Why run DeepSeek locally
Public services are convenient, but every request lands on someone else’s servers — and takes the contents of your documents, correspondence and customer records with it. Running locally removes that risk entirely: the model sits on your server, works without an internet connection, and nothing goes out. No per-seat subscriptions, no token limits — you pay once for the hardware.
On why owning the box beats renting one, there is a separate breakdown in own AI server or rented GPU.
The DeepSeek variants
DeepSeek ships in several sizes aimed at different hardware. Simplified, they break down like this:
| Variant | Good for | Requirements |
|---|---|---|
| Distilled | document chat, support, text analysis | a single mid-range GPU |
| Mid-size | harder reasoning, analytics | a powerful GPU or several of them |
| Full | maximum quality, heavy workloads | a server build with a lot of VRAM |
What it takes to run
- •A server with a GPU — or several GPUs for the larger models,
- •An inference runtime, typically one of the open local-inference tools,
- •The model itself, downloaded once to disk and offline from then on,
- •Optionally a knowledge base of your documents, so the model answers from your data (RAG).
Connecting your own documents without retraining the model is exactly what RAG does. That is how DeepSeek starts answering about your contracts, procedures and products instead of speaking in generalities.
DeepSeek is not the only option
DeepSeek is strong, but other open models sometimes suit a particular job better. For a survey of the current field and what each family is good at, see the best open-source LLMs to self-host. We choose by measured quality on your data rather than by the hype around a name.
Where to start in practice
The order is straightforward: define the tasks (support, documents, analytics), size the model and hardware to them, install and check the quality on your own examples, then connect the knowledge base. The full build path is laid out in how to build an AI server, and our team can do the whole thing turnkey — see Stitex AI servers.
Frequently asked questions
Can DeepSeek run without an internet connection?
Yes. Once the model has been downloaded to your server it works fully offline — every request is handled on your own hardware and nothing goes out to the network. That is the whole point of running it locally.
Which version of DeepSeek do I need?
It depends on the task and the hardware. For document chat, support and text analysis, a distilled version is usually enough and runs on a single GPU. The full model is stronger but needs substantially more VRAM. Pick the size that fits the job rather than defaulting to the largest one available.
DeepSeek or another open-source model?
DeepSeek is one of the strong open models, not the only one. For a specific job, Qwen, Llama or Gemma often fit better. We select the model by measured quality on your data, not by the name on the box.
Is the data guaranteed to stay in?
Running locally, the model never calls an external API. We additionally lock the server down with network rules so that outbound requests carrying working data are not possible even in theory.