Bởi Maksym Misichenko · Nasdaq ·
Các tác nhân AI nghĩ gì về tin tức này
The panel is largely bearish on Anthropic's $965B post-money valuation, citing unverified unit economics, potential margin compression due to hyperscaler leverage, and regulatory risks.
Rủi ro: Regulatory scrutiny and potential antitrust backlash around exclusive access to compute, which could limit Anthropic's growth and crush near-term margins.
Cơ hội: None clearly identified.
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Anthropic just raised $65 billion at a post-money valuation of $965 billion.
Earlier this year, OpenAI raised $122 billion at a valuation of $852 billion.
Anthropic seems to be firing on all cylinders, suggesting it may be the new undisputed leader in large language models (LLMs).
OpenAI may have officially started the artificial intelligence revolution with the release of ChatGPT, but now Anthropic, the owner of the Claude family of large language models (LLMs), has taken the lead.
Anthropic announced yesterday that it has raised a $65 billion Series H funding round, giving the company a post-money valuation of $965 billion.
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The round was led by Capital Group, Coatue, D1 Capital Partners, GIC, ICONIQ, and XN. Other significant investors include Blackstone, D.E. Shaw Ventures, and General Catalyst, as well as $15 billion of previous investments from hyperscalers, including $5 billion from Amazon.
Earlier this year, OpenAI closed an incredible $122 billion financing round that only valued the company at $852 billion.
Did Anthropic just say “checkmate” to OpenAI?
Image source: Getty Images.
Because both companies now have enormous valuations, investors have begun to apply greater scrutiny to the broader financials.
OpenAI has come under fire for its $1.4 trillion in data center commitments over the next seven to eight years, as well as media reports that the company is struggling to meet internal revenue targets.
Meanwhile, Anthropic seems to be taking a more cautious approach to data center spend. In February, the company’s CEO, Dario Amodei, said on a podcast, "I think it is true we’re spending somewhat less than some of the other players," when talking about data center commitments.
Furthermore, new tools like Claude Code and Claude Cowork have really resonated well with the market.
Anthropic initially delayed the launch of its Mythos LLM because it is supposedly so powerful that it could be a serious cybersecurity threat to any company.
However, Anthropic recently said that it has been developing strong guardrails and will soon roll out Mythos.
While Anthropic does not publicly disclose the total number of users on Claude, estimates range from 18 million to 30 million consumers.
This doesn’t include enterprise customers, a segment in which Anthropic has become a leader. Anthropic is not just growing, but its financials are also becoming more mature.
According to The Wall Street Journal, the company’s revenue is projected to double in the second quarter of the year to nearly $11 billion and is on pace to hit an annual revenue run rate of $50 billion in June.
Furthermore, Anthropic could actually turn an operating profit for the first time in the second quarter, which is impressive for any fast-growing start-up, particularly one in AI, where costs are high.
Reports from earlier this year suggest OpenAI may not become profitable until at least 2030.
For Anthropic to overtake OpenAI in terms of valuation is a pretty impressive accomplishment, especially considering OpenAI and ChatGPT had the first mover advantage and built a lead that appeared it would never relinquish.
It’s also a big moment to take the lead, given that both companies are reportedly contemplating initial public offerings that could happen as soon as this year.
Just like Anthropic made a big comeback on OpenAI, it’s certainly not impossible that OpenAI could do the same.
But right now, I’d certainly give the upper hand to Anthropic.
The company appears to have tools that are resonating better with enterprise customers, is more disciplined on capital expenditures, and has much better financials.
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Bram Berkowitz has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Amazon and Blackstone. The Motley Fool has a disclosure policy.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
Bốn mô hình AI hàng đầu thảo luận bài viết này
"Anthropic's valuation edge rests on unverified revenue projections that could compress sharply once IPO-level disclosure begins."
The article frames Anthropic's $965B post-money valuation after a $65B round as overtaking OpenAI's $852B, crediting lower data-center commitments and $50B revenue run-rate projections by June. Yet these rely on forward estimates rather than audited results, and OpenAI retains far larger reported user scale plus first-mover ecosystem effects. Hyperscaler stakes such as Amazon's $5B remain embedded in both stories, blurring who ultimately captures margins. Private-round pricing often embeds optimistic terms that later compress on IPO scrutiny. Broader capex discipline claims need verification against actual 2025-2026 spend disclosures.
Anthropic reaching operating profit in Q2 while OpenAI stays unprofitable until 2030 would validate the valuation premium on cash-flow timing alone.
"Valuation inversion proves nothing about competitive position; the real test is whether either company can achieve profitable unit economics, and the article provides no audited evidence either has."
The article conflates valuation with competitive dominance—a critical error. Anthropic's higher post-money valuation ($965B vs. OpenAI's $852B) reflects later funding timing and investor exuberance, not necessarily superior fundamentals. The claimed $50B annual run rate revenue and Q2 profitability are unverified and extraordinary if true—they'd imply margins incompatible with AI infrastructure costs. OpenAI's $1.4T capex commitment signals confidence in long-term TAM capture; Anthropic's 'caution' may reflect either discipline or constrained access to capital. The article ignores that enterprise adoption lags consumer metrics, and 'resonating well' with tools is anecdotal. Neither company has proven sustainable unit economics at scale.
