Ollama is the easiest way to run open AI models like Llama, Qwen, Gemma 4, DeepSeek-R1 and Mistral on your own server. One command downloads and runs a model, and it exposes an API that tools like Open WebUI, n8n and LangChain can use. With a GPU, Ollama responses are many times faster.
🧮 Not sure which GPU you need? Try our AI Model GPU Calculator: pick your model, your context length and usage, and see the VRAM needed, the cheapest hosting and the API cost side by side.
Table of Contents
How Much GPU Do You Need for Ollama?
| Model Size (4-bit) | Examples | VRAM | GPU |
|---|---|---|---|
| 2–4B | gemma4:e4b, llama3.2:3b | 3–5 GB | Any 8 GB GPU |
| 7–9B | llama3.1:8b, qwen3.5:9b | 5–7 GB | RTX 4060, RTX A4000 |
| 12–14B | gemma4:12b, ministral-3:14b | 8–10 GB | RTX A4000 (16 GB) |
| 24–32B | gemma4:31b, deepseek-r1:32b, devstral-small-2 | 15–20 GB | RTX 4090, RTX 5090 |
| 70B | llama3.3:70b, deepseek-r1:70b | ~42 GB | RTX A6000, A40 |
| 120B MoE | gpt-oss:120b | ~65 GB | A100/H100 80GB, RTX PRO 6000 |
Best Ollama Hosting Providers
1. GPU Mart
- Dedicated GPU servers and GPU VPS (US)
- GPUs from P1000 to RTX 5090, RTX PRO 6000, A100 and H100
- One-click AI apps: Ollama, Stable Diffusion, ComfyUI
- GPU VPS from $21/mo · RTX 4090 $409/mo · RTX 5090 from $419/mo · A100 80GB $1,559/mo · H100 $2,099/mo
Pros
- Lowest monthly prices for dedicated GPUs
- Full root/admin access, Windows or Linux
- Multi-GPU servers available
Cons
- Monthly billing only
- US data centers only
GPU Mart can pre-install Ollama and popular models; RTX A4000 VPS $119/month, RTX 4090 $409/month, RTX A6000 $409/month.
2. HOSTKEY
- GPU servers in the EU, UK and US
- RTX 4090, RTX 5090, RTX PRO 6000, A100, H100
- Pre-installed AI stack: Ollama, Open WebUI, ComfyUI
- GTX 1080 Ti from €70/mo · RTX 4090 €279/mo · RTX 5090 €590/mo · A100 80GB €1,300/mo · H100 €1,590/mo
Pros
- Hourly or monthly billing
- GDPR-friendly EU hosting
- Big-VRAM options
Cons
- Popular GPUs sell out
- Setup slower than cloud pods
HOSTKEY delivers servers with Ollama and Open WebUI pre-installed; RTX 4090 from €279/month.
3. RunPod
- Per-second billing in 30+ regions
- Templates: vLLM, ComfyUI, PyTorch, Ollama, Jupyter
- Serverless AI endpoints
- RTX 3090 $0.22/hr · RTX 4090 $0.34/hr · A100 $1.19/hr · H100 $1.99/hr · H200 $3.59/hr (Community Cloud)
Pros
- Very cheap consumer GPUs
- Huge GPU choice up to B200
- Fast start-up
Cons
- Storage billed when stopped
- Community hosts vary
Use the Ollama template on an RTX 4090 ($0.34/hour) or A6000 ($0.33/hour).
4. Vast.ai
- GPU marketplace, 68+ GPU types
- On-demand, interruptible and reserved pricing
- Docker templates for AI tools
- Market pricing: RTX 4090 from ~$0.30/hr · A100 80GB from ~$0.43/hr · interruptible 50%+ cheaper
Pros
- Often the lowest prices
- Per-second billing
- Great for experiments
Cons
- Host quality varies
- Not for strict compliance
Ollama templates on marketplace GPUs from a few cents per hour.
How to Install Ollama on a GPU Server
curl -fsSL https://ollama.com/install.sh | sh
ollama run gemma4:31b
# Expose the API (default port 11434) and add a web UI
docker run -d -p 3000:8080 --gpus all \
-v open-webui:/app/backend/data \
ghcr.io/open-webui/open-webui:ollamaSecure the server before exposing it: put Ollama behind a reverse proxy with authentication, because the API has no login by default.
FAQ
No, but a GPU makes it 5–20× faster. NVIDIA and AMD GPUs are supported.
An RTX 4090 or RTX 5090 runs models up to ~32B; choose 48 GB (RTX A6000) for 70B models.
Ollama is simplest for personal and small-team use; vLLM gives much higher throughput for production APIs with many users.
Conclusion
For a private Ollama server, GPU Mart and HOSTKEY offer ready-made setups at fixed monthly prices; RunPod is best for trying models by the hour.
Prices were checked in September 2026 and change often. Always confirm current pricing on the provider’s website before you order.