⚡⚡ PROVING THE EXPERTS WRONG! RUNNING 120B PARALLEL MODELS ON $225 OF SILICON WASTE! ⚡⚡

💥 THE MIGHTY M10 WORKBENCH 💥

⚡ A Transistor Corner Production // Host Node: ://webpagearea.com ⚡

💡 system_manifest.txt

// THE LOGIC EXPERIMENT

The common consensus among hardware enthusiasts is that running massive large language models on twelve separate 8GB legacy GPUs over a decade-old motherboard is highly impractical, if not impossible. They are right on paper... but are they right? I decided to find out.

The Reality: By leveraging a custom parallel optimization layer, this rig successfully loaded and ran GPT-OSS 120B locally at 7.70 tokens/sec using ancient DDR3 and three cheap graphics cards.

// RADICAL NAVIGATION

📷 rig_view.jpg

⚡ [PHOTO] THE COMPLETED 12-CORE MATRIX IN THE RIG ⚡

// HARDWARE TOPOLOGY & BUILD LINKS

Want to assemble this micro-cluster yourself? Track the components on eBay using the nodes below:

🛸 Graphics Matrix: [3x NVIDIA Tesla M10 on eBay] - 96GB Total VRAM Pool ($225 GPU Cost)
🔌 Motherboard Architecture: [Supermicro X9SCM-F on eBay] - LGA1155 Sandy/Ivy Bridge
📼 Storage Tier: [Server DDR3 ECC RAM on eBay] - Dirt Cheap Memory Slots
🔋 Power Architecture: [MSI MAG A750GL 750W PSU on eBay] - Fully Modular ATX 3.0
🌀 Active Card Cooling: [3D Printed Tesla M10 Fan Shrouds on eBay] - Critical for Passive Thermals
🔌 Fan Power Matrix: [SATA to 2-Pin Fan Power Adapter Cables on eBay] - Cooler Splitter Y Cables
🧬 Hard Riser Adapters: [PCI-E 8x to 16x Hard Riser Cards on eBay] - Male to Female Expander
🎗️ Flexible Riser Cable: [PCIe x16 Flexible Shielded Riser Cable on eBay] - Graphics Extension Ribbon
📐 Open Air Chassis: [ATX Open Frame PC Test Bench Case on eBay] - DIY Component Rack
🛒 Alternative 6/8-GPU Mining Frames: [ATX Open Frame Mining Rig Style on eBay] - DIY Component Rack

Disclaimer: As an eBay Partner, I earn from qualifying purchases made via the tracking nodes above at no additional cost to you. Supports the bench!

// EMPIRICAL OVERNIGHT BENCHMARKS

Model Identity	Footprint	Token Gen Speed (Eval)
gpt-oss-120b:latest	65 GB	5.83 tokens/s 🚀
qwen3.5-122b-a10b:latest	81 GB	2.71 tokens/s
gpt-oss-20b:latest	13 GB	8.14 tokens/s
deepseek-coder-v2-16b:latest	8.9 GB	12.38 tokens/s
llama3.3-70b:latest	42 GB	1.18 tokens/s

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