Hardware Redistribution Plan, 2026-05-03¶

Date: 2026-05-03 Author: Console Claude (Opus 4.7) Purpose: Decide what to do with brother's old PC parts (Ryzen 5 2600, GTX 1660 Super 6GB, 16GB DDR4) given Finn is RAM-pressured and Console keeps OOM-cascading.

1. Current loadout and bottlenecks¶

Finn, Proxmox host (MS-01)¶

CPU: Intel i9-13900H, 14C/20T, no headroom complaint.
RAM: 32GB DDR5-5600 SODIMM (2x16GB, A-DATA CBDAD5S560016G-BAD, BANK 0 + BANK 0). Both SODIMM slots filled.
Live pressure: 19Gi used / 31Gi total / 1.7Gi free, 3.4Gi swap at probe time. ZFS ARC + 8 LXCs/VMs are saturating it.
Storage: 8TB NVMe (52% full), 24TB HDD (48% full). Not a bottleneck.
Form factor: mini-PC, no PCIe slot for full-height GPU. SODIMM-only.
Bottleneck: RAM. Period. The CPU has plenty of cores; storage has runway. Memory is what is forcing swap and starving Console.

Console, dev VM on Finn (CT 103)¶

Allocated: 4 vCPU, 11GB RAM.
This morning's incident (memory/handoffs/console-instability-2026-05-03.md): kernel OOM-killed Chrome, systemd failed to unmount, forced reboot. VS Code extensionHost was at 1.77GB and 4 minutes old. Total VS Code footprint 3.1GB / 11GB.
Bottleneck: RAM, downstream of Finn's RAM. Console's slice cannot grow without growing Finn's.

Sol, MacBook Pro M3 Max 64GB¶

RAM: 64GB unified (soldered, not upgradeable).
Role: Premiere Pro, LM Studio MLX inference, Adobe Premiere MCP server.
Bottleneck: none we can fix with hardware swaps. Apple Silicon = no parts to redistribute to or from.

Vector, Win11 primary workstation¶

Specs: unknown to Console (not probed; Vector keeps its own forge memory). Need Justin to confirm CPU / GPU / RAM / mobo platform before recommending GPU swaps. Likely AM4 or LGA1200/1700 desktop.
Role: primary workstation, Premiere alternate, VS Code Remote SSH client to Console, local GPU work.
Bottleneck: unknown, but Vector is the only box where the 1660 Super could physically install (Finn can't, Sol can't, Console is a VM).

Brother's parts (incoming)¶

CPU: AMD Ryzen 5 2600, 6C/12T, Zen+ (2018-era).
GPU: GTX 1660 Super 6GB GDDR6.
RAM: 16GB DDR4 (speed unconfirmed, assume DDR4-2666 or 3000).
Implied platform: AM4, DDR4. Cannot go into Finn (DDR5 SODIMM only). Cannot go into Sol. Can possibly go into Vector if Vector is AM4 desktop.

2. Where each part can physically land¶

Part	Finn	Console	Sol	Vector	Standalone build
Ryzen 5 2600 (AM4)	no, wrong socket + form factor	n/a, VM	no	only if Vector is AM4 + B450/X470	yes, donor for a new node
GTX 1660 Super 6GB	no, no PCIe slot	n/a	no	yes if Vector has weaker GPU	yes
16GB DDR4	no, DDR5 SODIMM only	n/a	no	only if Vector is DDR4 desktop	yes

Hard constraint: none of brother's parts fit Finn. The thing Finn actually needs (more DDR5 SODIMM) is a separate purchase.

3. Options for absorbing brother's parts¶

Option A, Standalone "forge-gpu" node¶

Build the AM4 trio into a small Ubuntu/Proxmox box on the LAN. Roles it could absorb: - Frigate object detection with CUDA YOLO, offloads from CT 108 and replaces the Coral-on-USB pattern. - Plex hardware transcoding via NVENC, offloads from CT 101. - Stable Diffusion / SDXL image gen for site assets (6GB VRAM is tight but workable on SD 1.5 + SDXL Turbo). - Local small-LLM inference with quantized 7B-class models, but 6GB VRAM is the ceiling; Sol's M3 Max remains the better LLM box. - Potential: runs as forge-gpu LXC host or bare-metal Ubuntu, Tailscale joins it to the fleet. - Need to buy: case + PSU (550W gold, ~$60-80) if brother kept his case. Plus storage, ~$40 for a 500GB NVMe if not donated. - Cost if built fresh, conservative: ~$120-180 in supporting parts.

Option B, Donate parts to Vector¶

Only works if Vector is AM4 + DDR4 + has a weaker dGPU than 1660 Super.
Action item: Justin to share Vector's current CPU / mobo / GPU / RAM. If Vector is already on a 2020+ Intel platform (LGA1200/1700) or has a 2060 or better, this option dies.
If Vector turns out to be e.g. an older AM4 box with a 1050 Ti, this is the cheapest win, $0 net.

