Ollama Hosting on CPU Servers — No GPU Needed

Pre-installed with Ollama runtime, OpenWebUI interface, and Llama 3.1 8B model. Perfect for developers, data scientists, and privacy-focused teams who want to run LLMs without cloud dependencies.
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Deploy Ollama in 3 Simple Steps.

1

Choose Your Server

VDS Developer

Solo developer or learning?

Dedicated Team

Team of 5-10 people?

Dedicated Production

Production or high availability?

2

Select "OpenWebUI with Ollama"

During checkout, under “Software”:
  • Click the Apps Menu
  • Select OpenWebUI
  • Complete Checkout
Deployment time: 5-10 minutes depending on server configuration.
3

Start Chatting

Once deployed, you'll receive:
  • OpenWebUI URL
  • SSH Credentials
  • Quick start guide
No configuration needed. No terminal required. Just open the URL and start inferencing!

Why Host Ollama on Hivelocity?

Complete Data Privacy

Your conversations, prompts, and model outputs never leave your server. Unlike AI services (ChatGPT, Claude, etc.), you maintain complete control over your data.

Perfect for:
  • Healthcare data processing
  • Legal document analysis
  • Financial services applications
  • Any regulated industry requiring data sovereignty
1/5th the Cost of GPU Hosting

CPU-optimized Ollama runs 7B-8B models efficiently without expensive GPU hardware.

Price Comparison:
  • GPU dedicated servers: $1,500-$5,000/month
  • Cloud GPU instances (AWS): $400-$1,000/month + egress
  • Hivelocity Ollama servers: $65-$880/month

For 80% of Ollama use cases (development, internal tools, chatbots), CPU is sufficient.

Lower Latency Than Cloud

No API round-trips to OpenAI/Anthropic. Inference happens directly on your server.

Latency Comparison:
  • OpenAI API: 200-800ms (network + queue + inference)
  • Your Ollama server: 50-200ms (inference only, no network)
  • Plus: No rate limits. No quotas. No vendor outages affecting your application.
Greater Control and Flexibility
    • Run any ollama-supported model (Llama, Mistral, CodeLlama, Gemma, etc.)
    • Customize system prompts and parameters
    • Update models on your schedule
    • No vendor lock-in or API changes breaking your code

Skip the 4-Hour Setup. Start Chatting in Minutes.

Start inferencing immediately. No Docker knowledge required. No terminal commands needed.

The Traditional Way (DIY Setup)

  • Provision a server (30-60 minutes)
  • Set up OpenWebUI interface (45 minutes)
  • Download and configure models (20-60 minutes)
  • Configure networking, auth, and security (60+ minutes)
Total setup time:

3-4 hours

(and that's if everything works perfectly)

The Hivelocity Way (One-Click)

  • Select your server (VDS or Instant Dedicated)
  • Choose "OpenWebUI with Ollama" from Apps menu
  • Complete checkout
  • Access your OpenWebUI URL and start chatting
Total setup time:

5-10 minutes

from checkout to first inference

No GPU? No Problem.

While many LLMs require expensive GPU acceleration, Ollama is optimized for CPU and performs impressively on models like:

Llama 3.1 8B

(pre-installed with our One-Click App)

Mistral 7B

(fast, capable, great for chatbots)

CodeLlama 7B

(code completion and generation)

Gemma 7B

(Google's efficient open model)

These models strike a solid balance between performance and capability, making them ideal for running locally on CPU-powered servers.

View Server Options

Real-World Performance

CPU-based inference with 4-bit quantized models (Q4_K_M)

Model
Llama 3.1 8B (pre-installed)
Other 7B-8B models
13B models
Concurrent users
VDS Developer
8-10 tok/s
9-11 tok/s
Too slow
1-2
Dedicated Team
15-18 tok/s
15-19 tok/s
8-12 tok/s
5-10
Dedicated Team
18-25 tok/s
19-26 tok/s
12-16 tok/s
15-20+

vs Your Laptop

  • 3-5X faster than M2 MacBook Pro
  • More RAM for larger models
  • No thermal throttling
  • Always accessible

vs GPU Servers

  • GPU: 50-150 tok/s but $1,500-$5K/mo
  • CPU: 10-25 tok/s at $65-$880/mo
  • Ideal when cost matters more than extreme speed

vs Cloud LLM APIs

  • Similar latency but usage-based pricing
  • Example: 1M tokens/day = $45K/year
  • Hivelocity: $780-$10.5K/year*

Perfect for AI Applications.

