hosted chat does not make API calls free. The pricing guide explains those boundaries.

Current and historically important models

The official API pricing page listed deepseek-v4-flash and deepseek-v4-pro when this guide was verified. Both support thinking and non-thinking modes, JSON output and tool calling. DeepSeek described V4 Flash as the faster, lower-cost option and V4 Pro as the higher-capability option. Those are the current product labels, not a firsthand performance verdict.

DeepSeek V3 and R1 are historically important open releases. V3 is a mixture-of-experts language model; R1 focuses on reasoning and has several smaller distilled variants. DeepSeek Coder V2 targets programming workflows, while DeepSeek VL and VL2 combine text and image understanding. See the complete model overview before choosing a checkpoint or API ID.

How people access DeepSeek

The simplest route is the official browser chat. DeepSeek also provides an official mobile download page for iOS and Android. Developers can create an API key and use OpenAI-compatible or Anthropic-compatible request formats. Local users can obtain compatible open weights and run them through software such as Ollama, vLLM or other supported runtimes.

These routes have different privacy, cost and maintenance implications. Hosted chat trades local control for convenience. API use gives developers programmatic control but requires key management and usage billing. Local deployment can keep prompts on hardware you control, but you become responsible for model files, updates, access control, logs and adequate compute.

What DeepSeek can help with

Typical uses include explaining concepts, drafting and revising text, summarising supplied material, generating or reviewing code, extracting structured data, and working through multi-step reasoning problems. The API can also propose tool calls that your application validates and executes.

None of these uses removes the need for human judgment. For research, ask for a claim-and-source table and verify each source outside the model. For coding, run tests, linters, dependency checks and a security review. For business work, remove confidential information and require an accountable person to approve consequential output.

Open weights do not mean zero cost or zero risk

Several DeepSeek repositories publish weights under stated licences, but “open source” is often used loosely in AI discussions. Always read the licence attached to the exact repository and derived checkpoint. Distilled R1 models can also inherit terms from their base model families.

Downloading weights avoids per-token charges from DeepSeek, not computing costs. Storage, RAM or VRAM, electricity, administration and security still matter. A small quantised model may run on consumer hardware, while full-size mixture-of-experts models can require specialist infrastructure. The local installation guide explains the practical choices without promising a speed your hardware may not deliver.

Limits readers should understand

DeepSeek models can produce fluent but false answers, weak citations, insecure code or unjustified confidence. Web search can improve freshness, but it does not make every retrieved page reliable. Long context can hold more material, yet relevant details may still be missed. Tool calling means the model requests a function; it does not make the function safe to execute.

Privacy also depends on the route used. DeepSeek’s policy describes collection of prompts, uploads, account details, device and network data for its services. It advises users not to submit sensitive personal data. Read the privacy guide and your organisation’s policies before using confidential information.

Official resources

Use DeepSeek’s company site↗ — official external destination for official destinations, DeepSeek Chat↗ — official external destination for hosted access, the API documentation↗ — official external destination for integration details, the status page↗ — official external destination for incidents, and the official GitHub organisation↗ — external site for published code and model repositories. Similar-looking domains may be unrelated or fraudulent.

Conclusion

DeepSeek is best understood as an ecosystem: company, models, hosted services and open releases. Choose an access route based on your task, privacy requirements, budget and hardware. Then verify current model names and policies at the official source, because the product surface changes faster than a static guide can.