The Mach33 AI Compute Model is a market-clearing model of the AI compute build-out from 2026 to 2040, expressed twice — as a 46-tab live-formula Excel workbook and as a Python engine — with every run comparing the two across 513 values, and all 400 assumptions living in a single write-point register that carries bear/base/bull bands, evidence tiers, and sources, including explicit "Mach33 judgment — no external source" labels. Rather than being learned tab by tab, the package is built to be handed to an LLM: point a session at the folder and it runs the model, builds counterfactuals, and answers in plain English with the basis stated, with an MCP connector to live Mach33 research coming next.

Premium members - access the Mach33 SpaceX GigaModel here. If you're not a paid subscriber, you can also request access.

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.