Internal company chatbot
Build AI assistants for your team without data leaving your infrastructure.
  • HR policy chatbot
  • Documentation search
  • IT helpdesk assistant
  • Sales enablement bot
Code assistants
Help developers write better code faster with private code implementation.
  • Code completion & generation
  • API documentation Q&A
  • Code review assistance
  • Architecture decisions
RAG Pipelines
Build retrieval-augmented generation on your private knowledge base.
  • Legal document analysis
  • Medical records
  • Research paper synthesis
  • Customer support knowledge base
Model Development
Prototype and test AI features before scaling to production.
  • Prompt engineering experiment
  • Multi-modal comparison
  • RAG pipeline development
  • Fine-tuning preparation
Education & Learning
Learn LLM deployment without expensive infrastructure.
  • University AI courses
  • Corporate AI training
  • Personal skill development
  • Research experiments
Regulated Industries
Deploy AI with strict data privacy requirements.
  • Healthcare: Patient data analysis
  • Finance: Risk assessment
  • Legal: Contract analysis
  • Government: Classified processing
"In Hivelocity we finally found a data center provider that delivers reliable, fast network connectivity, the best hardware, and quality support. Their support team responds to us promptly in minutes — not hours. The difference between IBM SoftLayer and Hivelocity is night and day. Hivelocity has quality service, proven uptime records, a quality network, premium hardware, and responsive technical support."
Fabio Covolo Mazzo
CIO & Co-Founder, Klink AI

Frequently Asked Questions.

Yes! Our servers are CPU-only, and Ollama is specifically optimized for CPU inference. Models like Llama 3.1 8B (pre-installed) and other 7B-8B models run smoothly on CPU-powered servers with Q4 quantization.


When CPU is perfect:

  • 7B-13B models (80% of use cases)
  • 1-20 concurrent users
  • Development, testing, internal tools
  • Cost is a primary concern

When you need GPU:

  • Running 70B+ parameter models
  • Serving 50+ concurrent users
  • Requiring <100ms latency

Pre-installed: Llama 3.1 8B (ready to use immediately)
Recommended for CPU (smooth performance):

  • Llama 3/3.1 8B
  • Other 7B-8B models available in Ollama library

Possible on Dedicated tiers (slower):

  • 13B-14B models with Q4 quantization

You can add any Ollama-supported model after deployment.

Completely. Everything runs on your dedicated server:

  • Your conversations never leave your infrastructure
  • Your prompts aren’t sent to third-party AI services
  • Your model outputs stay on your server
  • You control who has access

Unlike cloud AI services:

  • OpenAI/Anthropic: Your data goes to their servers
  • Hivelocity: Your data stays on YOUR server

Perfect for: Healthcare (HIPAA), finance (SOC 2), legal, government, or any regulated industry requiring data sovereignty.

Yes! After deployment, you can pull any Ollama-supported model.


Via OpenWebUI (easiest):

  • Click “Models” in sidebar
  • Search Ollama library
  • Click “Pull” on any model
  • Model downloads and appears automatically

VDS (Virtual Dedicated Server):

  • Lower cost ($65/month)
  • Quick deployment (~7 min)
  • Virtualized (small performance overhead)
  • Limited RAM (24GB)

Best for: Learning, solo development, budget-conscious projects

Instant Dedicated (Bare Metal):

  • Higher performance (no virtualization)
  • More RAM (64GB-512GB)
  • Consistent performance (no noisy neighbors)
  • Higher cost ($249-$880/month)

Best for: Teams, production, multiple models, high reliability

Simple rule: Start with VDS for learning. Upgrade to Dedicated when you need better performance or team access.

What you DON’T need to know:

  • Docker
  • Linux server administration
  • Networking configuration
  • Security hardening
  • Ollama installation steps

What you DO need:

  • How to use a web browser (access OpenWebUI URL)
  • Basic chat interface usage (like ChatGPT)
  • (Optional) SSH for advanced model management

Most users never need to SSH and only use the web interface.

Yes, flexible upgrade paths:

From VDS → Dedicated Team: Migrate your models and data with 1-hour downtime. We can assist.

From Dedicated Team → Dedicated Production: Upgrade to more powerful server with minimal downtime.

Upgrade process:

  1. Contact support to schedule
  2. We provision new server with One-Click App
  3. You migrate data (or we assist)
  4. Update DNS to point to new server
  5. Old server decommissioned

Get a Quote from Our Experts Today.