Analysts Make Case That SpaceX IPO Valuation at $1.77 Trillion Is Cheapest Ever
Fireside Notes summarizes an 80-minute BG2 podcast discussion with Brad Gerstner and Gavin Baker arguing the $1.77 trillion SpaceX IPO is the cheapest it will get, citing AI compute revenue from Anthropic and Google deals and orbital data center economics.
Original post · 4 min read
The $SPCX IPO prices todays at $1.77 trillion. Brad Gerstner (@altcap) and Gavin Baker (@GavinSBaker) just spent 80 minutes on @BG2Pod making the case for why that's the cheapest it's going to get.
Here are the 10 takeaways worth saving:
1. In 30 days, SpaceX added $29 billion in AI compute revenue from the Anthropic and Google deals and jumped from not being an AI hyperscaler at all to being the #4 hyperscaler globally, passing Oracle. The trailing multiple compressed from ~100x to 39x in the same window. CoreWeave, Nebius, Iron and the 50 other neoclouds VCs are funding in Silicon Valley are now competing for a smaller slice of what's left.
2. xAI's Google deal generates more operating profit per gigawatt than Anthropic, Meta, Google or OpenAI's own infrastructure. Freda at Altimeter calculated a 55% IRR on Colossus 1. Borrow at 7%, invest at 55%, the math maths. Jensen called the build itself an "N of 1": 100,000 GPUs is normally a 3-year planning cycle plus 1-year deployment. xAI did it in 19 days. Speed is literally cost.
3. The premium Google is paying SpaceX for terrestrial compute is partly a call option on orbital. They want first-in-line when space data centres go live, so they're overpaying today to lock in the relationship.
4. Orbital compute costs about $5 billion per gigawatt of capex to put GPUs in space, vs $20-25 billion per gigawatt for the non-silicon half on the ground (land, power, cooling, switchgear). Space, power and cooling are effectively free up there. The unlock is rapid two-stage reusability of Starship, which takes launch from $1,500 per kg on Falcon to $250 per kg and eventually asymptotes to the cost of fuel. Elon says 3 years, Bezos says 6, truth is probably 4-5.
5. Starlink is at less than 1% global household penetration. The forecast going from $10bn to $50bn in connectivity revenue by 2028 is still only 0.3% of the global telecom market. TAM is not the constraint.
6. The most underrated piece of the IPO is the Cursor acquisition. Cursor and Anthropic each hold more proprietary coding tokens than exist on the public internet combined. xAI bought 700-800 people and a frontier-quality coding dataset, dropped it into Colossus 2 for 3 weeks of training, and Composer 2.5 went pareto-dominant on coding 12 days ago. Grok 4.3, a 1.5 trillion parameter model, is also currently on the pareto frontier. There are now four frontier labs, not three: xAI alongside Google (Gemini 3.1 Pro), Anthropic and OpenAI.
7. Anthropic just shipped Fable 5 (Mythos with safety classifiers). Karpathy says it's SOTA on benchmarks but the real unlock is long-running tasks. Stripe refactored a 50 million line Ruby codebase in a day. Used to take many weeks with many engineers. Noam Brown's corollary: snapshot benchmarks are dead. The x-axis now has to be time, tokens or compute, because frontier models can solve most problems if you let them run long enough. Nobody has ever run Mythos for a year continuously. We may never actually know how smart any given generation is.
8. The cleanest framing of the long-running thesis: imagine Albert Einstein, no need to eat, sleep, or age, thinking about one problem in fundamental physics for one straight year. That's the case for spending $1.5 trillion a year on compute.
9. The frontier captures ~90% of AI revenue. Open source captures ~80% of tokens. Both are true. The market priced one and missed the other. The bear case last year was that cheap open-source tokens would close the gap. Six months in, the frontier is extending its lead instead.
10. Capex for the hyperscalers is moving from $1.1T to ~$1.5T by 2027 (Morgan Stanley revised up). Inference revenue is projected at $300B by 2027 with 60-70% gross margins and roughly 35% of capex going to non-revenue training runs. Brad thinks $300B is low and we end this year at $200B+. Meanwhile Nvidia has not been losing share to ASICs. Once you adjust for Anthropic on TPUs, Nvidia has held or expanded against Broadcom, AMD, Cerebras, MTIA and OpenAI's Jalapeno. Tokens-per-watt is revenue-per-watt in a power-constrained world.
