# 1.3 The GAIB Model: Structural Precedents and Key Differences

The GAIB model addresses the CapEx paradox by separating hardware ownership from revenue-based participation. QuantaRail applies this logic to PQC hardware; however, intellectual rigor requires acknowledging the structural differences.

*Figure 1.B — GAIB vs. QuantaRail: Structural Comparison*

<table data-header-hidden><thead><tr><th width="139.4444580078125"></th><th width="176.44439697265625"></th><th width="179.2222900390625"></th><th width="252.888916015625"></th></tr></thead><tbody><tr><td>Dimension</td><td><p>GAIB</p><p>(GPU Computing)</p></td><td>QuantaRail (PQC)</td><td>Implications</td></tr><tr><td>Demand Maturity</td><td>Proven, large-scale AI demand</td><td>Early-stage, regulation-driven</td><td>Higher demand risk; mitigated by regulatory mandates</td></tr><tr><td>Hardware Generality</td><td>GPUs are multi-purpose</td><td>qSIM is single-purpose</td><td>Higher residual value risk; offset by longer lifespan</td></tr><tr><td>Revenue Predictability</td><td>Spot + contract pricing</td><td>Primarily B2B SLA contracts</td><td>More stable; requires execution in enterprise sales</td></tr><tr><td>Market Timing</td><td>Explosive AI demand</td><td>PQC demand curve (2025–2035)</td><td>Early entry into adoption curve; first-mover advantage</td></tr><tr><td>Depreciation</td><td>18–24 months</td><td>36–48 months</td><td>Longer cycles support lending models</td></tr></tbody></table>

These differences modify the risk profile without invalidating the structural model. Longer hardware depreciation cycles and B2B SLA-based revenue structures enable more predictable cash flows, partially offsetting early-stage demand characteristics. Critically, PQC demand is driven by regulatory compliance obligations rather than discretionary market demand—making it structurally more durable than spot-driven AI compute pricing.


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