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Handmade Coding

Hardware Hacking April 2026

Resurrecting a 2013 Desktop for 2026 AI Inference

How to bypass PCIe address limits to run a 16GB Blackwell GPU on an Asus B85M-E motherboard.

The "Frankenstein" Node Specs

GPU NVIDIA RTX 5060 Ti (16GB VRAM)
Motherboard Asus B85M-E (LGA 1150)
Primary Goal Dedicated Headless AI Inference (Ollama/OpenClaw)

The Challenge: PCIe Region Invalid

Modern 16GB GPUs require a memory "window" larger than what old B85 chipsets were designed to handle. Without intervention, the driver fails with a PCI-e region invalid error in dmesg.

1. BIOS Configuration

Crucial tweaks to isolate the GPU for compute-only tasks:

  • Primary Display: Set to iGPU (Force display to onboard VGA/HDMI).
  • iGPU Multi-Monitor: Enabled (Keeps the NVIDIA card visible).
  • PCIEX16_1 Speed: Gen3 (Max throughput for model loading).
  • Launch CSM: Disabled (Pure UEFI required for CUDA 12.8).

2. The Kernel Workaround

Since the BIOS can't map the memory window, we force the Linux kernel to reallocate resources:

# Edit /etc/default/grub

GRUB_CMDLINE_LINUX_DEFAULT="quiet splash pci=realloc,nocrs"

3. Results

With these flags, nvidia-smi communicates successfully. By offloading the UI to the integrated graphics, we reclaim the full 16GB VRAM for high-precision models like Gemma 4 E2B.

Update: Agent Testing Success

Following the initial hardware setup, we moved to the software stack with phenomenal results:

  • Successfully ran Gemma 4 E2B on Ollama with 100% GPU utilization.
  • Connected it as the agent model for OpenClaw and successfully interacted via chat.
  • Pulled the larger Gemma 4 E4B model and reran the exact same flow successfully!

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