Direct Answer: You do not need to spend $2,000 on an NVIDIA RTX 4090 or $3,999 on a Mac Studio to run capable 70B AI models. By using multi-device memory pooling with the RAMDeck Hardware Hub, you can network the computers you already own over local Wi-Fi or Ethernet. Pooling three standard 16GB computers creates a 48GB memory cluster that loads 32B and 70B models at native local speeds with $0 in recurring cloud subscriptions.
The 400% DRAM Inflation Crisis
Consumer memory prices have skyrocketed in 2026. Standard 32GB DDR5 kits that previously retailed for $90–$120 now frequently breach $350 to $450+. The culprit is High Bandwidth Memory (HBM): semiconductor foundries have shifted silicon wafer capacity to enterprise AI accelerators, creating an acute retail memory squeeze.
Buying high-end standalone hardware at current markups is mathematically inefficient when most households already own multiple computers with 16GB of DDR4 or DDR5 RAM sitting idle.
How Sequential Layer Pooling Works
Large language models process tokens sequentially through transformer layers. Weights remain loaded in RAM; during active generation, the networked computers only pass a compact activation vector (~650 KB per token) over the network. Standard Gigabit Ethernet is more than fast enough for conversational token rates.
| Deployment Method | Memory Available | Hardware Cost | Monthly Subscriptions |
|---|---|---|---|
| Single High-End GPU Workstation | 24 GB – 48 GB | $2,200 – $4,500 | $0 |
| Proprietary Cloud APIs | Cloud Server | $0 upfront | $200 – $800 / month |
| RAMDeck Hardware Hub + Existing PCs | 48 GB – 128 GB (Pooled) | $109 (One-Time) | $0 / month |
Read the comprehensive engineering guide and benchmark tables at RAMDeck.com.
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