Space-based power for AI compute is closer to economic parity than many think. In this week’s analysis, we break down the true $/W of orbital power systems, compare them directly to terrestrial datacenters, and show why mass-optimized HEO architectures could already compete on cost at Starship-era launch prices.

The premium model applies real-world constellation physics to the $37B DTC TAM to show how much revenue SpaceX and ASTS can actually serve. A full supply-side Monte Carlo reveals the potential performance of the two architectures, and projects 2030 DTC coverage gap revenue.

Mach33’s open-source model estimates a $37B consumer Direct-to-Cell market in 2030, driven primarily by large middle-income regions. Modelling on a per-country basis, the analysis shows that dropout prevalence, not income, is the dominant driver of consumer DTC demand.

A breakdown of SpaceX’s 100-gigawatt per year orbital compute goal in ~5 years: the power, thermal, and hardware breakthroughs needed to make it real.

Even with Starship-era launch rates, low Earth orbit remains vastly underutilized. Mach33’s latest analysis shows that by 2100, total satellites and debris will stay well below sustainability limits, shifting the challenge from space scarcity to smarter coordination.