How Much RAM Does Your Homelab Need? Practical Benchmarks

RAM: The Often Underestimated Resource

"How much RAM do I need?" is one of the most common homelab questions. Too little and services crash. Too much and you waste money. Let's look at real numbers.

Service RAM Usage (Idle/Active)

| Service           | Idle RAM  | Active RAM | Notes                    |
|-------------------|-----------|------------|--------------------------|
| Pi-hole           | 50MB      | 100MB      | Very lightweight         |
| Vaultwarden       | 30MB      | 50MB       | Extremely efficient      |
| Traefik           | 50MB      | 100MB      | Depends on routes        |
| Portainer         | 100MB     | 150MB      | Web UI overhead          |
| Nextcloud         | 200MB     | 500MB      | PHP memory hungry        |
| Plex              | 300MB     | 1-2GB      | Transcoding uses more    |
| Jellyfin          | 200MB     | 1-2GB      | Similar to Plex          |
| Home Assistant    | 300MB     | 500MB      | Depends on integrations  |
| Immich            | 500MB     | 2-4GB      | ML processing intensive  |
| Paperless-ngx     | 300MB     | 800MB      | OCR uses spikes          |
| GitLab            | 2GB       | 4-8GB      | Resource heavy           |
| Gitea             | 100MB     | 200MB      | Very efficient           |

Starter Homelab (8GB RAM)

With 8GB, you can comfortably run:

• Operating system overhead: ~1GB
• Pi-hole: 100MB
• Vaultwarden: 50MB
• Traefik: 100MB
• Portainer: 150MB
• Jellyfin: 500MB (no transcoding)
• Nextcloud: 400MB
• Buffer for spikes: 2GB
• Total: ~4.3GB used, 3.7GB buffer

Recommended Homelab (16GB RAM)

16GB opens up more possibilities:

• Everything from 8GB tier
• Home Assistant: 500MB
• Immich: 2GB
• Paperless-ngx: 500MB
• Multiple small services: 1GB
• Comfortable buffer: 4GB+

This is the sweet spot for most homelabs.

Power User (32GB+ RAM)

For virtualization or heavy workloads:

• Multiple VMs with Proxmox
• GitLab or development environments
• Large databases
• Machine learning workloads
• Many concurrent services

Tips for Managing RAM

• Set limits: Use Docker memory limits to prevent runaway containers
• Monitor usage: Use docker stats or Prometheus/Grafana
• Choose efficient alternatives: Gitea over GitLab, Alpine-based images
• Enable swap: Not ideal but prevents OOM kills
• Upgrade when needed: RAM is usually the cheapest upgrade

The Bottom Line

Start with 16GB if possible. It gives you room to grow without immediate upgrades. If budget is tight, 8GB works for a basic setup but you'll hit limits quickly.

Remember: it's easier to upgrade RAM later than to deal with constant OOM kills and service crashes.