AI VPS — Model Serving — Inference APIs

AI VPS — Deploy AI Models
& Inference APIs

Host AI inference APIs, embedding servers, classification models, and LLM wrappers on a dedicated Cloud VPS. Serve AI predictions 24/7 without per-inference billing from managed AI platforms.

AI Model Serving REST Inference API No Per-Call Billing Private Inference From $14/mo
Deploy Now — From $5/mo See Recommended Stack
Inference
API Serving
No
Per-Call Fees
Private
Model Hosting
$14
Recommended /mo
AMD Ryzen CPU
DDR5 RAM
NVMe SSD
10 Gbps Port
DDoS Protected
Full Root Access
35+ Locations
Instant Deploy
Why VPS?

Why Host AI Models on a Cloud VPS?

OpenAI charges per token. Hugging Face Inference API has rate limits. A VPS hosts your AI models privately — serve predictions 24/7 at a flat monthly cost with no per-inference billing.

No Per-Token / Per-Call Billing

OpenAI API charges $0.002–$0.06 per 1K tokens. At moderate usage, a $14/mo VPS serving a local model is significantly cheaper. Fixed infrastructure cost regardless of inference volume.

Private Model Inference

Send sensitive business data, customer PII, or proprietary documents to your own AI model — not to OpenAI or third-party APIs. Complete data privacy for AI inference.

Small LLMs on CPU

Quantized LLaMA 3 (4-bit GGUF) and Mistral models run on CPU with 4-8 GB RAM via llama.cpp. Slower than GPU but suitable for moderate traffic inference APIs without GPU cost.

Serve Embeddings & Classifiers

Sentence transformers for embeddings, scikit-learn classifiers, spaCy NLP models, and custom fine-tuned models serve predictions via FastAPI REST endpoints — fast on CPU for non-LLM tasks.

Recommended Stack

Recommended Tech Stack

The optimal software stack pre-configured for this use case on a Host4Fun Cloud VPS.

llama.cpp
CPU LLM inference
Ollama
Local LLM management
FastAPI
Inference REST API
HuggingFace Transformers
Model library
sentence-transformers
Embedding models
Gunicorn + Nginx
Production serving
PostgreSQL + pgvector
Vector storage
Redis
Inference caching
Quick Deploy

Deploy in Minutes

Get up and running on a fresh Host4Fun Cloud VPS with these commands.

root@vps — quick deploy
# Install Ollama for easy local LLM management
[root@vps ~]# curl -fsSL https://ollama.com/install.sh | sh
[OK] Ollama installed

# Pull and run a quantized LLaMA 3 model (4GB RAM)
[root@vps ~]# ollama pull llama3.2:3b && ollama run llama3.2:3b "Hello, world!"
[OK] LLaMA 3.2 3B running on CPU

# Serve embeddings with sentence-transformers + FastAPI
[root@vps ~]# pip install fastapi uvicorn sentence-transformers
# FastAPI endpoint: POST /embed → vector
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("all-MiniLM-L6-v2")
[root@vps ~]# uvicorn app:app --host 0.0.0.0 --port 8000
[OK] Embedding API live at https://ai.yourdomain.com/embed
[root@vps ~]#
Why Host4Fun

Why Host4Fun Cloud VPS?

Everything that makes Host4Fun Cloud VPS the ideal infrastructure for your use case.

Ollama — Local LLM Management

Ollama simplifies running quantized LLMs locally — pull models, manage versions, and expose an OpenAI-compatible REST API. Run LLaMA 3, Mistral, Gemma, Phi-3, and other models with simple CLI commands.

Flat Cost vs Per-Token APIs

OpenAI GPT-4o costs $0.005/1K input tokens. At 1M tokens/day, that's $150+/mo. A $14/mo VPS with a quantized Mistral 7B serves the same inference volume at fixed cost — 90%+ savings at scale.

Private Inference — No Data Leakage

Customer conversations, medical records, legal documents, and financial data stay on your server. Private LLM inference with llama.cpp or Ollama ensures sensitive inputs never reach third-party API endpoints.

Embeddings + pgvector RAG

sentence-transformers generates embeddings for documents. pgvector stores embeddings in PostgreSQL. Build RAG (Retrieval-Augmented Generation) pipelines entirely on your VPS — no OpenAI embeddings API needed.

ML Model Inference APIs

Serve scikit-learn classifiers, XGBoost models, and spaCy NLP pipelines as FastAPI endpoints. CPU inference for classification, regression, and NLP tasks is fast and doesn't require GPU hardware.

OpenAI-Compatible API

Ollama exposes an OpenAI-compatible REST API at /api/chat and /api/generate. Drop-in replacement for OpenAI API calls — point your application's OPENAI_BASE_URL to your VPS and switch from GPT to local models transparently.

Comparison

VPS vs Alternatives

How a self-managed Host4Fun Cloud VPS compares to shared hosting and managed cloud services.