Option C, Sell/trade for upgrades¶

Used Ryzen 5 2600 + GTX 1660 Super + 16GB DDR4 trade value: ~$200-260 on r/hardwareswap or eBay.
Buy with proceeds: used RTX 3060 12GB (~$220-260), put it in a future node. 12GB VRAM is the threshold for usable 13B-class local LLMs and serious SDXL.
Net: defer the build, end up with a GPU twice as useful.

Option D, Park for now¶

Stuff parts in storage, focus the budget on Finn's RAM upgrade (Section 4). Revisit when there's a concrete workload that needs CUDA on the LAN. Frigate runs fine without it; Plex runs fine on the i9-13900H's iGPU.

4. Recommended path forward¶

Two-step plan, ordered by leverage.

Step 1, fix Finn's RAM (urgent, $200-240, do this first)¶

This is the actual problem causing reboots and Console's instability. Brother's parts do not solve this; only DDR5 SODIMM does.

Item	Spec	Source	Cost
2x48GB DDR5-5600 SODIMM kit	Crucial CT2K48G56C46S5 or Kingston KCP556SD8K2-96	Newegg / Amazon	~$220

MS-01 official max: 64GB DDR5-5200, 2-DIMM. Community-confirmed: 96GB (2x48GB) DDR5-5600 works at 5200 MT/s. Many MS-01 owners run this kit.
Procedure: shut down Finn cleanly, swap both SODIMMs, boot. Existing 2x16GB kit becomes spare or sold ($60-80).
Result: Finn 32GB → 96GB. Console can grow from 11GB → 24-32GB. Eight Sleep poller, Plex, Frigate, Immich, n8n stop competing for the same 11GB tail. The reboot loop ends.

Step 2, decide brother's parts after Vector specs are known¶

Before recommending a path, Justin needs to confirm: 1. Vector's current CPU + mobo socket + RAM type/amount + GPU. 2. Whether brother needs the parts back as a working PC (i.e. is the goal "swap parts and return a complete build" or "absorb the parts, hand back an entirely new build"?).

Decision tree: - Vector is AM4 + DDR4 + weak GPU → Option B: 1660 Super + 16GB DDR4 into Vector, free workstation upgrade. Brother's CPU + leftover parts go to Option A or C. - Vector is already strong → Option A (standalone forge-gpu) or Option C (sell the trio, buy a 3060 12GB for a future node). Pick A if Justin wants Frigate-CUDA + SD image gen now; pick C if he'd rather wait and end up with more useful VRAM. - No clear use case in next 90 days → Option D, park the parts, revisit.

Brother's replacement build (whichever path)¶

If absorbing brother's parts, owe him a working PC. Cheapest credible options:

Tier	Parts	Cost
Reuse case + PSU + storage, replace internals	Used Ryzen 5 5600 ($90) + B450 mobo ($60 used) + 16GB DDR4-3200 ($30) + RX 6600 8GB ($170 new)	~$350
Prebuilt entry-level	HP Victus or Lenovo Legion refurb, Ryzen 5 5500 + RTX 3050 8GB	$550-700
New AM5 build	Ryzen 5 7600 + B650 + 32GB DDR5 + RX 7600, no GPU yet	$600-750

Recommended: tier-1 reuse path, lands him on a Zen 3 + RX 6600 (notable upgrade from his current 2018 Zen+ + 1660 Super), keeps his case/PSU/storage. ~$350 total, less than tier-2 prebuilt and zero waste.

5. Total cost summary (recommended path)¶

Item	Cost
Finn 96GB DDR5 kit (Step 1)	~$220
Brother's replacement parts (tier-1)	~$350
Standalone forge-gpu support parts (only if Option A)	$120-180
Subtotal, no forge-gpu build yet	~$570
Subtotal with forge-gpu build	~$700-750

Sell-off offsets: - Existing 2x16GB DDR5 kit from Finn: +$60-80 - Brother's 1660 Super + 2600 + 16GB DDR4 if Option C: +$200-260

6. Open questions for Justin¶

Vector specs, please. CPU, mobo socket, RAM type and amount, GPU model. Determines whether Option B is even on the table.
What does brother actually want back? Same parts swapped into a different shell, or a fresh build? Affects budget.
Is there a concrete CUDA workload you've been wanting? Frigate object-detect on YOLO, SDXL for site assets, local 7B LLM for n8n callouts? Picking Option A vs D hinges on whether you'd actually use it in 90 days.
Budget ceiling for the whole shuffle? $570 minimum, $750 if forge-gpu, +$350 for brother. Does that fit?

7. Don't do¶

Don't try to put any of brother's parts into Finn. Wrong socket, wrong RAM, wrong form factor.
Don't buy more 16GB DDR5 SODIMMs for Finn. The slots are already full at 2x16GB; you have to replace, not add. Buy the 2x48GB kit or don't bother.
Don't add a USB Coral to Frigate as a workaround for the 1660 Super sitting in a closet. If you have a CUDA card on the LAN, use it.
Don't skip Step 1 to chase Step 2. The reboot loop is the actual problem; brother's parts are a separate optimization.