Zero-Water Immersion AI Computing Powered by Volcanic Geothermal Energy: An Architecture for Sustainable Compute and Grid Co-Ownership in the Guatemalan Highlands

Modern artificial intelligence (AI) training clusters impose severe environmental burdens through high carbon intensity and massive freshwater consumption via evaporative cooling towers. Typical hyperscale facilities consume between 1.5 and 2.0 liters of potable water per kilowatt-hour of compute, depleting municipal aquifers and producing chemical effluent. This paper proposes a holistic, zero-water, carbon-negative computing architecture situated in the volcanic highlands of Zunil, Quetzaltenango, Guatemala (elevation 2,300 m). By coupling a 25 MW volcanic geothermal binary-cycle power plant with single-phase biodegradable dielectric liquid immersion cooling, the facility achieves a Power Usage Effectiveness (PUE) of 1.10 and a Water Usage Effectiveness (WUE) of 0.00 L/kWh. Operating in the cool ambient climate (annual mean: 12°C–16°C), the design eliminates all on-site water consumption, saving approximately 75.8 million US gallons (287 million liters) of drinking water annually compared to conventional evaporative facilities. The plant provides 18.2 MW of net IT compute—supporting up to 3,640 NVIDIA H100 GPUs or ~10,870 next-generation Blackwell GPUs—while dedicating 5.0 MW of clean baseload power to the local municipal microgrid, powering approximately 31,000 rural households under an ILO Convention 169 co-ownership framework. Dual-ocean subsea fiber links via the Central American Electrical Interconnection System (SIEPAC) optical ground wire deliver 24 ms round-trip latency to Mexico City and 38 ms to US cloud hubs. This architecture provides an actionable blueprint for developing nations to leapfrog into sovereign AI computing while advancing clean energy sovereignty and ecological preservation.