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
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?

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

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
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
"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.

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

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