What Is DeepSeek? The Company, Chatbot, API and Models Explained
DeepSeek is a Chinese artificial intelligence company founded in 2023. The same name also refers to its large language model families and the services through which people and developers use them: a hosted chatbot, mobile app, developer API, and downloadable model releases. DeepSeek is therefore not one chatbot or one model. “DeepSeek AI” is a common informal name for this wider company-and-product ecosystem.
This explainer focuses on what DeepSeek is, how its technology works, and where the company, products, and model releases differ. For access routes, model navigation, and broader product guidance, use the DeepSeek AI guide and access hub.
Independent publication: Chat-Deep.ai is not operated by, endorsed by, or affiliated with DeepSeek. Use official DeepSeek services for accounts, passwords, app downloads, API keys, billing, and support.
Last verified: July 16, 2026 · Reviewed by the Chat-Deep.ai Editorial Team.
On This Page
What Does “DeepSeek” Refer To?
The meaning depends on the context. A person saying “I used DeepSeek” may mean the official chat interface. A developer may mean the hosted API. A researcher may mean a particular model checkpoint. A news article may mean the company behind all of them. Keeping these meanings separate prevents several common mistakes about features, licensing, privacy, and cost.
| Term | What it means | What it does not automatically mean |
|---|---|---|
| DeepSeek company | The organization that develops models, publishes research, and operates official services. | It is not the name of one fixed model. |
| DeepSeek Chat | The hosted, end-user chat experience provided through DeepSeek’s official web service. | It is not the developer API or a locally installed model. |
| DeepSeek app | The mobile interface linked from DeepSeek’s official website. | It is not every third-party app that includes “DeepSeek” in its name. |
| DeepSeek API | A hosted developer service that lets software send requests to supported DeepSeek models. | It is not the same product as consumer chat, even when model capabilities overlap. |
| DeepSeek model release | A named language, reasoning, coding, vision, or research model, sometimes with downloadable weights. | It does not guarantee availability in every DeepSeek interface. |
This distinction is also why an official service and an independent interface can both provide access to a DeepSeek model without being the same website or having the same data practices. For verified account and product destinations, use the separate guide to official DeepSeek links.
Who Created DeepSeek?
DeepSeek’s official organization profile describes it as a Chinese company founded in 2023. DeepSeek’s official terms identify Hangzhou DeepSeek Artificial Intelligence Co., Ltd. as the owner and operator of its products and services. That legal identity matters because official accounts, service rules, privacy obligations, and user agreements belong to the operator—not to independent guides or third-party applications.
Independent reporting by The Associated Press identifies Liang Wenfeng as DeepSeek’s founder and describes his connection to the quantitative hedge fund High-Flyer. DeepSeek’s first-party profile and legal pages cited above confirm the company’s founding year and operating entity, but they do not publish an individual founder biography or a complete ownership structure. This page therefore separates the official company facts from independently reported background.
DeepSeek develops foundation models and related systems for language, code, reasoning, and other machine-learning tasks. Its public footprint includes hosted products, developer services, model repositories, technical reports, and downloadable releases. Describing it only as “a chatbot” misses the research and infrastructure behind the interface; describing it only as “a model” misses the company and hosted services.
How Does DeepSeek Work?
At a high level, DeepSeek models work like other large language models: they process a prompt as tokens and generate an output by estimating which token should follow from the supplied context and instructions. The company’s official model disclosure describes its foundation models as large-scale language models built with deep neural networks. The generated response can be useful without being a stored quotation or a guaranteed statement of fact.
1. The prompt becomes tokens
The system converts text and code into smaller units called tokens. Instructions, conversation history, attached context, and system rules all compete for space in the model’s context window.
2. The model performs inference
Its learned neural-network parameters transform the input into probability estimates for possible output tokens. The service or local runtime then decodes those estimates into a response.
3. The output is generated
The model produces text or code sequentially. Settings, tools, retrieved documents, and application rules can change the result, so the same underlying model can behave differently across products.
Mixture-of-Experts in plain English
Several flagship DeepSeek families use a Mixture-of-Experts, or MoE, architecture. Instead of activating every model component for every token, a routing mechanism selects relevant expert components. This is why a model can have a very large total parameter count while activating a smaller subset during inference. MoE is an architectural technique, not proof that every answer will be fast, cheap, or correct, and it should not be generalized to every model ever published under the DeepSeek name.
