N5 Max: Proxmox Strix Halo with Docker, ROCm FP4 and MTP - Ultimate Setup Guide

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Strix Halo ROCmFP4 + MTP LLM Inference Guide

Hardware: AMD Ryzen AI MAX+ 395 (16C/32T) + Radeon 8060S (gfx1151) + 64 GB unified memory

MINISFORUM N5 MAX AI NAS | AMD Ryzen AI Max+ 395 | 126 TOPS NPU | Radeon™ 8060S graphics

Last tested: 2026-06-06 (Proxmox VE 9.1.1, kernel 6.17.2-1-pve, ROCm 7.2.1)

Background

TODO: video goes here, explainer

My vision for this is to have an “all-in-one” home appliance for AI, Virtual Machines, internet ingress/egress (experimenting with Pangolin on this currently, maybe for a future video).. Home Assistant.. you name it. In a nutshell we’re using Proxmox as our NAS OS then setting up an LXC with full access to the underlying hardware for AI workloads via Docker! The best of both worlds. Or something.

This thing is a beast for any use case.

Models tested:

Qwopus3.6-27B-v2 (ROCmFP4, 14 GB),
Qwen3.6-27B (Q8_0, ~27 GB)
TODO?

Table of Contents

Overview & What’s New Architecture Overview Prerequisites & System Inventory Phase 1: Proxmox Host Preparation Phase 2: Kernel Boot Parameters (Critical) Phase 3: Create the LXC Container Phase 4: GPU Passthrough to LXC Phase 5: ROCm Installation (Inside LXC) Phase 6: Build the ROCmFP4 llama.cpp Fork Phase 7: Build Stock llama.cpp (for Q8 baseline) Phase 8: Download Models Phase 9: Run Inference Phase 10: Benchmarks vLLM Docker Setup (Alternative Backend) Troubleshooting Reference: Key Community Resources

Overview & What’s New

This guide covers running ROCmFP4-quantized models (a custom 4-bit format with native FP4 tensor layouts optimized for AMD GPUs) on Strix Halo hardware using a custom llama.cpp fork with Multi-Token Prediction (MTP) support.

Most of the work was done on the Minisforum N5 Max NAS, but I also validated on the GMK Tek Strix Halo, The Minisforum S1 Max and The Framework Desktop Strix Halo machine they offer.

This was quite an adventure to get setup. Many thinks to kyz0 and other resources linked throughout this guide.

What’s different from standard llama.cpp ROCm guides:

Architecture Overview

Proxmox Host (kernel 6.17.2-1-pve)
  ├── amdgpu.ko (in-tree, gfx1151 support)
  ├── /dev/dri/card1       ───┐
  ├── /dev/dri/renderD128  ───┤── LXC bind-mount
  ├── /dev/kfd             ───┤
  └── /dev/accel/accel0    ───┘  (NPU — not used for LLM today)
        │
  LXC Container (Ubuntu 24.04, privileged, 56 GB RAM)
    ├── ROCm 7.2.1 userspace (no DKMS — host kernel has drivers)
    ├── rocmfp4-llama fork (built for gfx1151 + ROCmFP4)
    ├── stock llama.cpp (for Q8 baseline comparisons)
    ├── Docker (for vLLM ROCm container)
    └── Models:
        ├── Qwopus3.6-27B-v2-MTP-ROCmFP4 (14 GB)
        └── Qwen3.6-27B-Q8_0 (~27 GB)

Prerequisites & System Inventory

Hardware Requirements

Verify your hardware

cat /proc/cpuinfo | grep "model name" | head -1

lspci | grep -i display

grep MemTotal /proc/meminfo

ls -la /dev/dri/* /dev/kfd /dev/accel/accel0

uname -r

pveversion

Expected output

model name : AMD RYZEN AI MAX+ 395 w/ Radeon 8060S
90:00.0 Display controller: AMD/ATI Strix Halo [Radeon 8060S Graphics]
MemTotal:       63407216 kB  (~60.5 GB)
crw-rw---- 1 root render 226, 128 /dev/dri/renderD128
crw-rw---- 1 root render 234,   0 /dev/kfd
6.17.2-1-pve
pve-manager/9.1.1

