DeepSeek Chat Review (2026) — Free, MIT-Licensed, and Hosted in China

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DeepSeek is the awkward one to write about honestly, because the capability argument and the privacy argument point in opposite directions. The web chat is free, the models behind it are genuinely competitive with expensive commercial systems, and the weights are released under one of the most permissive licences in the industry. It is also a service that tells you, in its own privacy policy, that your data is stored in China.

Neither of those facts cancels the other. Which one decides it for you depends entirely on what you intend to type into it.

What you get for nothing

The free web chat at chat.deepseek.com puts you in front of DeepSeek's current flagship line without a subscription. The 2026 releases are agent-oriented: the model cards describe million-token context handling, tool use, and selectable reasoning effort so you can trade latency for deliberation on hard problems.

In practice that means it holds up on the things people actually pay other assistants for — long documents, multi-step reasoning, code — rather than being a lightweight free alternative that folds under load. DeepSeek's own published benchmarks put its top model alongside the leading proprietary systems on coding and agentic tasks. Vendor benchmarks are marketing and should be read as such, but the independent reception since the first R1 release has broadly agreed with the direction, if not the decimal places.

Where your data goes, in DeepSeek's own words

DeepSeek's privacy policy is unusually direct, so it is worth quoting rather than characterising: it states that to provide its services it directly collects, processes and stores personal data in the People's Republic of China, and that data is used to train and improve its machine learning models.

There is an opt-out. The policy grants a right to opt out of having your personal data used for training, but it is exercised by emailing privacy@deepseek.com rather than by flipping a switch in the app — a meaningfully higher barrier than the settings-page toggles Google and OpenAI offer, and one most users will never cross.

What this does not mean is that DeepSeek is uniquely careless. Every free consumer assistant in this category trains on your conversations by default. What is specific to DeepSeek is the jurisdiction: the data protection regime, the legal recourse available to you, and the government access rules are those of the PRC, not of your own country. If you are in the EU or the UK, this is the kind of transfer your employer's policy probably has an opinion about.

The escape hatch that makes this reviewable at all

DeepSeek publishes its flagship weights on Hugging Face under the MIT licence. That is not a source-available marketing licence with a commercial-use carve-out; it is the real thing, with essentially no restriction on use, modification or redistribution.

The consequence is that the privacy objection above applies to DeepSeek's hosted service, not to DeepSeek's models. You can run the models on your own hardware, or through any inference host in a jurisdiction you are comfortable with, and none of your input reaches DeepSeek at all. The full flagship models demand serious hardware and are out of reach for most individuals, but smaller distilled variants run locally on a good desktop through tools like Ollama or LM Studio.

Very few products let you disagree with the vendor's data policy and keep using the product anyway. This one does, and that is the honest reason it earns a place here.

Pros

• Frontier-class capability at no cost, with no card and no trial period.
• Flagship weights released under the MIT licence, so self-hosting is a real option rather than a theoretical one.
• Long context and selectable reasoning effort on the free tier.
• The privacy policy states its position plainly instead of burying it.

Cons

• Data is collected, processed and stored in the PRC, which is a compliance question before it is a preference.
• Training opt-out requires emailing the company, not changing a setting.
• Self-hosting the full models needs hardware most readers do not have.
• Capability claims come largely from vendor-published benchmarks.
• Model naming changes fast, so what the free chat serves you this month may not be what it served last month.

Best alternatives

• Mistral Vibe — formerly Le Chat; the closest open-weights comparison from a European vendor, if jurisdiction is the sticking point (chatbots).
• HuggingChat — lets you reach open models, including DeepSeek's, through a different host (chatbots).
• Ollama — the practical route to running DeepSeek's weights locally with nothing leaving your machine (chatbots).

FAQ

Is DeepSeek Chat actually open source? The model weights are: DeepSeek publishes its flagship models on Hugging Face under the MIT licence, which is about as permissive as licensing gets. The chat service at chat.deepseek.com is a free hosted product, not an open-source application. Those are two different things and the distinction matters, because only the first one lets you run the model somewhere you control.

Where does DeepSeek store my data? DeepSeek's privacy policy states that it directly collects, processes and stores personal data in the People's Republic of China, and that data is used to train and improve its models. The policy also grants a right to opt out of having your data used for training, exercised by writing to privacy@deepseek.com rather than through a toggle in the app.

Can I use DeepSeek's models without sending data to DeepSeek? Yes, and this is the strongest argument for DeepSeek. Because the weights are MIT-licensed you can download them and run them on your own hardware or through a third-party host in a jurisdiction you choose. The full flagship models need serious hardware, but smaller distilled variants run on a well-specified desktop, and tools such as Ollama or LM Studio make local running straightforward.

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