Reasoning and post-training
After pre-training, developers can use supervised examples, preference data, reinforcement learning, and other post-training methods to improve instruction following or reasoning behavior. DeepSeek’s R1 research is a prominent example of work on reinforcement-learning-based reasoning. A thinking or reasoning mode may spend more computation on intermediate steps before returning an answer, but a longer reasoning trace is not evidence that the conclusion is true.
Key point: a language model generates a plausible response from patterns, instructions, and supplied context. It does not independently guarantee truth, complete source coverage, or professional judgment.
DeepSeek Chat, the API, and Open-Weight Models Are Different
DeepSeek can be used through hosted consumer products, a hosted developer service, or model files run on separate infrastructure. The route determines who operates the interface, where inference happens, what the user must configure, and which privacy or security responsibilities apply.
| Access route | Who operates the inference environment? | Suitable for | What the user manages |
|---|---|---|---|
| Official web chat | DeepSeek | Direct conversations without writing code | Account choices, prompts, files, and compliance with the official service terms |
| Official mobile app | DeepSeek | Hosted chat from a phone or tablet | App permissions, account choices, device security, and submitted content |
| Developer API | DeepSeek hosts the model service; the developer operates the downstream application | Software integrations, structured workflows, and controlled application features | API keys, application security, user notices, logs, output checks, and usage controls |
| Downloaded open-weight model | The person or organization running the model | Research, evaluation, customization, offline use, or private infrastructure | License review, hardware, runtime, access control, storage, logs, updates, and monitoring |
| Third-party interface | The third party, sometimes with a hosted model provider behind it | A separate product experience built around DeepSeek models or APIs | Reviewing both the interface provider and any disclosed upstream processor |
API compatibility with a familiar request format means a developer may be able to adapt existing software by changing the endpoint, key, and model setting. It does not mean another AI company operates DeepSeek’s API. Developers should use the dedicated DeepSeek API guide for implementation concepts. Teams considering their own inference environment can start with the guide to run DeepSeek locally.
Open-weight is the safer general term. DeepSeek publishes downloadable weights and supporting repositories for multiple releases, but licenses and included materials can differ. Public weights do not make the hosted website, app, API, training data, or every product component open-source software.
Where Do DeepSeek’s Model Families Fit?
A model-family name identifies a line of technical releases, not the whole DeepSeek company. Product menus and API availability can change independently of research repositories, and a downloadable checkpoint may not have the same tools or interface behavior as hosted chat.
- General language families: releases such as the V-series are designed for broad language, code, and instruction-following tasks. The official DeepSeek-V3 repository, for example, documents a Mixture-of-Experts language model and its research materials.
- Reasoning families: the DeepSeek-R1 repository describes reasoning-focused models and distilled variants developed through multiple training stages, including reinforcement learning.
- Specialized families: DeepSeek has also published work aimed at code, mathematics, formal theorem proving, vision-language tasks, and optical character recognition.
- Hosted product labels: a name shown in web chat or an API is a service-level choice. It should not be assumed to describe every public checkpoint or every historical release.
Model IDs, context limits, licenses, availability, and feature support belong in a maintained model reference rather than this definition page. Use the DeepSeek model hub when you need that level of detail.
What Can You Use DeepSeek For—and What Can It Not Guarantee?
What DeepSeek can do depends on the selected model, access route, tools, instructions, and context. It is best treated as a system for generating and transforming language or code, with human verification proportional to the consequences of the task.
Commonly useful tasks
- Explain a concept at a chosen level of detail.
- Draft, rewrite, translate, or summarize text.
- Brainstorm questions, outlines, examples, or alternatives.
- Explain code, draft functions, suggest tests, or help investigate a bug.
- Extract or reorganize information from supplied text.
- Produce structured output when the model and application support it.
- Work through mathematics, logic, or multi-step analysis as an aid to human review.
Important limits
- It can invent facts, citations, quotes, links, or technical details.
- It may not have live web access unless the product explicitly supplies a search or retrieval tool.
- It can miss context, misread an ambiguous prompt, or follow a flawed premise.
- Its answer can change with wording, settings, model version, and supplied documents.
- A large context window does not create permanent memory or prove that every included detail was used correctly.
- Reasoning behavior does not replace source checking, testing, or qualified professional judgment.
- Local execution does not guarantee privacy if the runtime, plugins, logs, or network settings transmit data elsewhere.