Bonus: The MAG 7 added $1 trillion of revenue over the last 7 years and that produced $17 trillion of market cap. The forecast: SpaceX, Anthropic and OpenAI add the next $1 trillion in revenue in 4-5 years. Three companies, half the time.
Here are the 10 takeaways worth saving:
1. In 30 days, SpaceX added $29 billion in AI compute revenue from the Anthropic and Google deals and jumped from not being an AI hyperscaler at all to being the #4 hyperscaler globally, passing Oracle. The trailing multiple compressed from ~100x to 39x in the same window. CoreWeave, Nebius, Iron and the 50 other neoclouds VCs are funding in Silicon Valley are now competing for a smaller slice of what's left.
2. xAI's Google deal generates more operating profit per gigawatt than Anthropic, Meta, Google or OpenAI's own infrastructure. Freda at Altimeter calculated a 55% IRR on Colossus 1. Borrow at 7%, invest at 55%, the math maths. Jensen called the build itself an "N of 1": 100,000 GPUs is normally a 3-year planning cycle plus 1-year deployment. xAI did it in 19 days. Speed is literally cost.
3. The premium Google is paying SpaceX for terrestrial compute is partly a call option on orbital. They want first-in-line when space data centres go live, so they're overpaying today to lock in the relationship.
4. Orbital compute costs about $5 billion per gigawatt of capex to put GPUs in space, vs $20-25 billion per gigawatt for the non-silicon half on the ground (land, power, cooling, switchgear). Space, power and cooling are effectively free up there. The unlock is rapid two-stage reusability of Starship, which takes launch from $1,500 per kg on Falcon to $250 per kg and eventually asymptotes to the cost of fuel. Elon says 3 years, Bezos says 6, truth is probably 4-5.
5. Starlink is at less than 1% global household penetration. The forecast going from $10bn to $50bn in connectivity revenue by 2028 is still only 0.3% of the global telecom market. TAM is not the constraint.
6. The most underrated piece of the IPO is the Cursor acquisition. Cursor and Anthropic each hold more proprietary coding tokens than exist on the public internet combined. xAI bought 700-800 people and a frontier-quality coding dataset, dropped it into Colossus 2 for 3 weeks of training, and Composer 2.5 went pareto-dominant on coding 12 days ago. Grok 4.3, a 1.5 trillion parameter model, is also currently on the pareto frontier. There are now four frontier labs, not three: xAI alongside Google (Gemini 3.1 Pro), Anthropic and OpenAI.
7. Anthropic just shipped Fable 5 (Mythos with safety classifiers). Karpathy says it's SOTA on benchmarks but the real unlock is long-running tasks. Stripe refactored a 50 million line Ruby codebase in a day. Used to take many weeks with many engineers. Noam Brown's corollary: snapshot benchmarks are dead. The x-axis now has to be time, tokens or compute, because frontier models can solve most problems if you let them run long enough. Nobody has ever run Mythos for a year continuously. We may never actually know how smart any given generation is.
8. The cleanest framing of the long-running thesis: imagine Albert Einstein, no need to eat, sleep, or age, thinking about one problem in fundamental physics for one straight year. That's the case for spending $1.5 trillion a year on compute.
9. The frontier captures ~90% of AI revenue. Open source captures ~80% of tokens. Both are true. The market priced one and missed the other. The bear case last year was that cheap open-source tokens would close the gap. Six months in, the frontier is extending its lead instead.
10. Capex for the hyperscalers is moving from $1.1T to ~$1.5T by 2027 (Morgan Stanley revised up). Inference revenue is projected at $300B by 2027 with 60-70% gross margins and roughly 35% of capex going to non-revenue training runs. Brad thinks $300B is low and we end this year at $200B+. Meanwhile Nvidia has not been losing share to ASICs. Once you adjust for Anthropic on TPUs, Nvidia has held or expanded against Broadcom, AMD, Cerebras, MTIA and OpenAI's Jalapeno. Tokens-per-watt is revenue-per-watt in a power-constrained world.
Bonus: The MAG 7 added $1 trillion of revenue over the last 7 years and that produced $17 trillion of market cap. The forecast: SpaceX, Anthropic and OpenAI add the next $1 trillion in revenue in 4-5 years. Three companies, half the time.
Bg2 Pod @BG2PodBG2 w/ Gavin Baker. The SpaceX IPO, Fable 5 / Mythos, AI Capex Update & Market Check. 🚀💰 @BG2Pod @altcap @GavinSBaker @_clarktang
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