Phase 1: Proxmox Host Preparation

4.1 Enable the no-subscription repository

rm /etc/apt/sources.list.d/pve-enterprise.sources

cat > /etc/apt/sources.list.d/pve-no-subscription.sources << 'EOF'
Types: deb
URIs: http://download.proxmox.com/debian/pve
Suites: trixie
Components: pve-no-subscription
Signed-By: /usr/share/keyrings/proxmox-archive-keyring.gpg
EOF

cat > /etc/apt/sources.list.d/ceph.sources << 'EOF'
Types: deb
URIs: http://download.proxmox.com/debian/ceph-squid
Suites: trixie
Components: no-subscription
Signed-By: /usr/share/keyrings/proxmox-archive-keyring.gpg
EOF

apt update

4.2 Install necessary tools

apt install -y curl wget pve-headers build-essential

Phase 2: Kernel Boot Parameters (Critical)

5.1 Why these parameters

The Strix Halo GPU (gfx1151

) needs explicit boot parameters to access all 64 GB of unified memory. Without these, ROCm memory allocation is severely limited.

| Parameter | Purpose | amd_iommu=off | Disables IOMMU for the GPU. Required for the GPU to access all system RAM as unified memory. Without this, ROCm memory allocation is capped at ~2 GB. | amdgpu.gttsize=131072 | Sets the GTT (Graphics Translation Table) size to 128 GB. This is a ceiling — it tells the GPU it can map up to 128 GB of system RAM. On a 64 GB system, this effectively enables full unified memory access. The value is in megabytes: 131072 MB = 128 GB. | ttm.pages_limit=31457280 | Increases the TTM (Translation Table Manager) page limit. Prevents allocation failures when large models. Value = number of 4 KB pages. |

Note on GTT sizing: The system has ~60.5 GB of usable RAM. Setting gttsize=131072

(128 GB) is safe — it’s just an upper bound. The GPU will only use what’s physically available. For a 64 GB system, a value of ~57344 (56 GB) would also work, but 131072 is harmless and future-proofs the config for systems with more RAM.

5.2 Apply the parameters

sed -i 's/GRUB_CMDLINE_Linux_DEFAULT="quiet"/GRUB_CMDLINE_LINUX_DEFAULT="quiet amd_iommu=off amdgpu.gttsize=131072 ttm.pages_limit=31457280"/' /etc/default/grub
update-grub
reboot

5.3 Verify after reboot

cat /sys/class/drm/card1/device/mem_info_gtt_total

cat /proc/cmdline | grep -o 'amdgpu.gttsize=[^ ]*\|amd_iommu=[^ ]*\|ttm.pages_limit=[^ ]*'

ls -la /dev/kfd

Phase 3: Create the LXC Container

6.1 Choose a template

Ubuntu 24.04 is recommended over Debian 13 for ROCm compatibility:

pveam available | grep ubuntu-24
pveam download local ubuntu-24.04-standard_24.04-2_amd64.tar.zst

6.2 Create the container

Must be privileged for GPU device access:

CT_ID=100
CT_HOSTNAME=strix-ai
CT_STORAGE=local-lvm

pct create $CT_ID local:vztmpl/ubuntu-24.04-standard_24.04-2_amd64.tar.zst \
  --storage $CT_STORAGE \
  --memory 57344 \
  --swap 0 \
  --cores 16 \
  --unprivileged 0 \
  --hostname $CT_HOSTNAME \
  --net0 name=eth0,bridge=vmbr0,ip=dhcp \
  --rootfs $CT_STORAGE:100 \
  --features nesting=1

Resource notes:

--memory 57344

— 56 GB RAM (leaves ~4 GB for Proxmox host) --swap 0

— No swap. With unified memory, swapping would thrash the GPU. --cores 16

— All 16 physical cores. --unprivileged 0

— Privileged container. Required for GPU device nodes to have correct ownership. --rootfs 100

— 100 GB minimum. 300 GB recommended if storing models locally.

6.3 Start and set up

pct start $CT_ID
pct enter $CT_ID

apt update && apt upgrade -y
apt install -y curl wget git build-essential cmake python3 python3-pip sudo

Phase 4: GPU Passthrough to LXC

7.1 Identify device nodes on the host

From the Proxmox host:

ls -la /dev/dri/* /dev/kfd

Expected:

crw-rw---- 1 root video  226,   1 /dev/dri/card1
crw-rw---- 1 root render 226, 128 /dev/dri/renderD128
crw-rw---- 1 root render 234,   0 /dev/kfd

