The sharpest technical objection to SpaceX's orbital AI plan is not power or heat. It is that modern AI models are designed to run across hundreds of interconnected chips... so we model how a typical 72 GPU NVDA rack would perform as a node in comparison. Forcing a frontier model into one satellite forgoes up to 44% of achievable output. The penalty is real but not permanent, better software, slimmer models, and models designed to fit the satellite could reduce it to near parity over time.

SpaceX prices its IPO this week. At $135 a share the deal carries roughly $1.77 trillion of equity value and raises about $75 billion, the largest listing on record; SPCX begins trading on NASDAQ on June 12. Our first article opened up the model and walked through how it works, but it held back on numbers. This piece puts the IPO opening price on the page.

We have been assembling the SpaceX ‘Gigamodel’ for several months. It is a ~400-variable undertaking, projecting the three engines that matter, launch, Starlink, and AI. We are confident it is the deepest independent financial model of SpaceX available. We are continuing to fine-tune it and will soon run the Monte Carlo simulation to derive valuation output ranges. (This is to follow in the next few days, ahead of the listing.)

The full Orbital Data Center Report is the convergence of all Mach33 diligence on orbital data centers; the complete narrative for the value of ODCs. This analysis is the synthesis: terrestrial hits a grid wall, orbital crosses the cost curve as SpaceX's stack matures, and four investor gates collapse to only one operator.