This is an automated archive made by the Lemmit Bot.
The original was posted on /r/homelab by /u/NovaAIHub on 2026-03-28 14:37:50+00:00.
After destroying two Proxmox installs trying to get GPU passthrough working, I figured I’d share what actually worked.
The mistakes I made:
- Installing the full CUDA toolkit on the host (wrong ▒@T you only need the driver)
- Using Docker instead of LXC (Docker adds complexity for GPU workloads)
- Not enabling persistence mode (GPU reinitializes on every container start)
- Mixing host/container CUDA versions (they must match)
What actually works:
# Host: Install driver only, no toolkit
apt install -y pve-headers-$(uname -r)
apt install -y nvidia-driver-550
# Enable persistence mode (survives reboots)
nvidia-persistenced --persistence-mode
# LXC container config (Proxmox)
lxc.cgroup2.devices.allow: c 195:* rwm
lxc.cgroup2.devices.allow: c 509:* rwm
lxc.mount.entry: /dev/nvidia0 dev/nvidia0 none bind,optional,create=file
lxc.mount.entry: /dev/nvidiactl dev/nvidiactl none bind,optional,create=file
lxc.mount.entry: /dev/nvidia-uvm dev/nvidia-uvm none bind,optional,create=file
lxc.mount.entry: /dev/nvidia-uvm-tools dev/nvidia-uvm-tools none bind,optional,create=file
Inside the container:
# Container: Match host driver version, no toolkit needed
apt install -y nvidia-driver-550
nvidia-smi # Should show your GPU
Container vs Docker for AI:
LXC is simpler because:
- No nested virtualization
- Direct device access
- Same isolation benefits
- Easier debugging
Hardware I’m using:
- RTX 3090 24GB (used from eBay, ~$700)
- 128GB RAM
- Ryzen 7900X
Runs Llama 3.2 11B at ~45 tokens/sec, Qwen 2.5 14B at ~30 tokens/sec.
Happy to answer questions in comments. I documented everything in more detail if anyone wants the full setup - see link in bio.


Same here. Finally got it working by setting the VM’s chipset to ‘PCIE 1:0’ and enabling ‘Assign special device’ for the NVIDIA card in the settings.