Note the render group GID:

getent group render

7.2 Add device passthrough to container config

Edit /etc/pve/lxc/$CT_ID.conf

on the Proxmox host:

cat >> /etc/pve/lxc/$CT_ID.conf << 'EOF'

lxc.cgroup2.devices.allow: c 226:* rwm
lxc.cgroup2.devices.allow: c 234:* rwm

lxc.mount.entry: /dev/dri dev/dri none bind,optional,create=dir
lxc.mount.entry: /dev/kfd dev/kfd none bind,optional,create=file
EOF

7.3 Restart and verify

pct stop $CT_ID
pct start $CT_ID

pct enter $CT_ID
ls -la /dev/dri/* /dev/kfd

Phase 5: ROCm Installation (Inside LXC)

8.1 Add the AMD ROCm repository

wget -q -O - https://repo.radeon.com/rocm/rocm.gpg.key | gpg --dearmor > /etc/apt/trusted.gpg.d/rocm.gpg

echo "deb [arch=amd64] https://repo.radeon.com/rocm/apt/7.2.1 noble main" > /etc/apt/sources.list.d/rocm.list

cat > /etc/apt/preferences.d/rocm-pin << 'EOF'
Package: *
Pin: release o=repo.radeon.com
Pin-Priority: 600
EOF

apt update

8.2 Install ROCm userspace (no DKMS)

Critical: Do NOT install rocm-dkms

. The amdgpu and amdkfd drivers are already in the Proxmox host kernel.

apt install -y rocm-hip-sdk rocwmma-dev

Also install Vulkan SDK (needed by the ROCmFP4 fork build):

apt install -y libvulkan-dev vulkan-tools

8.3 Set up memlock limits (Critical!)

ROCm needs to lock GPU memory pages. The default ulimit is 8 MB — far too low for LLM models:

echo 'root soft memlock unlimited' >> /etc/security/limits.conf
echo 'root hard memlock unlimited' >> /etc/security/limits.conf

ulimit -l unlimited

8.4 Verify ROCm

/opt/rocm/bin/rocminfo

Expected output should show:

Name:                    gfx1151
Marketing Name:          Radeon 8060S Graphics
Compute Unit:            40
Max Clock Frequency:     2900 MHz

Pool Info:
  Segment:               GLOBAL; FLAGS: COARSE GRAINED
  Size:                  125829120 KB  (120 GB GTT — full unified memory)

Also check:

/opt/rocm/bin/rocm-smi

Phase 6: Build the ROCmFP4 llama.cpp Fork

9.1 Clone the fork

cd /root
git clone https://github.com/charlie12345/rocmfp4-llama.git
cd rocmfp4-llama
git checkout mtp-rocmfp4-strix

9.2 Build

export PATH=/opt/rocm/bin:/opt/rocm/llvm/bin:$PATH
export HIP_PATH=/opt/rocm
export ROCM_PATH=/opt/rocm
export ROCM_WMMA_INCLUDE=/opt/rocm/include
export GGML_HIP_ROCWMMA_FATTN=ON
export CMAKE_HIP_ARCHITECTURES=gfx1151
export JOBS=$(nproc)

bash scripts/build-strix-rocmfp4-mtp.sh

Note: The build script enables Vulkan by default, which requires libvulkan-dev

. If you get Vulkan compilation errors (e.g., spv

namespace issues), reconfigure with -DGGML_VULKAN=OFF

:

cmake -S . -B build-strix-rocmfp4 \
  -DCMAKE_BUILD_TYPE=Release \
  -DGGML_HIP=ON \
  -DGGML_HIP_ROCWMMA_FATTN=ON \
  -DGGML_HIP_FORCE_MMQ=ON \
  -DGGML_VULKAN=OFF \
  -DGGML_CUDA=OFF \
  -DCMAKE_HIP_ARCHITECTURES=gfx1151 \
  -DLLAMA_BUILD_SERVER=ON
cmake --build build-strix-rocmfp4 -j$(nproc) --target llama-cli llama-server llama-bench

9.3 Verify

HSA_OVERRIDE_GFX_VERSION=11.5.1 \
GGML_HIP_ENABLE_UNIFIED_MEMORY=1 \
./build-strix-rocmfp4/bin/llama-cli --list-devices

Expected:

Available devices:
  ROCm0: Radeon 8060S Graphics (122880 MiB, 4096 MiB free)

Phase 7: Build Stock llama.cpp (for Q8 baseline)

For comparing ROCmFP4 against standard quantization formats:

cd /root
git clone https://github.com/ggml-org/llama.cpp.git stock-llama
cd stock-llama

