Your local AI Chat

Are you concern about your data security and also wanted to use power of ChatGPT kind of great tool but fearing to give any personal information? I would say, your concern is valid but good news that we do have an option to get your own ChatGPT kind of LLM model which can be deployed locally. Yes, I'm talking about DeepSeek.

You can get the feel of DeepSeek by visiting https://chat.deepseek.com, which you can immidiately started using after confirming your age. The interface is so simple where you can start your conversations by simply clicking "New Chat" from left panel. The good thing I like about deepseek is, it shows every steps the way it process the instuctions and feels more relatable how human really may think.

I'm not here to decide among OpenAI and DeepSeek, which one is better or winning over other but I believe they are great tools and each one of us can get benefit the way we would like.

Let's jump straight on the topic here we are for. To setup deepseek locally, you need following:

1. Ollama [Download] - It is open-source tool used to run Large Language Model locally without using any cloud services (so no recurring fee ??). Just download and double to begin installation. Once finish installation, Ollama will start running.

To verify, if your Ollama running, open command prompt and type ollama command, you should be seeing ollama related info.

2. DeepSeek R1 Model [Download] - You can choose your preference and copy the command (red circled). Ex. c:\>ollama run deepseek-r1:1.5b

Now you are ready with local AI chat and ready to see the results. I've fired my first prompt and I got the result what I was exactly expected

Using a local LLM (Large Language Model) has several benefits, especially compared to cloud-based or API-dependent models. Here are some key advantages:

1. Privacy & Security

No data is sent to external servers, ensuring confidential and sensitive information stays private.

Ideal for industries handling sensitive data, such as healthcare, finance, or legal services.

2. Offline Access

Works without an internet connection, making it reliable in remote locations or areas with limited connectivity.

Useful for on-premise deployments where internet access is restricted.

3. Faster Response Times

No network latency, as the model runs directly on local hardware.

Real-time responses make it ideal for applications requiring instant feedback, such as chatbots, coding assistants, and automation tools.

4. Cost Savings

No recurring API or cloud computing costs.

A one-time investment in hardware may be more cost-effective for long-term, high-volume usage.

5. Customization & Fine-tuning

Easier to fine-tune the model on proprietary data to improve accuracy and relevance for specific tasks.

Control over model updates and modifications without relying on third-party providers.

6. No Dependency on Third-party Providers

Ensures operational continuity even if external LLM providers change policies, pricing, or shut down services.

Avoids potential issues with API rate limits or downtime.

7. Energy Efficiency & Control

Can be optimized to run on specific hardware, reducing power consumption and improving performance.

Local deployment allows for better resource allocation and tuning.

8. Compliance with Regulations

Useful for organizations that need to comply with strict data regulations (e.g., GDPR, HIPAA) since data doesn’t leave the local environment.