---
title: "DeepSeek and Ollama: Advanced AI on bare-metal servers and private cloud with Stackscale"
description: "Deploying DeepSeek on Dedicated Servers and Private Cloud Generative AI and machine learning have revolutionized how businesses process and analyze data. DeepSeek-R1 , an open-source AI model, stands..."
url: https://www.stackscale.com/blog/deepseek-ollama-advanced-ai/
date: 2025-01-30
modified: 2025-01-29
author: "David Carrero"
image: https://www.stackscale.com/wp-content/uploads/2025/01/AI-stackscale.jpg
categories: ["Computing"]
tags: ["artificial Intelligence", "Deepseek", "GPU"]
type: post
lang: en
---

# DeepSeek and Ollama: Advanced AI on bare-metal servers and private cloud with Stackscale

#### **Deploying DeepSeek on Dedicated Servers and Private Cloud**

Generative AI and machine learning have revolutionized how businesses process and analyze data. **DeepSeek-R1**, an open-source AI model, stands out for its **advanced reasoning capabilities, resource optimization, and security**, as it runs locally. By combining **Ollama** with **Stackscale’s infrastructure**, organizations can deploy **DeepSeek-R1 on bare-metal dedicated servers or [private cloud](https://www.stackscale.com/private-cloud/) environments**, ensuring high performance and complete data sovereignty.

### **Why Use DeepSeek-R1 on Private Infrastructure?**

#### **1. Security and Privacy**

DeepSeek-R1 enables **local data processing**, eliminating reliance on external servers and ensuring sensitive information remains protected.

#### **2. Optimized Costs**

Running DeepSeek-R1 on **dedicated GPU servers from Stackscale** reduces the need for cloud-based AI services, eliminating token-based fees or recurring monthly costs.

#### **3. Enhanced Performance with NVIDIA GPUs**

Stackscale’s infrastructure offers **NVIDIA Tesla T4, L4, and L40S GPUs**, designed to accelerate **AI workloads, machine learning, and high-performance computing (HPC)**.

#### **4. Flexibility and Scalability**

Private cloud and **bare-metal servers** allow businesses to **scale resources** based on project demand, ensuring **stability and full control over infrastructure**.

---

### **Installing DeepSeek-R1 with Ollama**

To deploy **DeepSeek-R1 on dedicated servers or private cloud**, **[Ollama](https://github.com/ollama/ollama)** is the recommended tool for managing **local AI models**.

#### **Installation Steps:**

1️⃣ **Install Ollama**

```
curl -fsSL https://ollama.com/install.sh | sh
```

2️⃣ **Download DeepSeek-R1**

```
ollama pull deepseek-r1:8b
```

*(The 8B version provides a balance between performance and resource usage. Other versions are available depending on the GPU.)*

3️⃣ **Run DeepSeek-R1**

```
ollama run deepseek-r1:8b
```

Once started, DeepSeek-R1 will be ready to process queries within the private environment, with **no need for an internet connection**.

#### **Replace 8B with the desired model version:**

- **1.5B parameters:** `ollama run deepseek-r1:1.5b`
- **7B parameters:** `ollama run deepseek-r1`
- **70B parameters** *(Requires 24GB+ VRAM)*: `ollama run deepseek-r1:70b`
- **Full-scale 671B model:** `ollama run deepseek-r1:671b`

---

### **Optimizing GPU Acceleration**

- Ensure **NVIDIA CUDA drivers** are installed.
- Use `ollama list` to check installed models.
- Start the service: `ollama serve`

### **Enhancing Performance with Open WebUI**

For an improved user experience, **[Open WebUI](https://github.com/open-webui/open-webui)** provides a **browser-based interface** to interact with AI models running on Ollama. Key features include:
✅ **Model switching** via `@` commands.
✅ **Conversation tagging and management.**
✅ **Easy model download and removal.**

---

## **Optimizing Performance with NVIDIA GPUs on Stackscale**

For maximum **DeepSeek-R1 performance**, using optimized **GPUs** is recommended. **Stackscale** offers:

| **GPU** | **Memory** | **Tensor Cores** | **Shading Units** | **TFLOPS (FP32)** |
| --- | --- | --- | --- | --- |
| **Tesla T4** | 16 GB GDDR6 | 320 | 2,560 | 8.1 |
| **L4** | 24 GB GDDR6 | 240 | 7,024 | 30.3 |
| **L40S** | 48 GB GDDR6 | 586 | 18,176 | 91.6 |

These [GPUs](https://www.stackscale.com/products/gpu-servers/) **accelerate AI processing**, **reduce execution times**, and **optimize computing resources**.

---

## **Benefits of Using Stackscale for AI and Machine Learning**

✅ **100% European Infrastructure:** Servers in **Madrid and Amsterdam**, ensuring full **data sovereignty**.
✅ **High Availability:** **99.90% SLA**, with **redundant power supply and ultra-fast networks**.
✅ **Complete Isolation:** No resource oversubscription, ensuring **dedicated high-performance computing**.
✅ **24/7 Support:** Specialized technical assistance **in English and Spanish**.

---

### **Conclusion**

Deploying **DeepSeek-R1 with Ollama on Stackscale’s private infrastructure** enables businesses to access an **optimized, secure AI environment with full data control**. With **high-end GPUs** and an **infrastructure designed for demanding workloads**, **Stackscale provides the ideal solution for AI and machine learning projects**.

If you need **more information** about our **dedicated GPU solutions and private cloud**, [contact us](https://www.stackscale.com/contact/), and our team will **help you configure the ideal setup for your project**.