HIPCXX="$(hipconfig -l)/clang" \
HIP_PATH="$(hipconfig -R)" \
cmake -S . -B build \
  -DGGML_HIP=ON \
  -DGPU_TARGETS=gfx1151 \
  -DGGML_HIP_ROCWMMA_FATTN=ON \
  -DGGML_HIP_NO_VMM=ON \
  -DGGML_HIP_MMQ_MFMA=ON \
  -DCMAKE_BUILD_TYPE=Release

cmake --build build --config Release -j$(nproc) --target llama-cli llama-server llama-bench llama-perplexity

Phase 8: Download Models

11.1 ROCmFP4 Model (14 GB)

mkdir -p /models/rocmfp4
cd /models/rocmfp4

wget 'https://huggingface.co/jcbtc/qwopus3.6-27b-v2-chadrock-rocmfp4-mtp/resolve/main/Qwopus3.6-27B-v2-MTP-BF16-to-ROCmFP4-STRIX_LEAN.gguf'

wget 'https://huggingface.co/jcbtc/qwopus3.6-27b-v2-chadrock-rocmfp4-mtp/resolve/main/mmproj-F32.mmproj'

Expected SHA256: 1f1c0a9d63b9b38b06fe...

(verify after download)

11.2 Qwen3.6-27B Q8 Baseline (~27 GB)

mkdir -p /models/qwen36-27b
cd /models/qwen36-27b

wget 'https://huggingface.co/bartowski/Qwen_Qwen3.6-27B-GGUF/resolve/main/Qwen3.6-27B-Q8_0.gguf'

11.3 Qwen3.6-27B Q4_K_M (~16 GB, optional additional baseline)

wget 'https://huggingface.co/bartowski/Qwen_Qwen3.6-27B-GGUF/resolve/main/Qwen3.6-27B-Q4_K_M.gguf'

Phase 9: Run Inference

12.1 Critical: The setsid

Workaround

When running llama-cli inside an lxc-attach

shell, the process receives SIGTTOU

when trying to set terminal attributes because it’s not the foreground process group. **Always use **setsid -w

to create a new session:

setsid -w bash -c '
ulimit -l unlimited
HSA_OVERRIDE_GFX_VERSION=11.5.1 \
GGML_HIP_ENABLE_UNIFIED_MEMORY=1 \
/root/rocmfp4-llama/build-strix-rocmfp4/bin/llama-cli \
  -m /models/rocmfp4/Qwopus3.6-27B-v2-MTP-BF16-to-ROCmFP4-STRIX_LEAN.gguf \
  -ngl 999 \
  -fa on \
  -dio \
  -p "Your prompt here." \
  -n 200
'

Alternatively, if you pct enter

the container and run interactively (not via lxc-attach

), the setsid

wrapper is not needed.

12.2 ROCmFP4 Model with MTP (Full Config)

HSA_OVERRIDE_GFX_VERSION=11.5.1 \
GGML_HIP_ENABLE_UNIFIED_MEMORY=1 \
/root/rocmfp4-llama/build-strix-rocmfp4/bin/llama-server \
  -m /models/rocmfp4/Qwopus3.6-27B-v2-MTP-BF16-to-ROCmFP4-STRIX_LEAN.gguf \
  --mmproj /models/rocmfp4/mmproj-F32.mmproj \
  --alias qwopus3.6-27b-v2-chadrock \
  --host 127.0.0.1 \
  --port 8080 \
  --jinja \
  -c 262144 \
  -ngl 999 \
  -fa on \
  -dev ROCm0 \
  -b 512 \
  -ub 512 \
  -t 16 \
  -tb 32 \
  -ctk q4_0 \
  -ctv q4_0 \
  --spec-type draft-mtp \
  --spec-draft-device ROCm0 \
  --spec-draft-ngl all \
  --spec-draft-type-k q4_0 \
  --spec-draft-type-v q4_0 \
  --spec-draft-n-max 4 \
  --spec-draft-n-min 0 \
  --spec-draft-p-min 0.0 \
  --spec-draft-p-split 0.10 \
  --parallel 1 \
  --metrics \
  --no-mmap

12.3 Q8 Baseline (Stock llama.cpp)

HSA_OVERRIDE_GFX_VERSION=11.5.1 \
GGML_HIP_ENABLE_UNIFIED_MEMORY=1 \
/root/stock-llama/build/bin/llama-cli \
  -m /models/qwen36-27b/Qwen3.6-27B-Q8_0.gguf \
  -ngl 999 \
  -fa on \
  -dio \
  -p "Your prompt here." \
  -n 200

