- Processor
Intel/AMD 1 Core - RAM
1GB Memory - DISK
25GB Space - Bandwidth
Upto 1Gbps Unmetered - OS
Windows Server - Panel
Powerful Control Panel - Location
USA (6+ states) - Access
Full Admin Access - Setup
Instant to 4hrs max - Backup
Free/Paid Available
- Processor
Intel/AMD 2 Core - RAM
2GB Memory - DISK
40GB Space - Bandwidth
Upto 1Gbps Unmetered - OS
Windows Server - Panel
Powerful Control Panel - Location
USA (6+ states) - Access
Full Admin Access - Setup
Instant to 4hrs max - Backup
Free/Paid Available
- Processor
Intel/AMD 2 Core - RAM
3GB Memory - DISK
60GB Space - Bandwidth
Upto 1Gbps Unmetered - OS
Windows Server - Panel
Powerful Control Panel - Location
USA (6+ states) - Access
Full Admin Access - Setup
Instant to 4hrs max - Backup
Free/Paid Available
- Processor
Intel/AMD 3 Core - RAM
4GB Memory - DISK
80GB Space - Bandwidth
Upto 1Gbps Unmetered - OS
Windows Server - Panel
Powerful Control Panel - Location
USA (6+ states) - Access
Full Admin Access - Setup
Instant to 4hrs max - Backup
Free/Paid Available
- Processor
Intel/AMD 3 Core - RAM
6GB Memory - DISK
100GB Space - Bandwidth
Upto 1Gbps Unmetered - OS
Windows Server - Panel
Powerful Control Panel - Location
USA (6+ states) - Access
Full Admin Access - Setup
Instant to 4hrs max - Backup
Free/Paid Available
- Processor
Intel/AMD 4 Core - RAM
8GB Memory - DISK
160GB Space - Bandwidth
Upto 1Gbps Unmetered - OS
Windows Server - Panel
Powerful Control Panel - Location
USA (6+ states) - Access
Full Admin Access - Setup
Instant to 4hrs max - Backup
Free/Paid Available
- Processor
Intel/AMD 4 Core - RAM
12GB Memory - DISK
200GB Space - Bandwidth
Upto 1Gbps Unmetered - OS
Windows Server - Panel
Powerful Control Panel - Location
USA (6+ states) - Access
Full Admin Access - Setup
Instant to 4hrs max - Backup
Free/Paid Available
- Processor
Intel/AMD 8 Core - RAM
16GB Memory - DISK
240GB Space - Bandwidth
Upto 1Gbps Unmetered - OS
Windows Server - Panel
Powerful Control Panel - Location
USA (6+ states) - Access
Full Admin Access - Setup
Instant to 4hrs max - Backup
Free/Paid Available
- Processor
Intel/AMD 16 Core - RAM
32GB Memory - DISK
360GB Space - Bandwidth
Upto 1Gbps Unmetered - OS
Windows Server - Panel
Powerful Control Panel - Location
USA (6+ states) - Access
Full Admin Access - Setup
Instant to 4hrs max - Backup
Free/Paid Available
What Is a Self-Hosted AI / LLM Server?
A self-hosted AI server is a virtual private server (VPS) where you install and run open-weight large language models yourself, instead of calling a metered cloud API like OpenAI, Anthropic or Google. You connect over SSH (Linux) or RDP (Windows), install a runtime such as Ollama, llama.cpp, LM Studio or vLLM, download an open model like Llama 3.1 or Mistral, and serve it over a private, OpenAI-compatible API that only you can reach.
Because the model runs on hardware you rent exclusively, every prompt, document and response stays on your machine. There are no per-token charges, no rate limits, and no third party logging or training on your data — you pay one fixed monthly price for the entire server and use it as much as you like.
This is the practical difference: a cloud API bills you for every request forever and sees all your data; a self-hosted LLM server is a one-line monthly cost you fully own. For privacy-sensitive work, high-volume automation, and developers who want to experiment freely, self-hosting is almost always the better economics once usage is steady.
Self-Hosted LLM vs Cloud AI API
A clear side-by-side of the trade-offs, so you can decide what fits your workload.
Factor | Self-Hosted LLM (VostRDP VPS) | Cloud AI API (OpenAI etc.) |
| Cost model | Fixed from $7.99/mo, unlimited requests | Per token — scales with every call |
| Data privacy | Stays on a server you control | Sent to a third-party provider |
| Rate limits | None — your server, your throughput | Quotas and throttling |
| Model choice | Any open model (Llama, Mistral, Qwen, Gemma, Phi) | Only the vendor's models |
| Customization | Full root — fine-tune, quantize, swap models | Limited to API parameters |
| Best for | Steady use, privacy, automation, dev | Spiky traffic, frontier 100B+ models |
Why Self-Host Your AI Model
Full control, real privacy, and a fixed bill instead of metered API costs.
Prompts, documents and model outputs never leave a server you control — essential for legal, medical, financial or internal company data you cannot send to a third-party API.
Pay one flat monthly price, not per request. Batch jobs, bulk summarization and continuous agents that would cost hundreds on a metered API run on a fixed-cost VPS.
Install any open model or runtime — Ollama, vLLM, text-generation-webui — with no vendor lock-in and no content filters you didn't set yourself.
Your server, your throughput. Run non-stop inference, embeddings and RAG pipelines without hitting an API quota or getting throttled mid-job.
Keep a model loaded and serving 24/7 for apps, bots and agents — and pin an exact model version so results never change under you.
Dedicated CPU, RAM and NVMe that aren't shared with noisy neighbours, so inference latency stays consistent.
