Is DeepSeek R1 Safe to Run Locally?

When DeepSeek R1 launched in January 2025, it attracted significant scrutiny over data privacy. Multiple countries’ security agencies raised concerns about the DeepSeek cloud service, and several organisations banned its use on work devices. But those concerns apply specifically to the cloud version — running DeepSeek R1 locally via Ollama is an entirely different situation.

What Were the Privacy Concerns?

The concerns centred on DeepSeek’s cloud service (chat.deepseek.com and the DeepSeek API). Specifically:

• DeepSeek’s privacy policy states that user data is stored on servers in China, subject to Chinese law
• The app was found to transmit device information and usage data to Chinese servers
• Several governments and organisations (including Italy, Australia, and various US government agencies) restricted or banned the cloud service on official devices
• Security researchers identified obfuscated code in the iOS app that could collect device fingerprinting data

These are legitimate concerns for a cloud-based AI service. However, they are irrelevant when running DeepSeek R1 locally.

Why Local Deployment Is Different

When you run DeepSeek R1 via Ollama, you are downloading the model weights and running them entirely on your own hardware. There is no connection to DeepSeek’s servers during inference. Your prompts, responses, and data never leave your machine.

The model weights themselves are openly published on HuggingFace and have been independently reviewed by researchers worldwide. They contain no telemetry, no data collection, and no network calls — they are simply a large file of numerical weights.

What Actually Happens When You Run Ollama

1. You download the model weights from Ollama’s CDN (or HuggingFace) — a one-time download
2. Ollama runs a local server on your machine (port 11434)
3. All inference happens locally using your CPU/GPU
4. No outbound network requests are made during a conversation
5. Your prompts and responses are stored locally only (or not at all, depending on your setup)

Verifying There Are No Network Calls

If you want to verify this yourself, you can monitor network traffic while running a query:

# On macOS/Linux, monitor outbound connections from the ollama process
sudo lsof -i -P | grep ollama

# Or use netstat
netstat -an | grep 11434

You’ll see Ollama listening on localhost only, with no outbound connections during inference.

Is the Model Itself Trustworthy?

The DeepSeek R1 model weights have been:

• Published openly on HuggingFace with full transparency
• Downloaded and tested by thousands of independent researchers globally
• Integrated into Ollama’s official model library after review
• Used to create derivative models (the distilled versions are based on Llama and Qwen architectures)

There is no credible evidence of backdoors or malicious behaviour in the model weights themselves. The weights are deterministic mathematical values — they cannot “call home” or exfiltrate data.

Appropriate Use Cases for Local DeepSeek R1

Running locally is appropriate for:

• Sensitive business documents and client data
• Proprietary source code
• Personal financial or legal information
• Any task where you cannot allow data to leave your network
• Air-gapped environments

What You Should Avoid

Even running locally, standard security practices apply:

• Don’t expose the Ollama API publicly without authentication — the default port 11434 should not be open to the internet
• Don’t use the DeepSeek cloud service for sensitive data — this is where the privacy concerns are valid
• Don’t use the DeepSeek app on devices where data privacy is critical

Compared to Other Cloud AI Services

It’s worth noting that all cloud AI services — including ChatGPT and Claude — process your data on their servers. The difference with DeepSeek’s cloud is the jurisdiction (China) and the specific data practices. If privacy is a concern, the answer for any AI service is to run locally — and DeepSeek R1 via Ollama is one of the best local reasoning models available.

Verdict

Running DeepSeek R1 locally via Ollama is safe. The privacy concerns about DeepSeek apply to their cloud service, not to the open-source model weights running on your own hardware. For sensitive work, a local deployment is actually more private than any cloud AI service.

Get started: How to run DeepSeek R1 on Ollama | Which model size should you use?