What is AI & LLM Inference?
Running large language models on your own VPS eliminates per-token API costs and keeps your data completely private. With tools like Ollama and Open WebUI, you get a ChatGPT-like experience powered by open-source models like Llama, Mistral, and Phi.
For lighter workloads, smaller models (3-8B parameters) run well on CPU-only VPS instances with 16GB+ RAM. This is perfect for chatbots, content generation, code assistance, and document analysis without sending data to external APIs.
Self-hosted AI is ideal for businesses with data privacy requirements, developers building AI-powered products, and anyone who wants unlimited AI usage at a fixed monthly cost.
$ apt list --installable
Popular AI & LLM Inference Software
Top open-source tools you can self-host on your VPS.
Ollama
Run LLMs locally with a single command. Supports Llama, Mistral, Phi, and dozens of open-source models. Simple CLI and REST API.
Official siteOpen WebUI
Beautiful ChatGPT-like web interface for Ollama. Multi-user support, conversation history, RAG document upload, and model management.
Read our guideLocalAI
OpenAI API-compatible server for running LLMs, image generation, and audio models locally. Drop-in replacement for OpenAI's API.
Official sitevLLM
High-throughput LLM serving engine with PagedAttention. Optimized for production inference workloads with batching and streaming support.
Official siteVPS Specifications
What you need to run ai & llm inference workloads.
$ top --providers --for=ai
Best Providers for AI & LLM Inference
Hand-picked based on specs, pricing, and suitability for ai & llm inference workloads.
Contabo
Unbeatable value — 16GB RAM VPS at $8.99/mo, ideal for running smaller LLMs
Get Started
$ man ai
Frequently Asked Questions
Can I run ChatGPT-like AI on a VPS?
Yes. Ollama with Open WebUI gives you a ChatGPT-like experience using open-source models. Smaller models (7B parameters) run well on 16GB RAM VPS instances.
Do I need a GPU for AI inference?
Not necessarily. CPU inference works well for smaller models (3-8B parameters) and lighter workloads. For larger models or high throughput, GPU servers are recommended.
How much RAM do I need for running LLMs?
As a rule of thumb: 7B parameter models need ~8GB RAM, 13B models need ~16GB, and 70B models need ~48GB. Quantized versions use significantly less.
Is self-hosted AI private?
Completely. Your data never leaves your server. No API calls to external providers, no data logging, no usage tracking. Full data sovereignty.
What models can I run on a budget VPS?
Phi-3 Mini (3.8B), Llama 3.2 (3B), and Mistral 7B (quantized) all run well on 8-16GB RAM. These models handle most chatbot, coding, and writing tasks effectively.
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