12.4 Runtime Flag Reference

Phase 10: Benchmarks

13.1 ROCmFP4 Model Benchmark

setsid -w bash -c '
ulimit -l unlimited
HSA_OVERRIDE_GFX_VERSION=11.5.1 \
GGML_HIP_ENABLE_UNIFIED_MEMORY=1 \
/root/rocmfp4-llama/build-strix-rocmfp4/bin/llama-bench \
  -m /models/rocmfp4/Qwopus3.6-27B-v2-MTP-BF16-to-ROCmFP4-STRIX_LEAN.gguf \
  -ngl 999 \
  -fa on \
  -dio \
  -n 512 \
  -p 512
'

13.2 Q8 Baseline Benchmark

setsid -w bash -c '
ulimit -l unlimited
HSA_OVERRIDE_GFX_VERSION=11.5.1 \
GGML_HIP_ENABLE_UNIFIED_MEMORY=1 \
/root/stock-llama/build/bin/llama-bench \
  -m /models/qwen36-27b/Qwen3.6-27B-Q8_0.gguf \
  -ngl 999 \
  -fa on \
  -dio \
  -n 512 \
  -p 512
'

13.3 Large Context Test

setsid -w bash -c '
ulimit -l unlimited
HSA_OVERRIDE_GFX_VERSION=11.5.1 \
GGML_HIP_ENABLE_UNIFIED_MEMORY=1 \
/root/rocmfp4-llama/build-strix-rocmfp4/bin/llama-bench \
  -m /models/rocmfp4/Qwopus3.6-27B-v2-MTP-BF16-to-ROCmFP4-STRIX_LEAN.gguf \
  -ngl 999 \
  -fa on \
  -dio \
  -p 32768 \
  -n 128
'

13.4 MTP Speedup Test

Compare with and without --spec-type draft-mtp

to measure speculative decoding benefit.

vLLM Docker Setup (Alternative Backend)

vLLM provides a production-grade serving backend. On Strix Halo, it requires the ROCm Docker image and the HSA_OVERRIDE_GFX_VERSION=11.0.0

workaround.

We don’t want to run docker on the Proxmox host; we can run it in the LXC Container. I’ve skipped how to install docker in the LXC – you can follow the normal docker installation guide and it’ll work fine, just make sure you’re installing docker inside the lxc (not the Proxmox host).

i.e. run the wget get.docker.com

script from inside the LXC then run docker run hello-world

to make sure docker is working fine inside the LXC.

14.1 Pull the ROCm vLLM image

docker pull rocm/vllm:latest

14.2 Run vLLM with the Qwen3.6-27B model (HF format)

The model is already available in safetensors format at /nfs/models/Jackrong/Qwopus3.6-27B-v2/

(52 GB).

docker run -it --rm \
  --device=/dev/dri \
  --device=/dev/kfd \
  --group-add=render \
  --ipc=host \
  --network=host \
  -v /nfs/models:/models \
  -e HSA_OVERRIDE_GFX_VERSION=11.0.0 \
  -e HIP_VISIBLE_DEVICES=0 \
  rocm/vllm:latest \
  --model /models/Jackrong/Qwopus3.6-27B-v2 \
  --dtype float32 \
  --max-model-len 4096 \
  --gpu-memory-utilization 0.90

Note: vLLM on Strix Halo requires float32

— bfloat16 causes GPU hangs on current kernel/driver combos. The HSA_OVERRIDE_GFX_VERSION=11.0.0

maps gfx1151 to gfx1100 code paths.

14.3 Benchmark via vLLM

docker exec <container-id> python3 -m vllm.benchmarks.benchmark_throughput \
  --model /models/Jackrong/Qwopus3.6-27B-v2 \
  --dtype float32 \
  --num-prompts 100 \
  --input-len 512 \
  --output-len 256

Troubleshooting

If you have a problem not listed here please do comment below so I can improve the guide!

15.1 Model hangs with no output

Symptoms: llama-cli

starts but produces zero output and never completes.

Causes and fixes:

15.2 “ROCk module is not loaded” in rocminfo

The amdgpu

module is loaded but the ROCm compute path (amdkfd

) isn’t initialized.

cat /boot/config-$(uname -r) | grep CONFIG_HSA_AMD

modprobe amdkfd

ls -la /dev/kfd

15.3 “Not enough memory” errors

Check GTT size:

cat /sys/class/drm/card1/device/mem_info_gtt_total

If this shows less than ~60 GB, the amdgpu.gttsize

kernel parameter isn’t being applied:

cat /proc/cmdline | grep gttsize

If missing, re-run update-grub

and reboot.

