RAM powers your AI lab’s multitasking—handling model loading when VRAM overflows, Proxmox VMs, and n8n workflows alongside Ollama. Match it to your GPU (like RTX 4090’s 24GB) with the 2x rule for smooth self-hosted ops.
Minimum Specs
Your 16-32GB baseline fits 7B-13B models on quantized Llama/Phi, but scale up for context windows and multi-VMs in Proxmox.
- Entry (RTX 4070/12GB VRAM): 32GB DDR5—runs Mistral 7B inference fast.
- Core Lab (RTX 4090/24GB): 64-128GB ECC—feeds vLLM/PyTorch without swapping.
- Beast Mode (Multi-H100): 256GB+ DDR5 ECC—enterprise training, huge MoE models.
Capacity Guide
| GPU VRAM Total | Recommended System RAM | Proxmox Ollama Fit |
|---|---|---|
| 12-24GB | 32-64GB | 7-30B models, OpenWebUI |
| 48GB | 128GB | Multi-instance n8n agents |
| 80GB+ | 256GB ECC | Full fine-tuning stacks |
Go ECC on Threadripper Pro for stability in Docker/K8s nodes—avoids crashes during long runs.