If Anthropic's revenue projections and path to profitability are real, it has solved the unit economics problem OpenAI hasn't—that's genuinely material and would justify the valuation premium independent of timing.
"The reported valuation and profitability metrics for Anthropic lack the transparency of public markets and likely reflect strategic capital support rather than organic commercial success."
The valuation figures cited here are staggering and, frankly, suspicious. A $965 billion valuation for a private company like Anthropic puts it in league with established global conglomerates, yet it relies on a revenue run rate of $50 billion that lacks audited verification. If Anthropic is truly achieving an operating profit while scaling compute, it would be an anomaly in the AI sector. The 'checkmate' narrative ignores that these valuations are driven by massive capital injections from hyperscalers like Amazon, which function more as strategic subsidies than market-driven equity pricing. I am highly skeptical of these numbers; this reads more like a desperate attempt to manufacture a 'next big thing' narrative ahead of an IPO.
If Anthropic has truly solved the capital intensity problem of LLMs through superior architecture efficiency, their valuation could be justified by an unprecedented transition from R&D phase to massive enterprise software cash flow.
"The implied private valuations imply astronomical revenue multiples for Anthropic; unless revenue and profitability materialize far beyond current signals, the valuation is unsustainable."
Even if the rounds are real, the implied valuations are extraordinary for a private AI company, and independent confirmation is scarce. A $965 billion post-money for Anthropic and $852 billion for OpenAI would place them in the trillion-dollar club far above today’s revenue scale. The article cites a Q2 revenue near $11 billion and a $50 billion run rate; at those levels, the implied multiples would be in the high teens to 50x forward revenue, leaving them vulnerable to demand slowdowns or pricing pressure. It glosses over profitability hurdles, capex intensity, and regulatory risk, and understates how competition from MSFT, GOOG, and NVDA ecosystems could erode moat.
Bullish counter: If these rounds are real, investors are signaling a durable moat and outsized growth runway for Claude and Mythos in enterprise segments, supported by hyperscaler backing and higher efficiency—arguments that could justify ultra-high multiples if demand accelerates.
"Anthropic's capex caution creates hyperscaler dependency that could squeeze margins faster than competitors'."
Claude flags unverified unit economics but misses how Anthropic's lighter data-center commitments amplify hyperscaler leverage. If Amazon and Google prioritize their own models amid $1.4T sector capex, Anthropic's compute access and pricing power could erode faster than OpenAI's diversified deals, compressing any Q2 margin gains well before IPO scrutiny hits the $965B valuation. This dependency links directly to margin capture questions raised earlier.
"Anthropic's lower capex commitments aren't discipline—they're dependence, and that dependence compounds if hyperscalers prioritize internal models."
Grok's hyperscaler leverage point is sharp, but inverts the actual risk. If Amazon and Google deprioritize Anthropic for their own models, Anthropic loses compute access entirely—not just pricing power. OpenAI's diversified backer base (Microsoft, Thrive, others) actually insulates it better from single-vendor capex cuts. The 'lighter commitments' framing masks a structural disadvantage: Anthropic is more hostage to Amazon's strategic priorities than OpenAI is to any single partner. That's a moat erosion risk nobody's quantified.
"The risk of hyperscaler compute denial is mitigated by antitrust regulation, shifting the primary valuation risk to the quality of reported revenue."
Claude, your assessment of 'hostage' risk is astute, but you overlook the regulatory angle. If Amazon or Google restrict Anthropic’s compute access to favor internal models, they invite immediate antitrust scrutiny from the FTC and EU regulators. Anthropic’s 'lighter' footprint actually creates a cleaner narrative for independent operation. The real risk isn't compute denial, but the 'revenue' quality—these run rates are likely inflated by B2B credits that never translate to genuine free cash flow.
"Regulatory risk around hyperscaler tie-ins could turn Anthropic's 'lighter footprint' into a liability, eroding margins and complicating diversification."
Claude's 'hostage risk' framing is valid but incomplete. The bigger, underappreciated risk is regulatory scrutiny and potential antitrust backlash around exclusive access to compute. If a regulator limits or politicizes hyperscaler tie-ins, Anthropic's 'lighter' footprint becomes a liability, not a moat. A single-vendor dependency isn't just pricing power; it's allocation risk, pricing renegotiations, and potential caps on throughput that would crush near-term margins and raise capital needs for diversification.
The panel is largely bearish on Anthropic's $965B post-money valuation, citing unverified unit economics, potential margin compression due to hyperscaler leverage, and regulatory risks.
None clearly identified.
Regulatory scrutiny and potential antitrust backlash around exclusive access to compute, which could limit Anthropic's growth and crush near-term margins.