> ## Documentation Index
> Fetch the complete documentation index at: https://docs.levelrail.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Self-host Ollama: DeepSeek-R1 7B with Docker

> DeepSeek's R1 distilled 7B reasoning model, served locally through Ollama's HTTP API.

DeepSeek's R1 distilled 7B reasoning model, served locally through Ollama's HTTP API.

This page describes the Levelrail template for Ollama: DeepSeek-R1 7B (AI). It deploys the services below as one Docker Compose app on your own server. Project site: [https://ollama.com/library/deepseek-r1](https://ollama.com/library/deepseek-r1).

Recommended memory: about 6144 MiB.

## Services, ports and volumes

| Service | Image | Container ports | Volumes |
| - | - | - | - |
| `ollama` | `ollama/ollama:0.33.3` | 11434 | `ollama_data -> /root/.ollama` |

## Environment variables

This template sets no environment variables.

Passwords and keys marked as generated are created for you when the app is deployed and stored as secrets. Values are not shown here.

## Deploy Ollama: DeepSeek-R1 7B with Levelrail

In the dashboard, open **Apps**, choose **New app**, then **Browse templates**, and select Ollama: DeepSeek-R1 7B. Review the Compose body and deploy.

With the CLI:

```bash theme={"dark"}
levelrail-cli templates deploy ollama-deepseek --name my-ollama-deepseek
```

See the [service template catalog](/templates-and-registry) for how templates work, and [Getting started](/getting-started) if you have not installed Levelrail yet.

## More AI templates

* [AnythingLLM](/self-host/anythingllm)
* [ComfyUI](/self-host/comfyui)
* [Flowise](/self-host/flowise)
* [Flowise (Postgres + Qdrant)](/self-host/flowise-postgres)
* [Jupyter GPU Notebook](/self-host/jupyter-gpu)

All templates are listed in the [self-host gallery](/self-host).


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