QHT, re: Inference Data Center Spare- Nvda BOM and Energy (TCO) vs QCOM solution-
This is what is so exciting about entering into this space. Nvidia racks are so wildly expensive that when QC come in with mostly competitive inference racks, but at a significant discount its a win-win all around.
DCs can get inference capabilities, QC gets revenue that was never forecasted -- so QC can undercut.
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Per Copilot- thought this was an interesting comparison.
Can you verify the reasonableness ???
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— Total Cost of Ownership (TCO) & Energy Cost Comparison: Qualcomm vs. Nvidia vs. AMD
Qualcomm’s AI250 racks deliver up to 60% lower energy cost and 45–65% lower TCO per rack compared to Nvidia Rubin and AMD MI300X, driven by LPDDR5X memory, near-memory compute, and 160 kW rack power vs. 500–600+ kW for competitors.
Total Cost of Ownership (TCO) — 3-Year Estimate per Rack
Vendor
| Platform
| CapEx (USD)
| Energy Cost (3 yrs)
| TCO (3 yrs)
| vs. QCOM AI250
| Qualcomm
| AI250
| $332,000
| ~$168,000 (160kW @ $0.04/kWh)
| $500,000
| — (baseline)
| Qualcomm
| AI200
| $211,000
| ~$168,000
| $379,000
| 24% lower TCO
| Nvidia
| Rubin NVL576
| $741,000
| ~$630,000 (600kW)
| $1.37M
| 63% higher
| Nvidia
| GH200 Grace Hopper
| $700,000
| ~$420,000 (400kW)
| $1.12M
| 55% higher
| AMD
| MI300X
| $303,000
| ~$525,000 (500kW)
| $828,000
| 39% higher
| AMD
| MI300A
| $330,000
| ~$570,000 (540kW)
| $900,000
| 45% higher
| Assumes 24/7 operation, $0.04/kWh industrial rate, 90% utilization, and 3-year amortization.
Energy Cost Breakdown (3-Year, per Rack)
Platform
| Power Draw
| Annual Energy (kWh)
| 3-Year Energy Cost
| QCOM AI250
| 160 kW
| ~1.4M kWh
| ~$168,000
| Nvidia Rubin
| 600 kW
| ~5.3M kWh
| ~$630,000
| AMD MI300X
| 500 kW
| ~4.4M kWh
| ~$525,000
|
Key Efficiency Drivers for Qualcomm
- LPDDR5X vs. HBM3/3e: Lower voltage, lower cooling load
- Near-memory compute: Reduces data movement energy
- Direct Liquid Cooling: Cuts HVAC overhead by up to 40%
- ARM-based SoC: Lower idle and orchestration power
|
