Translation note: This English version was translated by Codex (GPT-5) on 2026-04-20 18:01:46 CST. The source text is the corresponding Chinese post in this repository.
If you want to jump straight into the hands-on part, you can skip to the “How” section.
Background
Since ChatGPT took off, AI and large language models have remained a hot topic. DeepSeek-R1, especially, became a symbol of the current AI wave in China.
As more and more people around me started talking about AI, I realized that the “AI era” was no longer a distant idea. At the same time, the official DeepSeek service often returned the familiar message: “Server busy, please try again later.”
This article explains what AI is, why private deployment matters, and how to get started with the least friction.
What: AI, LLMs, DeepSeek-R1, and Open Source
AI
AI is the field of building computer systems that can reason, learn, and act.
Large language model
A large language model is an artificial neural network trained on massive amounts of text.
DeepSeek-R1
DeepSeek-R1 is DeepSeek’s first-generation reasoning model. Since its release, it has been widely discussed because of its strong performance and low cost.
Open source
Open source means the design is publicly available and can be modified and shared by anyone.
Why did DeepSeek open source?
My view is that it was both a commercial move and a contribution to the public ecosystem.
Why are servers busy?
The main reasons are simple:
- Heavy domestic traffic
- Overseas traffic and attacks
- Competitive pressure and attacks from rivals
Why use APIs, cloud deployment, or local deployment?
Using DeepSeek through the official app is only one option. Other paths include:
- shared API access
- cloud deployment
- local deployment
These options trade off convenience, privacy, and cost.
Why private deployment costs money
Public web access is a shared service. Private deployment requires dedicated resources, which means hardware, electricity, network, and maintenance costs.
A side note on ads and privacy
The more AI learns about your behavior, the more it can shape what you see. That makes privacy hygiene even more important in the AI era.
How: A private setup with Chatbox
If you want a simple GUI instead of a complicated API-only setup, Chatbox is a practical choice.
Official website: https://chatboxai.app/zh
I tested it mainly because I wanted to see whether a low-friction setup could still work. The tool is open source, multi-platform, and supports API connections.
Step 1: Download the app
Step 2: Check pricing
Step 3: Pick a plan and pay
I chose the plan that matched my usage needs.
Step 4: View the API key
Step 5: Paste the key into Chatbox
Step 6: Start using it
If you do not want to use Chatbox, there are also other API vendors and local deployment paths. The important thing is to understand the trade-offs between cost and privacy.
Conclusion
The most important lesson is not that one app is better than another. It is that AI is becoming infrastructure, and private deployment is a useful skill to have.