What You Can Run on a CPU VPS
VostRDP plans are CPU + RAM servers (no GPU), which is exactly right for small and quantized models, embeddings, RAG retrieval and development. With Ollama you can run 3B–8B models such as Llama 3.1 8B, Mistral 7B, Qwen2.5 7B, Gemma 2 9B and Phi-3 Mini in 4-bit quantization — ideal for private chatbots, summarization, classification, data extraction and agent backends.
Quantization (packing model weights into 4-bit instead of 16-bit) is what makes this work on CPU: it cuts memory use roughly 4× with minimal quality loss, so a 7B model that would need ~14GB at full precision runs in ~5–6GB. The table below maps common models to the RAM you should provision. For frontier 70B-class models you would need GPU hosting, which this plan does not include — so we recommend staying in the 3B–13B quantized range for a smooth CPU experience.
Model & RAM Sizing Guide
Pick a plan with headroom above your model size plus a little for the OS and your app.
Model (4-bit quantized) | Approx. RAM needed | Good for | Recommended plan |
| Phi-3 Mini / Gemma 2 2B | ~2–3 GB | Fast chat, classification, edge tasks | 2GB–4GB VPS |
| Llama 3.1 8B / Mistral 7B | ~6–8 GB | General chatbot, RAG, summarization | 8GB VPS |
| Qwen2.5 14B / Gemma 2 9B | ~10–12 GB | Higher-quality reasoning & writing | 16GB VPS |
| Embedding models (BGE, E5) | under 1 GB | Vector search for RAG (run alongside) | any plan |
| 70B+ models | 40 GB+ and a GPU | Frontier quality (not CPU-suitable) | GPU host (not this plan) |
What People Build With It
The most common self-hosted AI workloads our customers run.
An internal assistant that answers from company data without sending anything to OpenAI.
A local LLM plus embeddings and a vector DB (Qdrant, Chroma) to answer questions over your own documents.
Back a 24/7 agent or workflow (n8n, LangChain) with a model you control, at no per-call cost.
A free sandbox to prototype prompts, test open models and build AI features before committing to a provider.
Summarize, classify, translate or extract data across thousands of documents without a metered bill.
Run models in environments where sending data to an external API simply isn't allowed.
How to Set Up a Self-Hosted LLM (Step by Step)
A working private LLM API is about five minutes of setup once your server is live. Here is the typical Ollama flow on a Linux VPS:
- Choose a plan with enough RAM for your target model — 8GB for a single 7B quantized model is a comfortable starting point.
- Deploy and connect: most servers are provisioned instantly (4-hour maximum). Connect over SSH, e.g.
ssh root@your-server-ip. - Install Ollama with one command:
curl -fsSL https://ollama.com/install.sh | sh. - Pull and run a model:
ollama run llama3.1downloads and starts Llama 3.1 8B. Swap inmistral,qwen2.5orgemma2as you like. - Serve it to your apps: Ollama exposes an OpenAI-compatible endpoint at
http://localhost:11434— point your chatbot, RAG pipeline or agent at it, and secure it behind a firewall or reverse proxy. - Scale when ready: upgrade to more RAM for larger models or higher concurrency without migrating servers.
Frequently Asked Questions
Everything you need to know before you deploy.
-
Yes. Small and quantized models (3B–8B in 4-bit) run well on CPU for chat, summarization, classification, embeddings and RAG. VostRDP servers are CPU + RAM (no GPU), which suits these models and development workloads. Very large 70B models need a GPU and are not a fit for this plan — we recommend 3B–13B quantized models for CPU hosting.
-
On a CPU VPS you can run Llama 3.1 8B, Mistral 7B, Qwen2.5, Gemma 2, Phi-3 and similar 3B–8B models in quantized form, plus embedding models. A 7–8B quantized model needs roughly 6–10GB RAM, so choose a plan with headroom above your model size.
-
Yes. The model runs on a single-tenant server you control, so prompts, documents and outputs never leave your machine or get sent to a third-party API. This is why self-hosting is popular for legal, medical, financial and internal company data.
-
As a guide: 3B models ~3–4GB, 7–8B quantized models ~6–10GB, embedding models under 1GB — plus a little extra for your app. Start with a 4GB plan for a single 7B quantized model and scale up for larger models or higher concurrency.
-
Yes, every plan includes full root (Linux) or administrator (Windows) access, so you can install Ollama, llama.cpp, vLLM, a vector database or any other AI tooling with no restrictions.
-
Absolutely. Many customers run a local LLM plus an embedding model and a vector database to power a private chatbot or RAG pipeline. See our AI Chatbot & RAG Hosting and AI Agent Hosting pages for related setups.
-
VostRDP accepts PayPal, PerfectMoney, Bitcoin, Bank Transfer, PayTM, and Indian debit/credit cards.
-
Most self-hosted AI servers are provisioned instantly, with a maximum of 4 hours for higher-tier plans. You'll receive your login details by email and can install Ollama within minutes.
-
For steady or high-volume use, usually yes. A cloud API bills per token with no upper limit, so bulk jobs and always-on agents add up fast. A self-hosted server is a fixed monthly price (from $7.99) for unlimited requests. For occasional, spiky use of a frontier 100B+ model, a managed API can still be simpler.
-
Both work. Ollama runs natively on Windows and Linux, so you can use a Windows VPS over RDP or a Linux VPS over SSH. Linux is slightly lighter on resources, which leaves more RAM for your model, but either is fine.
-
Yes. Ollama and vLLM expose an OpenAI-compatible API, so anything that speaks the OpenAI format — n8n, LangChain, LlamaIndex, Open WebUI, your own app — can point at your server instead of OpenAI by changing the base URL.
-
You can upgrade to a plan with more CPU and RAM at any time without rebuilding — useful when you move from a 7B to a 14B model or need to serve more concurrent users.