Five misconceptions to avoid
- “DeepSeek is one model.” It is a company, service ecosystem, and collection of model families.
- “DeepSeek Chat and the API are identical.” They are different access products with different controls and user responsibilities.
- “Open weights means everything is open source.” A model license does not automatically cover hosted services, training data, or every software component.
- “A reasoning response is a verified proof.” Intermediate reasoning can still rest on false assumptions or produce an incorrect conclusion.
- “Self-hosted means private by default.” Privacy depends on the entire deployment, including storage, logging, telemetry, access controls, plugins, and network traffic.
What Should You Check Before Using DeepSeek?
- Confirm the destination. Use official domains for passwords, API keys, billing, downloads, and support. A third-party interface should state who operates it.
- Identify the access route. Hosted chat, an API integration, and a self-hosted model have different operators, controls, and failure modes.
- Review data handling. Check the privacy terms for the exact service and avoid submitting secrets, credentials, regulated records, or confidential data without authorization and appropriate controls.
- Verify consequential outputs. Check claims against authoritative sources, run code and tests in a safe environment, and require qualified review for medical, legal, financial, security, employment, or other high-impact uses.
- Check the exact model license. Do not apply the license of one DeepSeek release to another checkpoint, dataset, repository, or hosted service.
For a focused assessment of data handling, third-party interfaces, sensitive prompts, and deployment choices, read the independent DeepSeek safety guide.
Where Should a Beginner Go Next?
Want to use the chat?
Follow the practical guide on how to use DeepSeek Chat, including prompt and verification basics.
Need model details?
Use the model hub linked above for release families, availability, feature notes, and model-specific caveats.
Building software?
Use the API guide linked above, then verify implementation details against DeepSeek’s official developer documentation.
Frequently Asked Questions
What is DeepSeek in simple terms?
DeepSeek is a Chinese AI company founded in 2023. It develops large language models and provides ways to use them through hosted chat, a mobile app, a developer API, and downloadable model releases. The name can mean the company, one of its products, or a model family.
Is DeepSeek a company, a chatbot, or a model?
It can mean all three, depending on the sentence. DeepSeek is the company; DeepSeek Chat is a hosted product; and names such as V-series or R1 identify model families. Treating those meanings as interchangeable can lead to wrong assumptions about access, features, licenses, and privacy.
Who created DeepSeek?
DeepSeek’s first-party profile says the Chinese company was founded in 2023, and its official terms name Hangzhou DeepSeek Artificial Intelligence Co., Ltd. as the operator of its services. The Associated Press identifies Liang Wenfeng as the founder. DeepSeek’s first-party pages cited in this article do not provide a complete founder biography or ownership structure.
How does DeepSeek work?
DeepSeek language models turn a prompt into tokens, process those tokens through a trained neural network, and generate output token by token from the supplied context and instructions. Several flagship families use Mixture-of-Experts routing, and reasoning-focused releases use post-training methods intended to improve multi-step problem solving.
What is the difference between DeepSeek Chat and the DeepSeek API?
DeepSeek Chat is a hosted interface designed for direct human conversations. The API is a developer service used by software applications. An API integration requires key management, application security, user notices, logging decisions, error handling, and output verification that a person using consumer chat does not configure in the same way.
Is all of DeepSeek open source?
No. DeepSeek publishes public repositories and downloadable weights for multiple releases, but “open source” should not be applied automatically to the entire company, every model, training data, or the hosted website, app, and API. Review the repository and license for the exact release you intend to use.
Can DeepSeek run locally?
Eligible open-weight releases can run on hardware you control through compatible inference software. Feasibility depends on model size, quantization, memory, storage, and runtime support. The full hosted experience is not reproduced automatically, and privacy still depends on how the local environment handles logs, plugins, files, and network traffic.
DeepSeek Explained: The Short Version
DeepSeek is a Chinese AI company, not a single chatbot or model. It develops language-model families and makes them available through distinct hosted and downloadable routes. Those routes can share underlying technology while differing in interface, features, operator responsibilities, privacy, licensing, and infrastructure. Understanding that distinction is the foundation for using DeepSeek accurately and choosing the right specialized guide.
Editorial note: Facts were checked against DeepSeek’s first-party company profile, legal terms, model disclosure, and official repositories, with independently reported founder background labeled separately. See the Chat-Deep.ai Editorial Policy for sourcing and corrections.