15.4 Container can’t see GPU devices

ls -la /dev/dri/* /dev/kfd

cat /etc/pve/lxc/$CT_ID.conf | grep -E 'lxc\.(cgroup|mount)'

pct stop $CT_ID
pct start $CT_ID

15.5 Permission denied on /dev/kfd inside container

Ensure the container is privileged (unprivileged: 0

in config). If using an unprivileged container, add:

lxc.idmap: g 993 993 1

15.6 Vulkan compilation errors during build

The ROCmFP4 fork’s build script enables Vulkan by default. If you get spv

namespace errors, rebuild with Vulkan disabled:

cmake -S . -B build-strix-rocmfp4 \
  -DGGML_VULKAN=OFF \

15.7 Slow performance

Verify you’re using the ROCm backend, not CPU fallback: the log should show ggml_rocm_init
Check that GPU_TARGETS=gfx1151

was used during build

Verify flash attention is enabled: -fa on
Check GPU clock speed: rocm-smi
For first runs, kernel compilation may slow things down — subsequent runs will be faster

Reference: Key Community Resources

Appendix A: Quick-Start Script

DANGER: I am providing this for reference, but again, if it works (or doesn’t) please comment below. Thanks!

#!/bin/bash

set -euo pipefail

CT_ID=${1:-100}
CT_NAME=${2:-strix-ai}

echo "=== Step 1: Add no-subscription repos ==="
rm -f /etc/apt/sources.list.d/pve-enterprise.sources
cat > /etc/apt/sources.list.d/pve-no-subscription.sources << 'EOF'
Types: deb
URIs: http://download.proxmox.com/debian/pve
Suites: trixie
Components: pve-no-subscription
Signed-By: /usr/share/keyrings/proxmox-archive-keyring.gpg
EOF
apt update

echo "=== Step 2: Add boot parameters ==="
sed -i 's/GRUB_CMDLINE_LINUX_DEFAULT="quiet"/GRUB_CMDLINE_LINUX_DEFAULT="quiet amd_iommu=off amdgpu.gttsize=131072 ttm.pages_limit=31457280"/' /etc/default/grub
update-grub

echo "=== Step 3: Download LXC template ==="
pveam download local ubuntu-24.04-standard_24.04-2_amd64.tar.zst

echo "=== Step 4: Create container ==="
pct create $CT_ID local:vztmpl/ubuntu-24.04-standard_24.04-2_amd64.tar.zst \
  --storage local-lvm \
  --memory 57344 \
  --swap 0 \
  --cores 16 \
  --unprivileged 0 \
  --hostname $CT_NAME \
  --net0 name=eth0,bridge=vmbr0,ip=dhcp \
  --rootfs local-lvm:100 \
  --features nesting=1

echo "=== Step 5: Add GPU passthrough ==="
cat >> /etc/pve/lxc/$CT_ID.conf << 'EOF'

lxc.cgroup2.devices.allow: c 226:* rwm
lxc.cgroup2.devices.allow: c 234:* rwm
lxc.mount.entry: /dev/dri dev/dri none bind,optional,create=dir
lxc.mount.entry: /dev/kfd dev/kfd none bind,optional,create=file
EOF

echo "=== Done! Reboot to apply the new kernel ==="
echo "After reboot:"
echo "  1. pct start $CT_ID"
echo "  2. pct enter $CT_ID"
echo "  3. Run the inside-container setup (ROCm + llama.cpp builds)"
echo ""
echo "Rebooting in 10 seconds... Ctrl+C to cancel."
sleep 10
reboot

Appendix B: Okay, that’s setup? Where’s my home lab?

So from here, you can setup containers or VMs or run Docker for whatever you like. Check out Proxmox VE Helper-Scripts to get some ideas.

Jellyfin Media Server | Proxmox VE Helper Scripts

Frigate | Proxmox VE Helper Scripts

Home Assistant OS | Proxmox VE Helper Scripts

…and so many more!

source & further reading

forum.level1techs.com — original article When Is It Worth Personally Preparing for AI Disasters? What should the EA community be doing now that the (AIS) Overton window has opened up again? Money Pumps for Agents Who Are Ambiguity Averse or Ambiguity Seeking

N5 Max: Proxmox Strix Halo with Docker, ROCm FP4 and MTP - Ultimate Setup Guide

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