FeatureHost4Fun Cloud VPSOpenAI APIHuggingFace InferenceReplicate
Data Privacy
Per-Call Cost$0 (flat $14/mo)$0.002–$0.06/1K tokensVaries$0.001+/run
Custom Models
OpenAI-Compatible API (Ollama)
Monthly Cost (1M tokens)$14/mo flat$100–$500+$50+$30+
Use Cases

Who Uses This VPS?

Real use cases from developers, agencies, and businesses running on Host4Fun Cloud VPS.

Private Business AI

Run AI assistants on company data without sending business information to OpenAI. Private LLM inference for internal document Q&A, customer support automation, and business analytics.

Semantic Search & RAG

Build RAG applications — embed documents with sentence-transformers, store in pgvector, retrieve relevant chunks, and generate answers with a local LLM. Complete private RAG pipeline on one VPS.

AI-Powered Applications

Integrate local LLM inference into web applications — text classification, summarization, translation, and generation features without per-API-call billing. FastAPI wrapper exposes inference as a REST endpoint.

AI Development & Testing

Develop AI features against a local LLM endpoint before using expensive GPT-4 in production. Test prompts, tune parameters, and iterate quickly against a free local model endpoint.

GDPR-Compliant AI

EU companies processing customer data with AI must ensure GDPR compliance. Self-hosted inference on an EU VPS (Frankfurt, Amsterdam) keeps data in the EU without relying on US API providers.

AI Learning & Research

Researchers and students studying LLMs, fine-tuning techniques, and AI application development need a server with sufficient RAM to load and experiment with quantized models.

Pricing

Choose Your VPS Plan

All plans include AMD Ryzen CPU, DDR5 RAM, NVMe SSD, 10 Gbps, DDoS protection, and dedicated IPv4.

Starter
 
$5/mo
 
  • 1 vCPU AMD Ryzen
  • 1 GB DDR5 RAM
  • 15 GB NVMe SSD
  • 1 TB Bandwidth
  • 10 Gbps Port
  • Full Root Access
  • DDoS Protection
Get Started
Basic
 
$7/mo
 
  • 2 vCPU AMD Ryzen
  • 2 GB DDR5 RAM
  • 30 GB NVMe SSD
  • 4 TB Bandwidth
  • 10 Gbps Port
  • Full Root Access
  • DDoS Protection
Get Started
Most Popular
Professional
AI optimal — RAM for model loading + serving
$14/mo
 
  • 4 vCPU AMD Ryzen
  • 4 GB DDR5 RAM
  • 60 GB NVMe SSD
  • 8 TB Bandwidth
  • 10 Gbps Port
  • Full Root Access
  • DDoS Protection
Deploy Now
Business
 
$28/mo
 
  • 6 vCPU AMD Ryzen
  • 8 GB DDR5 RAM
  • 120 GB NVMe SSD
  • 16 TB Bandwidth
  • 10 Gbps Port
  • Full Root Access
  • DDoS Protection
Get Started

Annual billing charged as one payment. Prices exclude taxes.

FAQ

Frequently Asked Questions

Yes — quantized models (GGUF 4-bit format) run on CPU via llama.cpp or Ollama. LLaMA 3.2 3B needs ~3 GB RAM and runs at 5-20 tokens/second on AMD Ryzen. Mistral 7B (4-bit) needs ~6 GB RAM. Suitable for moderate-traffic APIs and development — not for high-throughput production.
Ollama is a tool for running quantized LLMs locally. It manages model downloads, provides a simple CLI to run models, and exposes an OpenAI-compatible REST API. Pull models with `ollama pull modelname` and query them via `curl http://localhost:11434/api/generate`.
On the Professional plan (4 vCPU AMD Ryzen): LLaMA 3.2 3B generates 10-25 tokens/second. Mistral 7B (4-bit) generates 3-8 tokens/second. Suitable for internal tools and low-traffic APIs — for high-throughput production inference, GPU infrastructure is recommended.
sentence-transformers generates semantic embedding vectors from text. Popular models (all-MiniLM-L6-v2) use ~100 MB RAM and generate embeddings in <1ms on CPU. The Starter plan ($5/mo, 1 GB RAM) handles embedding model serving with pgvector storage.
(1) Chunk documents, generate embeddings with sentence-transformers. (2) Store embeddings in PostgreSQL with pgvector extension. (3) On query: embed the question, find similar chunks with vector similarity search. (4) Pass retrieved chunks as context to a local LLM (Ollama). All on one VPS.
For low-to-moderate traffic inference (classification models, embeddings, small LLMs under 10 requests/second), yes. For high-volume LLM inference, GPU infrastructure is needed. VPS is excellent for: RAG pipelines, embedding generation, classifier APIs, and internal AI tools.
Related Pages
Python VPSData Science VPSJupyter VPSPostgreSQL + pgvectorDeveloper VPS

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Private LLM inference. Embeddings API. No per-token billing. Ollama + FastAPI. From $14/mo.

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