20VC x SaaStr: Anthropic Hit $30 Billion and Training Costs a Quarter of OpenAI’s, SpaceX Files at $1.75 Trillion, and Why the Big Three Will Dwarf Every IPO of the Last 25 Years Combined

With Harry Stebbings, Jason Lemkin, and Rory O’Driscoll

Anthropic just hit $30 billion in annualized revenue. Up from $9 billion at the start of the year. That’s 3.3x growth in four months. It took Salesforce 25 years to get to $30 billion. Anthropic got there in five. Maybe three, depending on how you count.

And here’s the part that should terrify OpenAI investors: Anthropic’s training costs are a quarter of OpenAI’s. A quarter. You can explain some of that away with focus. No video generation. No consumer image products. Less of the slop. But when you’re out-accelerating your competitor on revenue AND doing it at a fraction of the cost AND the competitor is cycling through its entire management team? That’s not a code red. That’s a double code red.

Meanwhile, SpaceX confidentially filed for a $2 trillion IPO that would be the largest in history. OpenAI bought a media company nobody asked for. YC kicked out Delve for breaking the founder code. And a two-person company used AI-powered marketing to hit $1.8 billion in GLP-1 revenue by doing everything your compliance team would flag in 30 seconds.

The numbers keep getting bigger. The teams keep getting smaller. And the AI build-out continues to rain money on everyone in its path while we all quietly wonder: when does the music stop, and who’s still standing?

Key Takeaways

1. Anthropic at $30 Billion Is the Most Staggering Growth Story in Software History

Adding roughly $10 billion of net new ARR in four months while still being capacity constrained. Claude still can’t finish chats sometimes. Every engineer at every tech company has been told to consume more tokens. And they still can’t sell as much as the market wants to buy.

The supply side tells the story. Anthropic isn’t just growing into demand. They’re allocating scarce compute based on revenue optimization. That’s why they pulled open Claude out of the base plan. Heavy agentic users were consuming enormous amounts of tokens on fixed-price plans. When you can sell more than you can produce, you stop subsidizing the heaviest consumers and start pricing closer to value.

“It’s exactly what anyone in economics would tell you to do,” Rory explained. “You deemphasize things that consume huge amounts of compute for small amounts of revenue. In OpenAI’s case, that’s video. In Anthropic’s case, it’s open Claude access on fixed plans. You’re going to see a continued trend toward pricing tokens closer to the value they deliver.”

The comparison to Salesforce is almost unfair. Salesforce is the largest cloud software company on the planet. Anthropic matched its revenue in a fifth of the time. And Anthropic is still constrained by how fast it can bring data centers online. The question isn’t whether they hit $50 billion. It’s whether the estimates from two months ago even belong in the same conversation.

2. Training Costs at a Quarter of OpenAI’s Makes This a “Double Code Red”

The Wall Street Journal leaked financial details on both Anthropic and OpenAI this week. The number that jumped off the page: Anthropic’s model training costs are roughly 25% of OpenAI’s.

Focus explains part of this. Anthropic doesn’t build video products. Doesn’t do consumer image generation. Doesn’t maintain the sprawling product surface area that OpenAI has expanded into. But when you combine lower training costs with faster revenue growth, the compounding effects are devastating for the competition.

“You usually don’t have both together against your competitor,” Jason said. “You’re out-accelerating your competitor AND your training costs are a fraction of theirs. That just compounds.”

Rory drew the Uber/Lyft parallel, but noted the critical difference: “In the Uber/Lyft struggle, Uber had the ‘we’re out-accelerating’ story, but they were spending every dollar they had to do it. In this case, Anthropic is out-accelerating the opposition while being more efficient on a bunch of interesting measures. That’s a scary fact pattern.”

If both companies were public right now, the hedge fund trade would be obvious: short OpenAI at $820 billion, go long Anthropic at $370 billion. Roughly the same revenue. Better trajectory. Stronger management continuity. Half the price. And by shorting one and going long the other, you diversify away the overall AI risk and isolate a pure relative performance bet.

3. OpenAI’s Round Was “Barely Real” and Anthropic’s Valuation Looks Far More Comfortable

Dig into the OpenAI round structure and the picture gets worse. The SoftBank money comes in tranches. They have to borrow to pay it. The Amazon money is tranched partly on IPO or AGI milestones. The Nvidia money is almost entirely compute offsets, not cash. Andreessen’s money was real cash up front. And they tacked on another $10 billion that appears to have been actual dollars. But the vast bulk of the round wasn’t cash.

“That’s not a sign of strength,” Jason argued. “When the majority of the round is not cash up front, classically that’s a sign of barely getting the round done. Why wouldn’t you want $140 billion up front?”

At current revenue trajectories, Anthropic at $370 billion feels substantially more comfortable than OpenAI at $820 billion. Not a guarantee. OpenAI hasn’t released updated numbers, and they did claim $2 billion monthly in their most recent disclosure. But based on what’s public, the last-round investors in Anthropic appear to have gotten a meaningfully better deal.

4. The OpenAI Management Reboot Is Risky but Necessary

The COO moved to “special projects.” The CMO stepped down. The CRO is out. The head of apps took a leave of absence. And Denise Dresser, formerly CEO of Slack, just got handed basically everything go-to-market after being at the company for a couple months.

The changes make sense in context. When your primary competitor has radically changed the competitive posture over the last six months, you don’t sit still. The “code red” declaration three months ago didn’t magically change the trajectory. Something had to give.

But bringing in the executive with the perfect LinkedIn and handing them a massive portfolio during a period of turmoil? Jason put the success rate at about 30%. “In my experience, bringing in Mr. or Ms. Perfect LinkedIn and giving them a massive portfolio when you’re in turmoil has about a 30% chance of success. When things are executing to perfection, it always seems to work. But in turmoil, there’s not a lot of time for the get-to-know-you tour.”

The deeper concern isn’t the individual departures. It’s the signal. As Rory put it, borrowing from Oscar Wilde: “To lose one parent might be an accident. To lose both smacks of carelessness.” OpenAI is getting into carelessness territory.

5. The TBPN Acquisition Was a January Deal That Wouldn’t Happen Today

OpenAI’s acquisition of TBPN generated a lot of noise. Rory’s take was blunt: buying a media company while declaring a focus mandate is “just insane.” Not because the dollars are material. Not because it will sink the company. But because it sends exactly the wrong signal.

“OpenAI is the most known company on the planet, maybe after Apple,” Rory said. “The CEO has met every world leader. They get constant attention. In terms of media minutes, there’s nothing left to get. If you were to pick the one company that doesn’t need media attention and does need to focus, it would be OpenAI.”

The bull case exists. Jason argued for a profitable public company with trapped balance sheet cash and no ability to increase marketing spend, buying a media asset at scale can convert balance sheet into marketing. The problem: OpenAI is neither profitable nor public.

But the real meta lesson is about deal timing. The outreach happened in January. A different world. Fidji was new and thought it would be a great brand play. It took months to close. By the time it did, the management team that championed it was already changing. “There’s no way that deal happens today,” Jason said.